Lupine Publishers | Automatic Sampling of Product Temperature and Moisture within a Heat Pump Apple Dryer

 Lupine Publishers | Journal of Advances in Robotics & Mechanical Engineering

Abstract

Food losses in perishable fruits are present worldwide and in many cases half of the fruit harvested is lost. Drying is the oldest and most common food conservation process that increase product shelf life. However, some nutritional properties can be lost if dryer variables are not properly controlled. Heat pump drying (HPD) is useful for food products having high initial moisture as the dryer keeps the air relative humidity beneath 20%. A monitoring system was developed to check the homogeneity of each of the apple slices within a tray. The system touches all the slices within one row, before it moves to the next one. Product moisture was measured with a bifurcated optical fiber that acquired the 950nm and 800 nm wavebands and converted them to electrical signals with photodiodes. Surface plots show moisture measurements taken once the tray was inserted and two hours later.

Keywords: Heat Pump Dryer; Apple Slices; Moisture Fiber Optic Sensing; Product Temperature Sensing

Introduction

Half of all the fruit and vegetables produced worldwide are lost or wasted, representing 1.3 billion tons annually [1]. Fruit processing is becoming necessary to avoid its spoilage. Food dehydration is a common food conservation practice for increasing fruit shelf life. This technique maintains product sensorial attributes and can be easily transported worldwide after proper packing [2]. Drying removes free water from food reducing microbial spoilage and enzymatic reactions [3]. Food drying has been extensively studied in the last years trying to obtain high drying rates while maintaining product quality [4]. Energy consumption during drying has to be optimized, meanwhile fruit texture, flavor and chemical components persist [5]. Drying consumes 10-15% of the total industrial energy demand in Canada, France, and the USA [6]. Solar and hot air drying are the most common used methods due to their simplicity, but their performance is questionable due to long drying time and poor energy efficiency [5,7,8]. Total energy consumption in drying apple slices increased with air velocity and decreased with air temperature. Its energy efficiency varied from 2.87 to 9.11% [9]. Postharvest studies in the United States indicate that 8.6% fresh apples are lost at retail and 20% at consumer level [10]. Apple dehydration methods include solar, tunnel, microwave, infrared and freeze drying [11]. Hot air circulates through trays enclosed in a cabin and the poor drying and energy efficiency depends on air speed and heaters [5-9,11,12]. High quality food use vacuum-microwave and Refractance Window drying [13] due to its better energy efficiency.
Heat pump technology has been used to dry food based on dehumidification/heating principles. Heat pump drying (HPD) has been found to be more effective in drying materials with high initial moisture and in very humid places [14]. Heat pump drying is now encountered in food industries due to its low energy consumption, minimum quality loss and high drying performance. HPD dries fruit with lower air temperature and relative humidity preserving heat-sensitive vitamins [15,16]. A system composed of a solar and a HPD dryer combination can be more efficient [17]. Solar drying can take place in daytime meanwhile heat pump drying can be effective at night. Fruit slices are introduced in trays and require from continuous temperature and moisture sampling. Single-point spectroscopy in the visible and near infrared region (Vis-NIR) [18] is a non-destructive technique used to monitor quality changes in the food industry. In a study carried out with mango it was found that at the 532 and 785 nm wavebands, moisture changes were detected [19]. Reflectance to transmittance ratios in the photosynthetic domain at 555 nm represent a cost-effective alternative for water stress and quality estimation in maize [20]. The reflectance regions at 765–784 nm, and 950–957 nm is described as water absorption wavebands [21,22]. In this paper we describe an automatic system for sampling moisture and temperature of apple slices within a heat pump dryer. A mechanism was designed to move the sensors and measure both air and product variables.

Heat Pump Dryer

The block diagram of the heat pump dryer (Figure 1) shows the refrigerant cycle being its path highlighted by a blue line. The refrigerant components are a SM120S4VC scroll compressor, a condenser, an evaporator, and an expansion valve [17]. Airflow within the drying chamber circulates through the evaporator and the condenser as shown by the black line in Figure 1. Fans make airflow circulation possible.

Figure 1: Block diagram of the heat pump dryer showing the refrigerant and drying chamber paths.

Air Temperature, Air Relative Humidity and Slice Temperature Sampling

Figure 2a: Prototype used to measure fruit temperature showing top view.

Air temperature and relative humidity were measured with DHT22 sensors (Adafruit, Australia). The sensor uses a capacitive circuit to measure air humidity and a thermistor to measure temperature. There were 5 circuits installed inside the dryer hanging between the top bar (TBAR) and the bottom bar (BBAR), (Figure 2a). These circuits were connected through an I2C connection to an Arduino UNO microcontroller, sampling air variables every minute. Dryer control based on product temperature demands less energy than with air temperature control. Therefore, a prototype was designed to measure food temperature by contact using J type thermocouples (TS1-TS4). In Figure 2 only 4 thermocouples are shown, but the prototype used five sensors per row. The main elements used by the automatic monitoring process were a linear actuator, three solenoids (S1-S3) and two rectangular bars separated by springs (SP1, SP2). The bottom bar has the thermocouples fixed (Figure 2b), and the metal rod plunger of the solenoids welded. After releasing the 120 V solenoids the sensors touch the apple slices and measure their temperature (Figure 2b). When the solenoids are energized, the bottom bar is lifted (Figure 2c) and the bars are free to move, letting a distance of 10 mm between the apple slices and thermocouples. A linear actuator (PA 15, Progressive Automations, USA) with a 12 V brushed DC motor was employed to move the thermocouple bar back and forth. Apple slices measurements were done automatically and uses a microcontroller (Arduino UNO) to provide sampling time and actuator voltage. When the TBAR is over the 5 apple slices of the first row and the solenoids are turned-off, the J-thermocouples touch the slices (Figure 2b, Figure 3). The springs will maintain the bottom bar (BBAR) down and temperature measurements of five slices are taken simultaneously at the first row. After 10 seconds, energy is supplied to the solenoids lifting the BBAR. A voltage pulse is applied to the PA-15 actuator until it arrives to the second row of apple slices, being the sampling process repeated. An optical sensor was developed (Figure 4a) to detect moisture in apple slices. Two hundred samples were acquired from random apple slices using a Vis-NIR spectrometer (USB2000+, Ocean Optics Inc. USA). After analyzing the spectral signatures with discriminant analysis, the best wavebands for moisture detection were 950 nm and 800 nm.

Figure 2b: Prototype used to measure fruit temperature showing lateral view with released solenoids.

Figure 2c: Prototype used to measure fruit temperature showing lateral view after solenoids activation.

Figure 3: Flowchart for synchronous product temperature measurement.

A light source illuminates the bifurcated optical fiber system at one end and reflected light from the sample is obtained at the other fiber end (Figure 4a). The reflected light arrives to a NIR beam splitter (mod 47-123, Edmund Scientific, USA), that outputs two identical 50R/50T reflectance and transmission optical beams (Figure 4b). Each beam is filtered by a band pass filter (mod 65-118 for 800 nm and mod 88-569 for 950 nm, Edmund Scientific, USA). The optical information is directed to photodiodes and converted to electrical signals. After amplifying the photodiode signals with two precise, zero-drift operational amplifiers (LTC1050, Linear Technology Inc., USA) it is acquired by an Arduino UNO microcontroller and saved in memory. The PIN photodetector (PS7- 5, First Sensor Inc., USA) was used for 800 nm detection, meanwhile a precise PIN photodiode (S1223, Hamamatsu Inc., Japan) detected the 950 wavebands. Two hundred apple samples were measured at different drying stages with the optical sensor, weighted with a balance and then dried in an oven to obtain the dry weight without water. A linear curve resulted between real and optical moisture measurements having a R2 of 0.957 (Figure 5).

Figures (4a,4b): Optical fiber sensor (a) detects apple slice moisture, being (b) composed of a beam splitter, filters, and photodiodes.

Figure 5: Optical fiber sensor measurement correlated apple slice moisture given in grams of water against grams of dried solid content.

Results

Apple slices 6 mm thick were cut filling three trays of the HPD dryer. Only the top tray was monitored as the surface over it let a space for the prototype movement. Air temperature was of 40°C and air relative humidity 20%. These measurements were taken with the DTH22 sensors and were constant during the entire 250 min drying time. Temperature measurements taken with the prototype showed apple slice variations after 90 minutes of drying (Figure 6). Temperature of the 25 slices varied from 32.4 to 33°C. The X and Y axis number represents the slice number given in cartesian format (1,1; 3,4). The first case (1,1) represents the apple slice in the first row, being at left position. The second case (3,4) shows the middle apple slice (3) of the fourth row.

Figure 6: Temperature apple slices surface plot.

Optical fiber and photodetectors have been used to monitor chemical concentrations [22]. Optical moisture measurements were taken to 25 samples positioned over the top tray. Once the dryer was hot and the trays introduced, the 25 apple slices of the top tray had moisture content values between 76 and 78% (Figure 7a). After drying for 120 minutes, the slices reduced their moisture content considerably to values within 18 and 22% (Figure 7b). The slices at (2,4; 3,2 and 4,4) were smaller and shrinked quickly [23]; optical measurements were not taken over the fruit surface and their values were below 11% [24].

Figure 7a: Moisture area plot of apple slices just introduced to the HPD dryer.

Figure 7b: Moisture area plot of apple slices two hours later.

Conclusion

This work shows an automatic system for drying apple slices. It measures temperature and moisture content of the fruit during the drying process as it can provide a better signal for energyefficient dryers. The system can include more thermocouples and use instead infrared sensors avoiding solenoid lifting and releasing. The moisture optical sensor used 800 nm and 950 nm waveband filters. The optical sensor can be transformed to measure another fruit nutrients during drying by changing the waveband of the filters.

Acknowledgements

We would like to acknowledge all the technical staff of the University that provided funding to build the prototype. As well we would like to thank MI Angel Hernandez Facundo for his help in the development of all the drawings.

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Lupine Publishers | Surgical Repair of a Neglected Patellar Tendon Rupture

 Lupine Publishers | Journal of Orthopedics and Sports Medicine

Abstract

Neglected rupture of the patellar tendon is rare, as this type of injury is typically disabling in the acute setting. We present a 31-year-old male patient who sustained a left patellar tendon rupture while playing basketball. The diagnosis of patellar tendon rupture was neglected by the patient and care was delayed by 8 months. The proximally retracted patella and distally detached patellar tendon were brought back to their anatomic positions and repaired surgically while avoiding the use of autograft or allograft tissue due to fat interposition maintaining the patellar tendon length. This case report contributes to the scarce literature on surgical management of neglected patellar tendon rupture and presents a unique radiologic appearance of a chronic patellar tendon rupture.

Keywords: Patella; Athlete; Neglected; Delayed Repair

Introduction

Neglected ruptures of the patellar tendon are defined as ruptures presenting after at least six weeks and are often difficult to repair [1]. These injuries are rare, as they are often acutely disabling, and usually occur in patients under the age of 40 [2]. Rupture of the patellar tendon usually occurs near the inferior pole of patella, and most often occurs during sporting activities [3]. Surgical management of neglected patellar tendon rupture is more technically difficult to manage than acute ruptures, and the results are less favorable due to quadriceps muscle atrophy, adhesions, and proximal patellar migration [4]. Many different surgical techniques have been described for reconstruction of the disrupted extensor mechanism of the knee following neglected patellar tendon rupture. In this case we describe a simple technique of direct tendon reattachment with strong Ethibond suture reinforcement to allow immediate postoperative mobilization without the need for autograft or allograft tissue.

Case Report

A 31-year-old male presented to our orthopedic clinic for evaluation of his left knee after sustaining an injury 8 months earlier while playing basketball. He was seen in an urgent care clinic immediately following his injury, but was told his patella was displaced due to edema and should improve with time. He was unable to fully extend his knee (45 degree extension lag) following the injury and was using an over-the-counter knee brace to maintain knee extension in order to ambulate. Focused examination of the left knee revealed a superiorly displaced left patella and 45° to 120° passive range of motion with crepitus throughout. There was no pain to palpation of the knee, ankle, foot, or thigh, and the patient was neurovascularly intact. He had full strength in all muscle groups except the left quadriceps, which demonstrated grade 2 out of 5 strength. A chronic left patellar tendon rupture was suspected and confirmed by MRI (Figure 1). Operative management options were discussed, including primary vs. allograft repair of the patellar tendon.

All the risks and benefits of surgery were explained to the patient in detail, which the patient understood and consented to the procedure. A left femoral nerve block was performed for postoperative pain control and to prevent contraction of the quadriceps tendon stressing the repair. Patient was positioned supine on the operating room table and a bump was placed under the left hip. A midline incision was made ending medial to the tibial tubercle. Sharp dissection was performed down through the skin and subcutaneous tissues. There was noted to be a complete rupture of the patellar tendon just distal to the inferior pole of the patella with significant scar tissue surrounding the patellar tendon. There was rupture of both the medial and lateral retinacula. Adhesions were present laterally around the patellar tendon, additionally there were adhesions from the quadriceps to the femur proximally, these adhesions were carefully released in order to achieve necessary excursion and reapproximation. There was mild chondromalacia noted on the patella and trochlea of the femur. No fracture of the patella was appreciated. At that point, the tendon edges were gently debrided several millimeters down, back to healthy-appearing tendon. The inferior pole of the patella was then prepared using a #15 scalpel blade to resect up the periosteum from the anterior patella, then a rongeur and a curette were used to prepare down to the bleeding bony surface to improve tendon healing to bone. At that point, #2 Ethibond was used to run a total of 4 strands of suture coming out proximally on the patellar tendon in a running locking-type Krackow stitch. At that point, a drill was used for pilot holes in the inferior pole of the patella. Next, a tap was used in each of the pilot holes for the 3.5 mm suture Swivelock anchors (Stryker, Kalamazoo, MI). Then, the suture limbs were passed through the Swivelock suture anchor and tension was maintained by placing a polydioxanone (PDS) suture through the quadriceps tendon and manually pulling to approximate the inferior pole to the patellar tendon. There was excellent purchase of the anchors in the patella as well as approximation of the patellar tendon to the inferior pole of the patella. The repair was felt to take up excellent tension without undue stress to about 30 degrees of knee flexion and maintained full extension. At that point, the knee was then extended and the Ethibond sutures were passed proximally into the patellar periosteum and distally into the patellar tendon to reinforce our repair. There was excellent tracking of the patella within the trochlea without subluxation. The retinaculum was repaired. Subcutaneous tissues were closed with 2-0 Vicryl followed by running 3-0 Monocryl suture for the skin. Dermabond Prineo dressing was then applied. A sterile dressing followed by an Ace wrap was then applied, followed by a knee immobilizer locked in extension. The post-operative plan was to continue weight bearing as tolerated with early rehabilitation focusing on isometric strengthening of the quadriceps. The knee was to remain in full extension for six weeks, which was achieved using a hinged brace locked in full extension for ambulation, followed by a transition to graduated range of motion over the course of 12 weeks. At 4 months, the patient achieved 121 degrees of flexion with a 5 degree extension lag. In comparison, his nonoperative leg demonstrated 125 degrees of flexion with a 5 degree extension lag. No instability was observed in varus and valgus stress testing. The patient’s Knee Society Score (KSS) was 80/100.

Figure 1: Sagittal T2-weighted magnetic resonance imaging (MRI) of the left knee revealed a patellar tendon with avulsion of its origin from the distal pole of the patella (green arrow). The degree of patellar tendon retraction was decreased due to the presence of the large amount of infrapatellar fat (white arrow).

Discussion

The major disability for our patient was an absent extensor mechanism of the left knee as a result of complete patellar tendon rupture. This was a unique presentation of a chronic patellar tendon rupture due to patient delayed presentation. Our primary goal was to restore this mechanism by repairing the patellar tendon. Patellar tendon rupture is usually unilateral and is commonly reported as a result of athletic injury [5], which were both seen in our patient. Patellar tendon rupture is acutely disabling and as such often treated primarily, however in rare cases chronic patellar tendon injuries are reported either as a result of missed injury or neglect. In our patient, the delay in treatment was due to a missed diagnosis immediately following injury by the urgent care communication. Early repair of patellar tendon ruptures is preferred and gives favorable results [3]. The results of reconstruction of neglected ruptures of the patellar tendon are less predictable because of quadriceps muscle atrophy and proximal retraction of the parapatellar soft tissues. Various reconstruction techniques, largely as case reports, have been reported by authors for neglected patellar tendon ruptures however there is no widely accepted method. Primary repair with autogenous graft augmentation using hamstring tendons or fascia lata has been most commonly seen [4]. External fixation using wires and pins has been reported as a solution for patients with an elevated patella and severe contracture of the quadriceps tendon [2]. Reconstruction with allografts consisting of an intact patellar tendon or Achilles tendon has also been used [6]. Mandelbaum et al. recommended Z lengthening for the quadriceps tendon and Z shortening for the patellar tendon with augmentation using the gracilis and semitendinosus tendons [7]. Our patient avoided the the use of allograft or autograft tissue, and a primary repair technique utilizing knotless anchors and suture tape [8]. However, given this patient’s anatomy the patellar tendon did not retract or enfold upon itself due to the presence of a large infrapatellar fat pad. Due to this presentation we were able to primarily repair his native patellar tendon. It is important to maintain the normal position of the patella intraoperatively as both patella baja and patella alta have been shown to negatively impact knee function [9]. In addition, maintaining patellar tendon length avoids any restriction of flexion or extension lag. It is also important to prevent excessive compression of the patella over the trochlea of the femur via retinacular release, which maintains smooth tracking and gliding of the patella and prevents anterior knee pain. In addition, the strength of the reconstruction can be confirmed intraoperatively with gentle passive knee movements up to 90°. This can also verify normal patella tracking over the femoral trochlea without undue pressure.

Conclusion

This case represents a unique presentation of a chronic patellar tendon rupture that presented 8 months following the injury but was still able to be repaired primarily. Additionally, we utilized suture anchors to strengthen our repair and tendon fixation into the patella.

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Lupine Publishers | Pathophysiology of Cardiovascular Complications in Obesity and Diabetes

 Lupine Publishers | Journal of Diabetes & Obesity

Introduction

According to the World Health Organization (WHO), the global incidence of obesity has nearly tripled since 1975; more than 1.9 billion adults were overweight and 650 million of those were obese in 2016. The WHO has defined obesity as an abnormal or excessive accumulation of fat that may impair health [1]. On the other hand, the number of people with diabetes rose from 108 million in 1980 to 422 million in 2014. Between 2000 and 2016, there was a 5% increase in premature mortality from diabetes and in 2019, an estimated 1.5 million deaths were directly caused by diabetes. Another 2.2 million deaths were attributable to high blood glucose in 2012 [2]. It is without any ambiguity that both these chronic metabolic diseases represent universal major health hazards and are on the rise in both developed and developing nations. It should be pointed out that type 1 diabetes involves the lack of production of insulin, whereas type 2 diabetes is due to an insulin resistance. Both types of diabetes as well as obesity lead to several health complications, including cardiovascular disease. Several books are available that provide a wealth of experimental and clinical lines of evidence indicating that both diabetes and obesity are major risk factors for the development of heart disease [3-8]. In this article we describe some of the common characteristics and features in the etiology of cardiovascular abnormalities associated with obesity and diabetes-induced cardiomyopathies [9,10].

Obesity cardiomyopathy occurs in individuals with severe and long-standing obesity that can lead to progressive congestive heart failure and increased risk of sudden cardiac death [9]. In this regard, there is an increase in total blood volume and cardiac output because of the high metabolic activity of excessive fat in obesity [9]. In moderate to severe cases of obesity this can lead to an increase in left ventricle (LV) dilation, increase in LV wall stress, compensatory LV hypertrophy and LV diastolic dysfunction. If the LV wall stress remains high then LV systolic dysfunction occurs. Likewise, diabetic cardiomyopathy presents with reduced LV ejection fraction, augmented pre-ejection time and increased LV end-diastolic pressure due high LV wall stiffness and isovolumic relaxation as well as depressed cardiac contractility [10,11]. The similarities in the major biochemical mechanisms in both diabetes and obesity are shown in (Table 1). It is our contention that the main upstream factors that lead to heart dysfunction are hormonal imbalance in diabetes-induced heart disease and excessive food intake in obesity-induced heart disease. Figure 1 shows the key downstream sequence of events that ultimately lead to cardiomyopathy in diabetes and obesity in these two metabolic diseases. It is noteworthy that sympathetic outflow is increased in both diabetic and obese subjects [11,12]. Oxidative stress and inflammation are considered to play critical roles in inducing cardiomyopathy as well as insulin resistance in diabetes and obesity [11,13-15]. Oxidative stress, inflammation and mitochondrial dysfunction (including reactive oxygen species production and energy deficiency) may be due to the effects of the upregulation of the renin angiotensin system (RAS) in these metabolic diseases [16,17].

Hyperglycemia has also been identified as the key determinant in the development of oxidative stress and cardiomyopathy in both diabetes and obesity [18,19]. The development of oxidative stress may induce defects in cardiomyocyte Ca2+-handling that attenuate cardiac function because dysregulation of Ca2+-homeostasis is known to occur in both diabetic cardiomyopathy and obesity cardiomyopathy [11,20,21]. It is pointed out that although the molecular and cellular aspects of diabetic cardiomyopathy have been studied extensively, there is relatively a paucity of information regarding the mechanisms involved in the pathogenesis of obesity cardiomyopathy and thus needs to be further explored. Furthermore, nutritional approaches involving macronutrients, have been well documented for the management and treatment of both obesity and diabetes. However, the potential of micronutrients, particularly as many of them exhibit antioxidants/anti-inflammatory actions [11,13,22], as well as pharmacological agents that exert dual antioxidant and anti-inflammatory actions [23] should be explored in preclinical trials in these pathological conditions.

Table 1: Pathogenic mechanisms that lead to cardiomyopathy in chronic obesity and diabetes.

Ref. number for each mechanism in obesity or diabetes refer to those cited in the Reference Section.

Figure 1: Schematic representation of events involved in the pathogenesis of cardiomyopathy in chronic diabetes and obesity. Hormonal imbalance in diabetes refers to the changes in plasma levels of insulin deficiency or resistance in addition to the elevated levels of other hormones such as catecholamines and angiotensin II, which are known to promote oxidative stress. FFA, free fatty acids;  - increase; - decrease.

Body mass index is related to diabetes and insulin resistance, in fact, both type 2 diabetes and obesity are associated with insulin resistance [24]. Both diabetes and obesity induce a distinct cardiac metabolic phenotype that underlie the functional abnormalities of the heart [25]; dyslipidemias are alterations to the plasma lipid profile that are often associated with both metabolic diseases [26,27]. Most patients with obesity and diabetes have hypertriglyceridemia and increased plasma levels of fatty acids (FA), which are taken up and stored in lipid droplets in the heart. Intramyocardial lipids that exceed the capacity for storage and oxidation can be lipotoxic and induce non-ischemic and nonhypertensive cardiomyopathy [28]. Type 2 diabetes and obesity are associated with systemic inflammation, generalized enlargement of fat depots and uncontrolled release of FA into the circulation [29]. The heart balances uptake, metabolism and oxidation of FA to maintain ATP production, membrane biosynthesis and lipid signaling. Under conditions where FA uptake outpaces FA oxidation and FA sequestration as triacylglycerols in lipid droplets, toxic FA metabolites such as ceramides, diacylglycerols, long-chain acyl- CoAs, and acylcarnitines can accumulate in cardiomyocytes and cause cardiomyopathy [30,31].

Metabolic derangement results in an increase in FA uptake and β-oxidation in the heart. These changes in FA metabolism have a negative effect on cardiac contractile function in both diabetes and obesity; the relation and the mechanisms of myocardial FA metabolism have been highlighted in an excellent review article by Lopaschuk et al, [25]. In addition, these researchers have examined the potential of targeting of FA metabolism as a therapeutic intervention for heart disease, which could be an important approach for the treatment/prevention of heart disease in high risk diabetic and obese individuals. It is interesting to note that following the onset of heart failure, obesity per se is associated with preserved tissue ATP and mitochondrial oxyradical production, which has been suggested to be a favorable metabolic pattern for survival [32]. It is also pointed out that sympathetic overdrive contributes to the derangement of glucose metabolism in clinical conditions such as obesity and type 2 diabetes and the increased cardiac levels of catecholamines and production of catecholamine oxidation products have been shown to result in metabolic derangements and Ca2+ -handling abnormalities [33]. Thus, targeting of the sympathetic nervous system directly may prove to be highly beneficial; an approach that could be incorporated in routine clinical practice [34].

Interestingly, there occurs a close relationship between obesity and diabetes because the metabolic derangement in obesity can be seen to lead to the occurrence of diabetes, whereas similar metabolic derangement in diabetes may result in obesity. An excellent editorial by Robert Lustig [35] has addressed this very important question of the sequence of events for insulin resistance with respect to the time-course for diabetes and obesity. It has also been argued that resistance to insulin action starts in the liver and then the pancreas secretes more insulin to make the liver do its job; this raises insulin levels in the body, promotes adipogenesis, and increases peripheral insulin resistance all at the same time. However, when the hypothalamus becomes insulin resistant first, the leptin signal is antagonized resulting in increased appetite and weight gain and eventually peripheral insulin resistance. The role of the hypothalamus-leptin axis with respect to insulin resistance and the relationship with diabetes and obesity is an important area of research and needs to be further investigated [36].

Conclusion

In conclusion, we have attempted to show that there are several common concepts and mechanisms that result in cardiomyopathy in individuals with obesity and/or diabetes. While in chronic conditions of both these metabolic diseases, the occurrence of oxidative stress and inflammation are major factors that cause insult on cardiac function. Thus, targeting these factors may prove to be highly beneficial in the prevention of downstream defects that lead to functional abnormalities in the heart in diabetes and obesity. It should also be mentioned that sex differences and ethnic variations are known to exist in the incidence of both diabetes and obesity and thus any approach to understand the etiology and disease outcomes should take these important aspects into consideration. Nonetheless, the present discussion regarding the overlap in the pathogenic mechanisms of cardiomyopathy in obesity and diabetes is indicative of their co-existence and provide scope for the examination on the cause-effect relationship between these metabolic diseases.

Acknowledgement

Infrastructural support for this work was provided by the St. Boniface Hospital Albrechtsen Research Centre.

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Lupine Publishers | Factors Influencing Stereotaxic Pulmonary Vein Isolation

 Lupine Publishers | Journal of Advancements in Cardiology Research & Reports

Abstract

Background – Catheter ablation of atrial fibrillation (AF) is performed to restore and maintain a sinus rhythm. Remote magnetic navigation system (RMNS) allows an efficient and safe procedure. Left atrial (LA) anatomic barriers of this device are not well known. Aims – This study was aimed to evaluate clinical, echocardiographic and cardiac computed tomography (CCT) anatomic LA characteristics as predictors of stereotaxic AF procedure duration. Methods – From February 2015 to April 2016, 102 symptomatic and drug refractory AF patients were consecutively enrolled in an observational, prospective trial when first AF ablation. AF Radiofrequency (RF) was performed with a RMNS using Niobe ES. Clinical endpoints and LA characteristics were reported, prospectively by a transthoracic and transesophageal echocardiography, and CCT scan. Results – Mean patient age was 5912 years old, 77% male, mean CHA2DS2VASc of 1.31.3 and mean LA surface of 236.5cm2. Procedure duration of 97.232.9 minutes and fluoroscopy duration of 13.47.9 minutes were recorded. Persistent versus paroxysmal AF (p<0.05), previous flutter ablation (p<0.01), LA dilation (p<0.05), narrow LA ridge (p=0.01), small surface area and high eccentricity of the left inferior pulmonary vein (LIPV) (p<0.01) are correlated to an increased procedure duration. Previous flutter ablation (p<0.01), persistent AF (p<0.05), LIPV eccentricity (p<0.05) and ridge width (p=0.05) were found to be independently associated with procedure duration. Conclusion – Our study is the first analyzing predictors of stereotaxic procedure duration. Narrow LA ridge, small and flattened LIPV were independently correlated with an increased procedure duration. Yet neither co-morbidity nor cardiomyopathy was associated to procedure changes.

Keywords: Atrial fibrillation ablation; pulmonary vein isolation; remote magnetic navigation; procedure duration; anatomic characteristics

Introduction

Radiofrequency ablation (RF) is a treatment of choice for atrial fibrillation (AF) because of a positive risk/benefit ratio compared to antiarrhythmic drugs [1-3].
Even if significant advances have been made over the past years regarding RF, pulmonary vein isolation (PVI) notably, several limitations remain to be overcome, such as the management of recurrences usually due to pulmonary veins (PV) reconduction, the high level of X-ray exposure and a significant risk of complications [4-6].
AF ablation is carried out in expert centers with high patient volumes. It is one of the most common procedures in electrophysiology departments (30 to 50% of total procedures) due to its prevalence and the recent guidelines [1-3]. The management of end cavity ablation in challenging clinical settings may lead to tedious and risky procedures [6,7]. and the evolvement of AF ablation indications lead to increased procedures per operator [8]. Consequently, operators are facing an increased X-ray exposition, fatigue and lack of concentration [4-6], leading to extended procedures and an increased complications risk [6, 9].
Recently, a remote magnetic navigation system (RMNS) was introduced as a way to ensure stable catheter positioning, to provide adequate tissue contact, and to reduce patient and physician X-ray exposure [10-19]. Stereotaxic procedure is supposed to reduce the usual drawbacks when manual RF, tamponade and X-ray exposure notably [10-20]. New robotic technologies seem to be as effective as manual RF [6,13,20]. Despite of ongoing RMNS improvement in order to enhance remote navigation with fast computing hardware and new motion controllers, factors influencing PVI using RMNS are not well understood [13]. Consequently, the assessment of both strengths and weaknesses of the RMNS regarding AF ablation is clinically relevant.
The aim of this study was to itemize clinical and anatomical factors influencing stereotaxic PVI duration when AF ablation.

Methods

Study population

The current trial was an observational, prospective, and blinded endpoint-assessment trial. This monocentric trial included 102 consecutive patients hospitalized for a first procedure of AF ablation in the electrophysiology department of the University Hospital of Saint-Étienne (France) from February 2015 to April 2016. All patients underwent AF ablation by a single experienced operator accustomed to stereotaxic procedures.
Inclusion criteria were: first ablation procedure due to symptomatic and drug refractory AF, be over 18 years old and collection of an oral consent. Pregnant women were excluded as patients with left atrial appendage (LAA) thrombus. The local ethics review committee approved the study.
The following data were prospectively collected: demographic patients data, comorbidities, AF background and AF therapeutic management.

Pre procedure imaging

Conventional transthoracic echocardiography (TTE) and transesophageal echocardiography (TEE) were systematically performed 24-72 hours before the ablation procedure with a commercially available system (Vivid E9, GE Healthcare, France). During TEE study, LAA was carefully analyzed to detect left atrial thrombi and spontaneous echo contrast [21].
Cardiac computed tomography (CCT) was performed using 256-slice (Somatom Definition Flash, Siemens Medical Solutions, Erlangen, Germany) scanner technologies with similar protocols in patients in a supine position during suspended end-expiration, 24h to 72h prior of the AF ablation procedure. Post-processing of cardiac computed tomographic images was performed on a dedicated advanced image processing workstation (Aquarius intuition, Tera recon, Foster City, CA). Reconstructed cardiac computed tomographic images were reviewed and interpreted by an experienced independent investigator blinded to clinical and echocardiographic data. The anatomy of PVs, LAA and left atrium (LA) ridge were assessed. CCT procedure and CT-scan data are reported in the supplementary appendix.

Ablation procedure

The procedure is detailed in the supplementary appendix. LA mapping was performed using CartoÒ 3 System (Carto® 3 system, Bio sense Webster, CA), an electromagnetic system allowing realtime Advanced Catheter Location™ and visualization of both ablation and circular mapping catheters (NaviStar® and Lasso catheters®). Once the map was completed, 3D computed tomography scan was performed in order to optimize LA reconstruction.
The RMNS (Niobe™ EPOCH, Stereotaxis Inc., St Louis, MO) employs a steerable magnetic field remotely guiding a flexible catheter [6, 9–13]. Two giant computer-controlled 1.8-ton magnets are positioned at opposite sides of the fluoroscopy table. A magnetic field of 0.08 to 0.1 Tesla is generated allowing a 3D navigation thanks to three small magnets incorporated in parallel in the RF catheter tip. The magnetic field is applied to a theoretical cardiac volume of 20cm x 20cm. Catheter movements depend on direction changes of the two magnets in relation to each other. A computerized motor drive system (Cardiodrive®, Stereotaxis Inc., St Louis, MO) advances or retracts the catheters, whilst its spatial orientation requires a computerized work station (Navigant® 2.1, Stereotaxis Inc., St Louis, MO). A constant application of the magnetic field maintains contact between the catheter tip and endocardial tissue throughout the cardiac cycle. The new generation RMNS results in faster control of the catheter, leading to potentially reduced navigation duration [22].

Procedure and fluoroscopy parameters

Skin to skin total duration was recorded for all patients. The following parameters were also recorded: X-ray duration (sec), X-ray (Gy) and indexed X-ray (Gy x cm²) procedure time. These parameters were divided in different periods: setting up, mapping and ablation period (including left and right PVI).

Statistical analysis

Continuous variables were presented as mean±SD, or median+IQR as appropriate. Categorical variables were expressed as percentage. Linear uni and multi-variate models were generated to predict procedure duration. Characteristics of each model were given at the regression parameter for each variable (b), with its 95% confidence intervals and p-value. The multiple linear regression model was built in a backward stepwise manner, selecting theoretically impacting covariates (defined by p<0.05 in the univariate analysis) to predict procedure times and X-ray patient exposure, to maximize the goodness of fit expressed as R². All analyses were performed using R (R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org).

Results

Patients

Population data are summarized in (Table 1). One hundred and two consecutive patients were prospectively included, divided into 63 paroxysmal AF (62%) and 39 persistent and long-standing AF (38%). The population characteristics were as follows: mean age of 59±12years old, 77% of male, a body mass index of 27±4.5 kg/m², mean CHA2DS2VASc of 1 [1-2], anticoagulated with non-vitamin K oral anticoagulant (81%) and without cardiomyopathy. Mean LA surface was 23±6.5 cm² and LAA normocontractility was mostly assessed.

Table 1:Patient characteristics.

Continuous variables are presented as mean±SD. Categorical variables are expressed as number (percentage). AF=atrial fibrillation; BMI=body mass index; LAA=left atrial appendage; LVEF=left ventricular ejection fraction; NOAC=non-vitamin K antagonist oral anticoagulant; sAoVTI=sub aortic velocity time integral.

Procedure features

Procedure parameters are summarized in (Table 2). A 100% acute PV isolation success was reported. Mean ablation procedure time was 97±33 minutes with a mean RF time of 66±31 minutes. Total X-ray duration was 13.4±7.9 minutes. Fluoroscopic use was mainly related to the setting up period (58%), compared to 23% of ablation procedure duration. Ablation and total duration are not different whether paroxysmal or persistent AF. Three acute complications occurred: a pericardial effusion without tamponade and two medically-treated inguinal haematomas.

Table 2:Procedure parameters.

Continuous variables are presented as mean±SD. AF=atrial fibrillation.

Univariate analysis

Clinical characteristics impacting the ablation duration No co-morbidity was associated with an increase of the AF ablation procedure or X-ray exposure duration (Table 3). On the other hand, persistent versus paroxysmal AF (p<0.05), and previous flutter ablation (p<0.01) were both risk factors associated with a with procedure duration. The left ventricular function was not associated with a change in ablation procedure duration parameters (Table 3): neither LVEF (p=0.2) nor sAoTVI (=0.6). Furthermore, mitral valve disease, whether mitral regurgitation (p=0.9) or stenosis (p=0.4), was not correlated to longer procedures.

Table 3:Impact of clinical, hemodynamic and anatomical characteristics on the procedure duration.

Univariate analysis. AF=atrial fibrillation; BMI=body mass index; LVEF=left ventricular ejection fraction; LIPV=left inferior pulmonary vein; LSPV=left superior pulmonary vein.

Anatomical characteristics impacting the ablation duration LA dilation, assessed by LA area (p<0.05) and LA volume (p<0.05), was associated to an increased procedure duration (Table 3). This association was found during the mapping poeriod of the procedure (p<0.01), but not for the setting up and ablation ones (Table 1), supplementary appendix). On the other side, wider LAA ridge was correlated with a shorter fluoroscopy duration (p=0.01). Smaller LIPV surface area (p<0.01) and higher LIPV eccentricity (p<0.01) were correlated with longer RF duration (Table 2), supplementary appendix).

Multivariate analysis

Through multivariate linear regression analysis with relevant clinical and echocardiographic features, a previous flutter ablation (p<0.01) and persistent AF (p=0.03) were found to be independently associated with total procedure duration. Furthermore, left LA fluoroscopy duration was independently influenced by LIPV eccentricity (p<0.05) and LA ridge width (p=0.05).

Discussion

Major findings

This prospective observational study suggests that no comorbidity and cardiomyopathy was associated to longer stereotaxic PVI procedures. LA dilation was correlated with increased setting up but not ablation duration. Persistent AF and previous atrial flutter are independently associated to an increased procedure duration. Only LA ridge width and LIPV anatomy influenced significantly and independently the ablation duration.

Stereotaxic procedure duration

Due to the improving indications of AF ablation, all dedicated EP departments deal with an increased daily ablation procedure. Thereby, different challenges appear: [1] decrease procedure duration leading to reduce physician fatigue and X-ray exposure and [2] optimize the management of consecutive daily procedures. As an indicator shown in (Figure 1), the procedure duration seems to be significantly shorter in the current study using stereotaxic system, compared to cry balloon and manual RF ablation in FIRE and ICE trial [23]. Indeed, manual RF ablation seems to approximately 50% longer than stereotaxic procedure, while fluoroscopy duration is 75% longer with cry balloon and 33% longer with manual RF than stereotaxic ablation. In addition to a shorter procedure, stereotaxic ablation reduces the operator tiredness and increases its accuracy by allowing a seated and comfortable procedure. However, it is important to keep in mind that all ablations were performed with an experienced operator, after a usual learning curve.

Figure 1: Procedure and fluoroscopy duration with stereotaxic ablation compared to cryoballoon and radiofrequency ablation in FIRE and ICE trial [23].

Factors influencing procedure duration (Figure 2) Clinical characteristics impacting the ablation duration. Age, sex, diabetes mellitus, vascular disease and obesity are not correlated with an increased manual RF procedure duration [24], which is consistent with our trial. Our study was the first highlighting the lack of association between body weight and procedure duration. In addition, AF radiofrequency seems to be safe despite of overweight: there is not a higher hemorrhagic and infectious complications incidence reported [25]. Yet several AF risk factors such as obesity and sleep apnea, seems to be important to maintain a sinus rhythm after AF ablation [26]. Persistent AF was associated to a longer PVI procedure, suggesting the presence of more severe LA architectural abnormalities when persistent AF. Indeed, persistent AF seems to be associated to a much more severe atrial cardiomyopathy compared to paroxysmal AF [27]. Furthermore, previous ablation of atrial flutter RF was an independent risk factor of longer ablation procedure. The interrelationship between AF and atrial flutter is still unclear [28]. But this finding suggests that patients with previous atrial flutter get a complex atrial cardiomyopathy including fibrosis [24] and atrial dilation. It could lead to a longer and less efficient IVP procedure [29].

Figure 2: Central figure: Clinical, hemodynamic and anatomical factors influencing the stereotaxic AF ablation duration.

This figure summarizes results of the univariate analysis. Image corresponds to an endocavity view of the left atrium with a septal view. AF=atrial fibrillation; AFL=atrial flutter; LIPV=left inferior pulmonary vein; LA= left atrium; LAA=left atrial appendage.

Hemodynamic characteristics impacting the ablation duration neither systolic left ventricular dysfunction nor mitral disease were correlated to a longer procedure. Since 50% of AF patients get heart failure and 25% of heart failure patients get AF [30], the efficacy and safety of the AF ablation has to be proved. Indeed, antiarrhythmic drugs fail AF patients with heart failure [31], and AF ablation could be a therapeutic key, as suggested by CASTLE-AF trial [32]. In this study, catheter ablation decreased hospitalization rate and mortality, increased left ventricular function, over midterm follow up [33]. The stereotaxic ablation seems to be an interesting strategy when heart failure, regarding the safety of the procedure and the absence of LV dysfunction and LA dilation impact in procedure duration.
Left atrial architectural features impacting the ablation duration In our study, LA dilation led to a longer procedure, with an increased mapping duration, yet no effect on stereotaxic ablation duration was reported. Stereotaxic procedure seems to overcome anatomical difficulties such as LA dilation, preventing technical difficulties because of an efficient navigation.
On the other side, a narrow ridge was a predictor of longer ablation using RMNS. The left lateral ridge is known as a uniform width or muscular thickness being narrower and thicker at the antero-superior level [34]. This area acts as a fibrillary process due to the presence of the vein of Marshall, an electrical gap between left PV and LA [35]. This area constitutes a preferential zone of PVs reconnection [36]. Manual RF procedures often fail to complete ablation line in LA ridge [37]. This study also pointed out a tough ablation in this area despite stereotaxic accurate navigation.

Clinical implications

AF catheter ablation is an efficient treatment to achieve a rhythm control strategy, regarding recent guidelines [8]. But this procedure is still challenging and needs to be more efficient and safer. RMNS may be an interesting way to achieve this goal. In this study, all procedures allow an acute PV isolation, associated to a short procedure and fluoroscopy time. Furthermore, RMNS allows an efficient navigation during PVI, regardless LA dilation and left ventricular dysfunction.
But RMNS accuracy could be improved. The Stereotaxis Magnetic Navigation System allows precise navigation with a spatial resolution of 1 degree of omni-directional deflection and 1 mm for catheter advancement and retraction, as opposed to the manual catheter manipulation and catheter movements which highly depends on the operator. RMNS leads to a stable cathetertissue contact during cardiac motion, unlike manual RF ablation [38]. This study suggests that a narrow LA ridge and a small and flattened LIPV increase overall procedure time. The knowledge of these anatomical limitations ta achieve IVP may help the engineers to work on RMNS improvements.

Study limitations

The major limitation of this observational study was its lack of randomization. However, this study included consecutive patients, prospectively, in order to prevent bias analysis. In addition, this monocentric trial was based on IVP procedures performed by a single operator. It avoids the inter-observer variability but limits the exptrapolability of the data. Finally, a new trial should be designed to test LA anatomical predictors of AF recurrences and PVs reconnection with RMNS compared to manual RF and cry balloon procedures.

Conclusion

Our study proposed to highlight predictors of stereotaxic procedure duration. Both narrow LA ridge, small and flattened left inferior PV are independently correlated with increased procedure duration. But no co-morbidity and cardiomyopathy were linked to a procedure change.

Supplementary Appendix

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Lupine Publishers | Statistical Analysis to Identify the Effect of Risk Factors on Diabetic Patients from the Sheikh Zaid Hospital Lahore

 Lupine Publishers | Journal of Current Trends on Biostatistics & Biometrics

Abstract

To identify the effect of risk factors on diabetic patients. a study was conducted among diabetic patients attending the outdoor at the Sheikh Zaid Hospital, Lahore. Data was collected by interviewing the patients using a structured questionnaire after the approval of synopsis. SPSS 23.0 was used for data entry and analysis. A sample of 100 respondents was selected by nonprobability convenient sampling. The risk factors were analyzed in a gender study of 100. Tabular form was used to represent the finding. Graphs shows the response of respondents. The Chi-Square test has been used to assess the statistical significance of risk factors for the diabetic patients. The check the normality of risk factors and then apply Mann-Whitney test to check the effect of each risk factor on diabetic patients w.r.t gender and marital status. The result found that in sheikh Zaid hospital patients only physical exercise, complications and environmental factors are affected in diabetic patients.

Keywords: Diabetic patient; questionnaire; risk factors; chi square test; mann whitney test

Introduction

Diabetes mellitus

The word “diabetes” stems from a Greek term for passing through, a reference to increased urination (polyuria), a common symptom of the disease. “Mellitus” is the Latin word for honeyed, a reference to glucose noted in the urine of diabetic patients. Diabetes mellitus is sometimes referred to as sugar diabetes but usually is simply called diabetes. Diabetes mellitus is a chronic disease caused by inherited or acquired deficiency of insulin production or resistance to action of the produced insulin. Diabetes occurs when the pancreas does not produce enough insulin (a hormone that regulates blood sugar) or alternatively, when the body cannot effectively use the insulin it produces. The overall risk of dying among people with diabetes is at least double the risk of their peers without diabetes (Setter et al., 2000). Insulin is more of an anabolic hormone rather than catabolic. Insufficient amounts of insulin or poor cellular response to insulin as well as defective insulin leads to improper handling of glucose by body cells or appropriate glucose storage in the liver and muscles. This ultimately leads to persistently high levels of blood glucose, poor protein synthesis, and other metabolic derangements. When there will be no insulin production or insulin become resistant then glucose will not be supply to the cells and remain as it is in the body. When it will not utilize by the cells then glucose level elevates in the body and cause hyperglycemic conditions in the body and the person is said to be diabetic. Following may be the reason of increased level of glucose in diabetic patients

1. No production of insulin by pancreas
2. Not enough insulin production that help in glucose supply to the cells
3. Misfunctioning of insulin known as insulin resistance

The disease has been considered as one of the major health concerns worldwide today. The increase in incidence of diabetes in developing countries follows the trend of urbanization and lifestyle changes, perhaps most importantly diet [1]. Diabetes Mellitus is the common endocrine disease and affects nearly 10% of world population. At present, 347 million people worldwide have diabetes. In 2004, an estimated 3.4 million people died from consequences of fasting high blood sugar. A similar number of deaths have been estimated for 2010. More than 80% of diabetes deaths occur in low- and middle-income countries . Many experts continued to advise strict carbohydrate restriction, with the result that most people with diabetes adopted a high fat, low carbohydrate diet. Diabetes mellitus (DM) could be a risk factor for the development and progression of liver disease.

1. Weight loss: Overly high blood sugar levels can also cause rapid weight loss, say 10 to 20 pounds over two or three months-but this is not a healthy weight loss. Because the insulin hormone is not getting glucose into the cells, where it can be used as energy, the body thinks it's starving and starts breaking down protein from the muscles as an alternate source of fuel.
2. Hunger: Recessive pangs of hunger, another sign of diabetes, can come from sharp peaks and lows in blood sugar levels. When blood sugar levels plummet, the body thinks it has not been fed and craves more of the glucose that cells need to function.
3. Slow healing: Infections, cuts, and bruises that do not heal quickly are another classic sign of diabetes. This usually happens because the blood vessels are being damaged by the excessive amounts of glucose traveling the veins and arteries. This makes it hard for blood-needed to facilitate healing-to reach different areas of the body.
4. Increased urination, excessive thirst: If you need to urinate frequently-particularly if you often must get up at night to use the bathroom-it could be a symptom of diabetes. The kidneys kick into high gear to get rid of all that extra glucose in the blood, hence the urge to relieve yourself, sometimes several times during the night. The excessive thirst means your body is trying to replenish those lost fluids.
5. Causes of diabetes: The causes of diabetes are complex and only partly understood. This disease is generally considered multifactorial, involving several predisposing conditions and risk factors. In many cases genetics, habits and environment may all contribute to a person’s diabetes. Weight and body type, Family medical history, Lack of physical activity, Carbohydrate intake, Chemical exposure, Smoking, Alcohol intake. This is blamed largely on the rise of obesity and the global spread of Western-style habits: physical inactivity along with a diet that is high in calories, processed carbohydrates, and saturated fats and insufficient in fiber rich whole foods. The aging of the population is also a factor. However, other factors, such as environment may also be contributing, because cases of autoimmune diabetes (type 1) are also becoming more common [2-10]. Experts are urging people to help stem this epidemic by getting regular exercise and controlling their diet and weight. Humans are not the only species that can develop diabetes. This disease also occurs in dogs, cats and other animals, as increasing numbers of pet owners are discovering.

Diabetic complications

The direct and indirect effects on the human vascular tree are the major source of morbidity and mortality in both type 1 and type 2 diabetes. Generally, the injurious effects of hyperglycemia are separated into macrovascular complications (coronary artery disease, peripheral arterial disease, and stroke) and microvascular complications (diabetic nephropathy, neuropathy, and retinopathy). More than half of all individuals with diabetes eventually develop neuropathy. Long-term metabolic complications of diabetes mellitus include retinopathy, nephropathy, peripheral neuropathy, amputations, and Charcot joints as well as autonomic neuropathy causing gastrointestinal, genitourinary, cardiovascular symptoms and sexual dysfunction. Diabetics are also at a greater risk atherosclerotic, cardiovascular, peripheral arterial and cerebrovascular disease. Hypertension and abnormalities of lipoprotein metabolism also accompany uncontrolled diabetes mellitus. These cardiovascular disorders are the leading cause of death in people with diabetes. Diabetes is the chief cause of end-stage renal disease, which requires treatment with dialysis or a kidney transplant. These include diabetic retinopathy, glaucoma and cataracts. Diabetes is a leading cause of visual impairment and blindness. This includes peripheral neuropathy, which often causes pain or numbness in the limbs, and autonomic neuropathy, which can impede digestion (gastroparesis) and contribute to sexual dysfunction and incontinence. Neuropathy may also impair hearing and other senses. Many studies have linked diabetes to increased risk of memory loss, dementia, Alzheimer’s disease and other cognitive deficits. Recently some researchers have suggested that Alzheimer’s disease might be “type 3 diabetes,” involving insulin resistance in the brain. Foot conditions and skin disorders, such as ulcers, make diabetes the leading cause of nontraumatic foot and leg amputations. People with diabetes are also prone to infections including periodontal disease, thrush, urinary tract infections and yeast infections [11-16]. Diabetes increases the risk of malignant tumors in the colon, pancreas, liver and several other organs. Conditions ranging from gout to osteoporosis to restless legs syndrome to myofascial pain syndrome are more common in diabetic patients than nondiabetics. Diabetes increases the risk of preeclampsia, miscarriage, stillbirth and birth defects. Many but not all the studies exploring connections between diabetes and mental illness have found increased rates of depression, anxiety and other psychological disorders in diabetic patients. In addition to chronic hyperglycemia, diabetic patients can experience acute episodes of hyperglycemia as well as hypoglycemia (low glucose).

Gestational diabetes

Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with onset or first recognition during pregnancy. The definition applies whether insulin or only diet modification is used for treatment and whether the condition persists after pregnancy. Approximately 7% of all pregnancies are complicated by GDM, resulting in more than 200,000 cases annually.

Type 1 diabetes

In type 1 diabetes, hyperglycemia occurs because of a complex disease process where genetic and environmental factors lead to an autoimmune response that remains to be fully elucidated. During this process, the pancreatic B-cells within the islets of Langerhans are destroyed, resulting in individuals with this condition relying essentially on exogenous insulin administration for survival, although a subgroup has significant residual C- peptide production. Type 1 diabetes is a disease in which the pancreas does not produce any insulin. Insulin is a hormone that helps your body to control the level of glucose (sugar) in your blood. Without insulin, glucose builds up in your blood instead of being used for energy. Your body produces glucose and gets glucose from foods like bread, potatoes, rice, pasta, milk, and fruit. An autoimmune disease in which the immune system mistakenly destroys the insulin-making beta cells of the pancreas. It typically develops more quickly than other forms of diabetes. It is usually diagnosed in children and adolescents, and sometimes in young adults. To survive, patients must administer insulin medication regularly. This form of diabetes previously encompassed by the terms insulin–dependent diabetes, Type 1 diabetes, or juvenile– onset diabetes, results from autoimmune mediated destruction of the beta cells of the pancreas. The rate of destruction is quite variable, being rapid in some individuals and slow in others. The rapidly progressive form is commonly observed in children, but also may occur in adults. The slowly progressive form generally occurs in adults and is sometimes referred to as latent autoimmune diabetes in adults (LADA) [17-26]. Markers of immune destruction, including islet cell autoantibodies, and/or autoantibodies to insulin, and autoantibodies to glutamic acid decarboxylase (GAD) are present in 85–90 % of individuals with Type 1 diabetes mellitus when fasting diabetic hyper glycaemia is initially detected.

Type 2 diabetes

Type 2 diabetes is the result of failure to produce sufficient insulin and insulin resistance. Elevated blood glucose levels are managed with reduced food intake, increased physical activity, and eventually oral medications or insulin. Type 2 diabetes is believed to affect more than 15 million adult Americans, 50% of whom are undiagnosed. It is typically diagnosed during adulthood. However, with the increasing incidence of childhood obesity and concurrent insulin resistance, the number of children diagnosed with type 2 diabetes has also increased worldwide Type 2 diabetes is Caused by insulin resistance in the liver and skeletal muscle, increased glucose production in the liver, over production of free fatty acids by fat cells and relative insulin deficiency. Insulin secretion can be decreases with gradual failure of beta cells.

Contributing factors of type 2 diabetes: Obesity, Age (onset of puberty is associated with increased insulin resistance) Lack of physical activity, Genetic predisposition, Racial/ethnic background (African American, Native American, Hispanic and Asian/Pacific Islander), Conditions associated with insulin resistance, (e.g., polycystic ovary syndrome).

Causes of type 2 diabetes: Obesity, Excess glucorticoid, Excess growth hormone, Gestational diabetes, Polycystic ovary disease, Lipodystrophy, Mutation of insulin receptor, Hemochromatosis, Blurry vision, Tingling or numbness. The most significant contributors to or causes of type 2 diabetes are diet and exercise. Obesity is a major risk-factor for diabetes.

Blurry vision: Having distorted vision and seeing floaters or occasional flashes of light are a direct result of high blood sugar levels. "Blurry vision is a refraction problem. Diabetes mellitus is group of metabolic disorders characterized by hyper glycemia, glycosuria and hyperlipemia”. In 2000 almost 177 million inhabitants of the world were affected by diabetes and in future (2025) predictable range of the people which are going to effect by the diabetes is 300 million. Type 2 diabetes is the type of diabetes in which insulin is produced but cells don’t take insulin for glucose uptake. Inactive sittings, fatness is the main cause of type 2 diabetes. Diabetes is a global problem, and its occurrence is continuously increasing in the world. Pakistan is at 7th rank in list of countries and it expected to have on 4th rank in future. Therefore, for research purpose diabetes is selected because the ratio of this disease is continuously increasing. Serum samples were collected from Sheik Zayed hospital Lahore because this hospital was nearer to Punjab University Lahore and have a separate diabetes department.

Methodology:

Study design: It was a cross-sectional study.

Setting: The Study was conducted at Diabetes Centre, Sheikh Zaid Hospital Lahore.

Selection of hospital: Shaikh Zayed Hospital is a tertiary care hospital located in Lahore, Punjab, Pakistan. It is attached with Shaikh Khalifa Bin Zayed Al-Nahyan Medical and Dental College as a teaching hospital and is part of Shaikh Zayed Medical Complex Lahore. And hospital is under Government of Pakistan. Their management will be very fine as compared other government hospitals. People believes that hospital is better than other so mostly people are coming in this hospital for their treatments so that why I use this hospital.

Target Population: All the patient came to the outpatient diabetes department of Sheikh Zaid Hospital Lahore. Who have Type 2 diabetes?

Duration of study: The duration of study was two months (02-05-2018 to 02-07-2018) after the approval of synopsis.

Sample Selection: Sample selection is one of the most vital steps for conducting a research. As the conclusion of the study is based on sample and all the inference are consequently referred to whole the population it should be a good representative to the target population.

Sampling technique: Non-probability convenient sampling technique was used for collection of data.

Sample size: 1000 cases were used in this study.

Data collection procedure: The success of the survey depends upon accuracy of the data collection. The correction of the accurate data depends upon the correct choice of survey method. After questionnaire, the next step was data collection. Face to face method was used for the collection of data keeping in mind the difficulty of locating the respondent after giving them the questionnaire. So, it was the best way to give the questionnaire to the respondent and be there for a while until the respondent fill and give it back. Respondent asks the purpose of the survey, meaning of the questions which they do not completely understand. Data were collected by suing a Performa/Questionnaire. The first part of the Performa contained information’s about the demographic characteristic of the patients while the second part contained information regarding risk factors of the disease. The collection of the accurate data depends upon the careful construction of a tool of data collection. There are some difficulties in field experience [27-34]. The respondent’s behavior was good, but some respondents refused to fill up the questionnaire. After explaining the objective of the study, they agreed to cooperate. Though at some places of the behavior of the respondents were not encouraging but it was a great experience overall.

1. Inclusion criteria: The patient came to the outpatient diabetes department agreed to provide information.
2. Exclusion criteria: Patients who are not agreeing to provide information.

Data Analysis:

Software package: Data were entered and analyzed by using SPSS (Statistical Package for Social Science) version 23.

Statistical Technique

1. Descriptive Analysis: For descriptive of variables frequency were shown in tables. Charts and graphs were given for percentages in qualitative variables.
2.  Analytical Analysis: To find the risk variable of diabetes gender wise the current section is divided in the two main components.
3. Bivariate Analysis
4. Logistic Regression

Results

Figure 1: Shows the perecentage variation among the diabetic patients with various factors from figure 4.1.1 to 4.2.41.

This study consists of 1000 subjects in which both male and female are included. There are 53 variables age, other diabetic patients in family, family members, address, marital status, gender, regarding follow doctor, type of meal, skip meal, gain weight, vision problem, wound problem, sugar fluctuation, social life, smoking, alcohol, alcohol frequently use, sanitary area, regularly use of medicine, fact of necessary exercise, fact of routine walk, daily walk, exercise, kind of exercise, time of exercise, day spend in exercise, walking time, Meals, hoteling, frequently of hoteling, use of fruits, use of milk, take care of yourself, loss weight, kidney problem, skin problem, regularly check sugar, sugar check time in a day, sugar record, sugar level, routine work, hobbies, effect of diabetes, industry area, industry type, living area, type of water, kind of medicine, use of vitamins, check-up, discuss problem with doctor, satisfaction from treatment. Figure 1 shows that out of 1000 respondents, 23(23.0%) persons have 30-45 age, 52(52.0%) persons have 46-60, 21(21.0%) persons have 61-75 and 4(4.0%) persons have 76-90. Among 23 persons who have the 30-45 age, the count (percentages) for male and female were 7(30.4%) and 16(69.6%) respectively and among 52 persons who have the 46-60 age, the count (percentages) for male and female were 16(30.8%) and 36(69.2%) respectively and among 21 persons who have 76-90 age , the count (percentages) for male and female were 4(100.0%) and 0(0.0%) respectively . Figure 1 shows that out of 1000 respondents, 25 (25.0%) persons have single while 75(75.0%) persons have married. Among 25 persons who are single , the count (percentages) for male and females were 11(44.0) and 14(56.0%) respectively and among 75 persons who are married, the count (percentages) for male and females were 28(37.3%) and 47(62.7%) respectively. Figure 1 shows that of out of 1000 respondents, 37(37.0%) persons have 1-5 family members, 47(47.0%) persons have 6-10 family members, 12(12.0%) have 11-15 family members and 4(4.0% have 16-20 family members. Among 37 persons have 1-5 family members, the count (percentages) for male and females were 18(49.6%) and 19(51.4%) respectively and among 47 persons have 6-10 family members, the count (percentages) for male and females were 19(40.4%) and 28 (59.6%) respectively and among 12 persons have 11-15 family members, the count (percentages) for male and females were 1(8.3%) and 11(91.7%) respectively and among 4 persons have 16-20 family members, the count (percentages) for male and females were 1(25.0%) and 3(75.0%). Figure 1 shows that of out of 1000 respondents, 34(34.0%) persons have 1-2 diabetic patient in family members, 8(8.0%) persons have 3-4 diabetic patient in family members, 3(3.0%) have 5-6 diabetic patient in family members and 55(55.0%) have no diabetic patient in family members. Among 34 persons have 1-2 diabetic patient in family members, the count (percentages) for male and females were 12(35.3%) and 22(64.7%) respectively and among 8 persons have 3-4 diabetic patient in family members, the count (percentages) for male and females were 0(0.0%) and 8(100.0%) respectively and among 55 persons have no diabetic patient in family members, the count (percentages) for male and females were 27(49.1%) and 28(50.9%) respectively [35-46]. Figure 1 shows that of out of 1000 respondents, 54(53.0%) persons address of towns, 3535.0%) persons have address of local areas and 11(11.0%) persons address out of Lahore. Among 54 persons address of towns, the count (percentages) for male and females were 20(37.0%) and 34(63.0%) respectively and among 35 persons address of local areas, the count (percentages) for male and females were 16(45.7%) and 19(54.3%) respectively and among 11 persons address of out of Lahore, the count (percentages) for male and females were 3(27.3%) and 8(72.7%) respectively Figure 1 shows that of out of 1000 respondents, 22(22.0%) persons that are doing smoking and 78(78.0%) persons that are not doing smoking. Among 22 that are doing smoking, the count (percentages) for male and female were 20(90.0%) and 2(9.1%) respectively and among 78 persons that are not doing smoking, the count (percentages) for males and females were 19(24.4%) and 59(75.6%) respectively Figure 1 shows that of out of 1000 respondents, 6(6.0%) persons that are taking alcohol and 94(94.0%) persons that are not taking alcohol. Among 6 that are taking alcohol, the count (percentages) for male and female were 6(100.0%) and 0(0.0%) respectively and among 94 persons that are not taking alcohol, the count (percentages) for males and females were 33(35.1%) and 61(64.5%) respectively Figure 1 shows that of out of 1000 respondents, 23(23.0%) persons that are living in rural area and 77(77.0%) persons that are living in urban area [47-53]. Among 23 that are living in rural area, the count (percentages) for male and female were 6(26.1%) and 17(73.9%) respectively and among 77 persons that are living in urban area, the count (percentages) for males and females were 33(42.9%) and 44(57.1%) respectively. Figure 2 shows that of out of 1000 respondents, 27(27.0%) persons that their area sanitary system is very good and 45(45.0%) persons that their area sanitary system is good and 17(17.0%) persons that there are a sanitary system is bad and 11(11.0%) persons that their area sanitary system is very bad. Among persons that their area sanitary system is very good, the count (percentages) for male and female were 4(14.8%) and 23(85.2%) respectively and among 45 persons that their area sanitary system is good, the count (percentages) for males and females were 27(60.0%) and 18(40.0%) respectively and among persons that there are a sanitary system is bad, the count (percentages) for male and female were 7(41.2%) and 10(58.8%) and 11 persons that their area sanitary system is very bad, the count (percentages) for male and female were 1(9.1) and 10(90.9%) respectively Figure 1 shows that of out of 1000 respondents, 42(42.0%) persons that consume tap water and 58(58.0%) persons that are consume filter water. Among 42 that are consume tap water, the count (percentages) for male and female were 15(35.7%) and 27(64.3%) respectively and among 58 persons that are consume filter water, the count (percentages) for males and females were 24(40.0%) and 36(60.0%) respectively. Figure 2 shows that of out of 1000 respondents, 25(25.0%) persons that are living in industrial area and 75(75.0%) persons that are not living in industrial area. Among 26 that are living in industrial area, the count (percentages) for male and female were 10(40.0%) and 15(60.0%) respectively and among 75 persons that are not living in industrial area, the count (percentages) for males and females were 29(38.7%) and 46(61.3%) respectively Figure 2 shows that of out of 1000 respondents, 80(80.0%) persons think that exercise is necessary for diabetic patients, 17(17.0%) persons thought that exercise is not necessary for diabetic patients and 3(3.0%) persons have no idea that exercise is suitable or not for diabetic patients. Among 80 persons think that the exercise is necessary for diabetic patients, the count (percentages) for male and females were 31(38.8%) and 49(61.3%) respectively and among 17 persons think that exercise is not necessary for diabetic patients, the count (percentages) for male and females were 6(35.3%) and 11(64.7%) respectively and among 3 persons don’t know that exercise is necessary for diabetic patients, the count (percentages) for male and females were 2(66.7%) and 1(33.3%) respectively. Figure 2 shows that of out of 1000 respondents, 88(88.0%) persons think that routine Walk is helpful for diabetic patients, 9(9.0%) persons think that walk is not helpful for diabetic patients and 3(3.0%) persons have no idea that walk is helpful or not. Among 88 persons think that the routine walk is helpful for diabetic patients, the count (percentages) for male and females were 32(36.4%) and 56(63.6%) respectively and among 9 persons think that routine is not helpful for diabetic patients, the count (percentages) for male and females were 5(55.6%) and 4(44.4%) respectively and among 3 persons don’t know that routine walk is helpful or not for diabetic patients, the count (percentages) for male and females were 2(66.7%) and 1(33.3%) respectively.

Figure 2: this shows percentage variation in pi charts form from 4.2.1 to 4.2.11.

Figure 2 shows that of out of 1000 respondents, 67(67.0%) persons follow doctor regarding to exercise, 32(32.0%) persons do not follow doctor regarding to exercise, and 1(1.0%) persons don’t know about follow doctor regarding to exercise. Among 67 persons follow doctor regarding to exercise, the count (percentages) for male and females were 21(31.3%) and 46(68.7%) respectively and among 32 persons don’t follow doctor regarding to exercise, the count (percentages) for male and females were 18(56.3%) and 14(43.8%) respectively and among 1 persons don’t know about follow doctor regarding to exercise, the count (percentages) for male and females were 0(0.0%) and 1(100.0%) respectively Figure 2 shows that of out of 1000 respondents, 79(79.0%) persons go for daily walk, 21(21.0%) persons do not go for daily walk. Among 79 persons go for daily walk, the count (percentages) for male and females were 34(43.0%) and 45(57.0%) respectively and among 21 persons do not go for daily walk, the count (percentages) for male and females were 5(23.8%) and 16(76.2%) respectively. Figure 2 shows that of out of 1000 respondents, 80(80.0%) persons follow any kind of exercise, 20(20.0%) persons do not follow any kind of exercise. Among 80 persons follow any kind of exercise, the count (percentages) for male and females were 31(38.8%) and 49(61.3%) respectively and among 20 persons do not follow any kind of exercise, the count (percentages) for male and females were 8(40.0%) and 12(60.0%) respectively Figure 2 shows that of out of 1000 respondents, 67(67.0%) persons that follow manual exercise , 15(15.0%) persons that follow electrical exercise and 18(18.0) persons that don’t follow any manual or electrical exercise. Among 67 persons that follow manual exercise, the count (percentages) for male and females were 25(37.3%) and 42(62.7%) respectively and among 15 persons that follow electrical exercise, the count (percentages) for male and females were 6(40.0%) and 9(60.0%) respectively and among 18 persons don’t follow any manual or electrical exercise, the count (percentages) for male and females were 8(44.4%) and 10(55.6%) respectively Figure 2 shows that of out of 1000 respondents, 17(17.0%) persons that spend time in exercise 15 min, 37(37.0%) persons that spend time in exercise 30 min, 25(25.0) persons that spend time in exercise 1 hour , 6(6.0) persons that spend time in exercise 1.5 hour and 15(15.0) persons that spend no time on exercise. Among 17 persons that spend time in exercise 15 min, the count (percentages) for male and females were 3(17.6%) and 14(82.4%) respectively and among 37 persons that spend time in exercise 30 min, the count (percentages) for male and females were 19(51.4%) and 18(48.6%) respectively and among 25 persons that spend time in exercise 1 hour, the count (percentages) for male and females were 9(36.0%) and 16(64.0%) respectively and among 6 persons that spend time in exercise 1.5 hour, the count (percentages) for male and females were 1(16.7%) and 5(83.3%) respectively and among 15 persons that spend no time in exercise, the count (percentages) for male and females were 7(46.7%) and 8(53.3%) respectively

Figure 2 shows that of out of 1000 respondents, 42(42.0%) persons that spend morning in exercise, 4(4.0%) persons that spend afternoon in exercise, 31(31.0) persons that spend evening in exercise and 23(23.0%) persons spend no part of day in exercise. Among 42 persons that spend morning in exercise, the count (percentages) for male and females were 15(36.7%) and 27(64.3%) respectively and among 4 persons that spend afternoon in exercise, the count (percentages) for male and females were 2(50.0%) and 2(50.0%) respectively and among 31 persons that spend evening in exercise, the count (percentages) for male and females were 11(35.5%) and 20(64.5%) respectively and among 23 persons spend no part of day in exercise, the count (percentages) for male and females were 11(47.8%) and 12(52.2%) respectively. Figure 2 shows that of out of 1000 respondents, 52(52.0%) persons that spend morning for walk, 4(4.0%) persons that spend afternoon for walk, 23(23.0%) persons that spend evening for walk and 21(21.0%) persons spend no time for walk. Among 52 persons that spend morning for walk, the count (percentages) for male and females were 24(46.2%) and 28(53.8%) respectively and among 4 persons that spend afternoon for walk, the count (percentages) for male and females were 1(25.0%) and 3(75.0%) respectively and among 23 persons that spend evening for walk, the count (percentages) for male and females were 8(39.1%) and 14(60.9%) respectively and among 23 persons spend no time for walk, the count (percentages) for male and females were 5(23.8%) and 16(76.2%) respectively. Figure 2 shows that of out of 1000 respondents, 1(1.0%) persons that 1 time take meal in day, 19(19.0%) persons that 2 times take meal in a day, 71(71.0%) persons that 3 times take meal in a day, and 9(9.0%) persons that 4 times take meal in a day. Among 1 persons that 1 time take meal in a day, the count (percentages) for male and females were 0(0.0%) and 1(100.0%) respectively and among 19 persons that 2 times take meal in a day, the count (percentages) for male and females were 8(42.1%) and 11(57.9%) respectively and among 71 persons that 3 times take meal in a day, the count (percentages) for male and females were 25(35.2%) and 46(64.8%) respectively and among 9 persons that 4 times take meal in a day, the count (percentages) for male and females were 6(39.0%) and 3(33.3%) respectively. Figure 2 shows that of out of 1000 respondents, 74(74.0%) persons that use wheat in meal, 17(17.0%) persons that use rice in meal and 9(9.0%) persons that use fiber in meal. Among 74 persons that use wheat in meal, the count (percentages) for male and females were 33(44.6%) and 41(55.4%) respectively and among 17 persons that use rice in meal, the count (percentages) for male and females were 2(11.8%) and 15(88.2%) respectively and among 9 persons that use fiber in meal, the count (percentages) for male and females were 4(44.4%) and 5(55.6%) respectively. Figure 3 shows that of out of 1000 respondents, 37(37.0%) persons that go out for meal, 63(63.0%) persons that do not go out for meal. Among 37 persons that go out for meal, the count (percentages) for male and females were 15(40.5%) and 22(59.5%) respectively and among 63 persons that not go for meal, the count (percentages) for male and females were 24(38.%) and 39(61.9%) respectively .

Figure 3 shows that of out of 1000 respondents, 64(64.0%) persons that never go out for meal, 23(23.0%) persons that sometimes go out for meal, 8(8.0%) persons that normally go out for meal, and 5(5.0%) persons that have frequently go out for meal. Among 64 persons that never go out for meal, the count (percentages) for male and females were 25(39.1%) and 39(60.9%) respectively and among 23 persons that sometimes go out for meal, the count (percentages) for male and females were 7(30.4%) and 16(69.6%) respectively and among 8 persons that normally go out for meal, the count (percentages) for males and females were 5(62.5%) and 3(37.5%) respectively and among 5 persons that frequently go out for meal, the count (percentages) for male and female were 2(40.0%) and 3(60.0%). Figure 3 shows that of out of 1000 respondents, 41(41.0%) persons that regularly use of fruit, 20(20.0%) persons that are not use of fruit, 39(39.0%) persons that sometimes use the fruits. Among 41 persons that regularly use of fruit, the count (percentages) for male and females were 16(39.0%) and 25(61.0%) respectively and among 20 persons that are not use of fruit, the count (percentages) for male and females were 7(35.0%) and 13(65.0%) respectively and among 39 persons that sometime use of fruit, the count (percentages) for males and females were 16(41.0%) and 23(59.0%) respectively Figure 3 shows that of out of 1000 respondents, 48(48.0%) persons that regularly use of milk, 18(18.0%) persons that are not use of milk, 34(34.0%) persons that sometimes use the milk. Among 48 persons that regularly use of milk, the count (percentages) for male and females were 21(43.8%) and 27(56.3%) respectively and among 18 persons that are not use of milk, the count (percentages) for males and females were 4(22.2%) and 14(77.8%) respectively and among 34 persons that sometime use of milk, the count (percentages) for males and females were 14(41.2%) and 20(58.8%) respectively Figure 3 shows that of out of 1000 respondents, 37(37.0%) persons that skip their meal, 34(34.0%) persons that are not skip their meal, 29(29.0%) persons that response is don’t know means that persons have not in mind that they skip meal or not in routine. Among 37 persons that skip their meal, the count (percentages) for male and females were 7(18.9%) and 30(81.1%) respectively and among 34 persons that are not skip their meal, the count (percentages) for males and females were 19(55.9%) and 15(44.1%) respectively and among 29 persons that have not in mind that they skip meal or not in routine, the count (percentages) for males and females were 13(44.8%) and 16(55.2%) respectively.

Figure 3: This also shows the percentage variation in pi chart form from 4.2.12. to 4.2.40.

Figure 3 shows that of out of 1000 respondents, 71(71.0%) persons that take of their diet, 20(20.0%) persons that are not take of their diet, 9(9.0%) persons that response is don’t know means that persons have not in mind that they take of diet or not. Among 71 persons that skip their meal, the count (percentages) for male and females were 25(35.2%) and 46(64.8%) respectively and among 20 persons that are not take of their diet, the count (percentages) for males and females were 11(55.0%) and 9(45.0%) respectively and among 9 persons that have not in mind that they take of their diet or not, the count (percentages) for males and females were 3(33.3%) and 6(66.7%) respectively. Figure 3 shows that of out of 1000 respondents, 20(20.0%) persons that weight gain, 66(66.0%) persons that not weight gain, 14(14.0%) persons that response is don’t know means that persons have not know that about their weight that gain or not. Among 20 persons that gain weight, the count (percentages) for male and females were 2(10.0%) and 18(90.0%) respectively and among 66 persons that are not gain weight, the count (percentages) for males and females were 31(47.0%) and 35(53.0%) respectively and among 14 persons that don’t know that weight gain or not, the count (percentages) for males and females were 6(42.9%) and 8(57.1%) respectively. Figure 3 shows that of out of 1000 respondents, 47(47.0%) persons that weight loss, 39(39.0%) persons that not weight loss, 14(14.0%) persons that response is don’t know means that persons don’t know that about their weight that loss or not. Among 47 persons that loss weight, the count (percentages) for male and females were 18(38.3%) and 29(61.7%) respectively and among 39 persons that are not lose weight, the count (percentages) for males and females were 15(38.5%) and 24(61.5%) respectively and among 14 persons that don’t know that weight gain or not, the count (percentages) for males and females were 6(42.9%) and 8(57.1%) respectively Figure 3 shows that of out of 1000 respondents, 66(66.0%) persons that have vision problem, 29(29.0%) persons that have no vision problem and 5(5.0%) persons that response is don’t know means that persons don’t know that about their vision problem. Among 66 persons that have vision problem, the count (percentages) for male and females were 18(27.3%) and 48(72.2%) respectively and among 29 persons that have no vision problem, the count (percentages) for males and females were 17(58.6%) and 12(41.4%) respectively and among 5 persons that don’t know about their vision problem, the count (percentages) for males and females were 4(80.0%) and 1(20.0%) respectively. Figure 3 shows that of out of 1000 respondents, 18(18.0%) persons that have kidney problem, 74(74.0%) persons that have no kidney problem and 8(8.0%) persons that response is don’t know means that persons don’t know that about their kidney problem. Among 18 persons that have kidney problem, the count (percentages) for male and females were 4(22.2%) and 14(77.8%) respectively and among 74 persons that have no kidney problem, the count (percentages) for males and females were 30(40.5%) and 44(59.5%) respectively and among 8 persons that don’t know about their kidney problem, the count (percentages) for males and females were 5(62.5%) and 3(37.5%) respectively. Figure 3 shows that of out of 1000 respondents, 36(36.0%) persons that have wound healing problem, 56(56.0%) persons that have no wound healing problem and (8.0%) persons that response is don’t know means that persons don’t know that about their wound healing problem. Among 36 persons that have wound healing problem, the count (percentages) for male and females were 5(13.9%) and 31(86.1%) respectively and among 56 persons that have no wound healing problem, the count (percentages) for males and females were 29(51.8%) and 27(48.2%) respectively and among 8 persons that don’t know about their wound healing, the count (percentages) for males and females were 5(62.5%) and 3(37.5%) respectively.

Figure 3 shows that of out of 1000 respondents, 17(17.0%) persons that have skin problem, 79(79.0%) persons that have no skin problem and 4(4.0%) persons that response is don’t know means that persons don’t know that about their skin problem. Among 17 persons that have skin problem, the count (percentages) for male and females were 5(29.4%) and 12(70.6%) respectively and among 79 persons that have no skin problem, the count (percentages) for males and females were 32(40.5%) and 47(59.5%) respectively and among 4 persons that don’t know about their skin problem, the count (percentages) for males and females were 2(50.0%) and 2(20.0%) respectively Figure 3 shows that of out of 1000 respondents, 51(51.0%) persons check their sugar level regularly, 42(42.0%) persons that are not check their sugar level regularly and 7(7.0%) persons that response is don’t know means that persons don’t know that check their sugar level regularly. Among 51 persons that check their sugar level regularly, the count (percentages) for male and females were 15(29.4%) and 36(70.6%) respectively and among 42 persons that are not check their sugar level regularly, the count (percentages) for males and females were 22(52.4%) and 20(47.6%) respectively and among 7 persons that don’t know about check their sugar level regularly, the count (percentages) for males and females were 2(528.6%) and 5(71.4%) respectively Figure 3 shows that of out of 1000 respondents, 8(8.0%) persons check their sugar level once a day, 20(20.0%) persons that check their sugar level twice a day, 46(46.0%) persons that check their sugar level weekly and 8(8.0%) that check their sugar level monthly. Among 8 persons that check their sugar level once a day, the count (percentages) for male and female were 4(50.0%) and 4(50.0%) respectively and among 20 persons that check their sugar level twice a day, the count (percentages) for male and female were 7(35.0%) and 13(65.0%) respectively and among 46 persons that check their sugar level weekly, the count (percentages) for male and female were 20(43.5%) and 26(56.5%) respectively and among 8 person that check their sugar level monthly, the count(percentages) for male and female were 8(30.8%) and 18(69.2%) respectively. Figure 3 shows that of out of 1000 respondents, 52(52.0%) persons record their sugar level , 32(32.0%) persons that are not record their sugar level and 16(16.0%) persons that response is don’t know means that have not in mind that record their sugar level. Among 52 persons that record their sugar level, the count (percentages) for male and female were 19(36.5%) and 33(63.5%) respectively and among 32 persons that are not record their sugar level, the count (percentages) for males and females were 16(50.0%) and 16(50.0%) respectively and among 16 persons that don’t know means that have not in mind that record their sugar level, the count (percentages) for male and female were 4(25.0%) and 12(75.0%) respectively. Figure 3 shows that of out of 1000 respondents, 43(43.0%) persons mostly their sugar level remain normal , 39(39.0%) persons that are not their sugar level remain normal and 18(18.0%) persons that response is don’t know means that have not in mind that their sugar level remain normal. Among 43 persons that their sugar level remain normal, the count (percentages) for male and female were 18(41.9%) and 25(58.1%) respectively and among 39 persons that are not their sugar level remain normal, the count (percentages) for males and females were 14(35.9%) and 25(64.1%) respectively and among 18 persons that don’t know means that have not in mind that their sugar level remain normal, the count (percentages) for male and female were 7(38.9%) and 11(61.1%) respectively. Figure 3 shows that of out of 1000 respondents, 28(28.0%) persons never fluctuate their sugar level, 45(45.0%) persons sometimes fluctuate their sugar level and 27(27.0%) persons every time fluctuate their sugar level Among 28 persons never fluctuate their sugar level, the count (percentages) for male and female were 16(57.1%) and 12(42.9%) respectively and among 45 persons sometimes fluctuate their sugar level, the count (percentages) for males and females were 18(40.0%) and 27(60.0%) respectively and among 27 persons that every time fluctuate their sugar level, the count (percentages) for male and female were 5(18.5%) and 22(81.5%) respectively.

Figure 3 shows that of out of 1000 respondents, 52(52.0%) persons that agree that diabetes hindrance in daily activities, 31(31.0%) persons that not agree that diabetes hindrance in daily activities and 17(17.0%) persons that response answer in don’t know means they have no idea that diabetes hindrance in daily activities. Among 52 that agree that diabetes hindrance in daily activities, the count (percentages) for male and female were 20(38.5%) and 32(61.5%) respectively and among 31 persons that not agree that diabetes hindrance in daily activities, the count (percentages) for males and females were 11(35.5%) and 20(64.5%) respectively and among 17 persons that response answer in don’t know means they have no idea that diabetes hindrance in daily activities, the count (percentages) for male and female were 8(47.1%) and 9(53.9%) respectively. Figure 3 shows that of out of 1000 respondents, 50(50.0%) persons that agree that health interfere hobbies or recreational activities, 32(32.0%) persons that not agree that health interfere hobbies or recreational activities and 18(18.0%) persons that response answer in don’t know means they have no idea that health interfere hobbies or recreational activities. Among 50 that agree that health interfere hobbies or recreational activities, the count (percentages) for male and female were 16(32.0%) and 34(68.0%) respectively and among 32 persons that not agree that health interfere hobbies or recreational activities, the count (percentages) for males and females were 16(50.0%) and 16(50.0%) respectively and among 18 persons that response answer in don’t know means they have no idea that health interfere hobbies or recreational activities, the count (percentages) for male and female were 7(38.9%) and 11(61.1%) respectively. Figure 3 shows that of out of 1000 respondents, 47(47.0%) persons that agree that diabetes affected daily life, 35(35.0%) persons that not agree that diabetes affected daily life and 18(18.0%) persons that response answer in don’t know means they have no idea that diabetes affected daily life. Among 47 that agree that diabetes affected daily life, the count (percentages) for male and female were 15(31.9%) and 32(68.1%) respectively and among 35 persons that not agree that diabetes affected daily life, the count (percentages) for males and females were 17(48.6%) and 18(51.4%) respectively and among 18 persons that response answer in don’t know means they have no idea that health diabetes affected daily life, the count (percentages) for male and female were 7(38.9%) and 11(61.1%) respectively. Figure 3 shows that of out of 1000 respondents, 55(55.0%) persons that agree that health interfere in household chores, 32(32.0%) persons that not agree that health interfere in household chores and 13(13.0%) persons that response answer in don’t know means they have no idea that health interfere in household chores. Among 55 that agree that health interfere in household chores, the count (percentages) for male and female were 16(29.1%) and 39(70.9%) respectively and among 32 persons that not agree that health interfere in household chores, the count (percentages) for males and females were 16(50.0%) and 16(50.0%) respectively and among 13 persons that response answer in don’t know means they have no idea that health interfere in household chores, the count (percentages) for male and female were 7(53.8%) and 6(46.2%) respective. Figure 3 shows that of out of 1000 respondents, 37(37.0%) persons that agree that diabetes affected social life, 43(43.0%) persons that not agree that diabetes affected social life and 20(20.0%) persons that response answer in don’t know means they have no idea that diabetes affected social life. Among 37 that agree that diabetes affected social life, the count (percentages) for male and female were 6(16.2%) and 31(83.8%) respectively and among 43 persons that not agree that diabetes affected social life, the count (percentages) for males and females were 26(60.5%) and 17(39.5%) respectively and among 20 persons that response answer in don’t know means they have no idea that health diabetes affected social life, the count (percentages) for male and female were 7(35.0%) and 13(65.0%) respectively.

Figure 3 shows that of out of 1000 respondents, 0(0.0%) persons that are taking alcohol daily and 2(2.0%) persons that are taking alcohol weekly and 5(5.0%) persons that are taking alcohol monthly and 93(93.0%) persons are taking no alcohol. Among 0 that are taking alcohol daily, the count (percentages) for male and female were 0(0.0%) and 0(0.0%) respectively and among 2 persons that are taking alcohol weekly, the count (percentages) for males and females were 2(100%) and 0(0.0%) respectively and among 5 persons that are taking alcohol monthly, the count (percentages) for male and female were 4(80.0) and 1(20.0) and 93 persons that are not taking alcohol, the count (percentages) for male and female were 33(35.5) and 60(64.5) respectively. Figure 3 shows that of out of 1000 respondents, 75(75.0%) persons that are living in non- industrial area and 5(5.0%) persons that are living near the tyre industry and 3(3.0%) persons that are living near the textile industry and 5(5.0%) persons that are living near the steel mill and 12(12.0%) persons are living near the other industries. Among 75 that are living in non- industrial area, the count (percentages) for male and female were 29(38.7%) and 46(61.3%) respectively and among 5 persons that are living near the tyre industry, the count (percentages) for males and females were 3(60.0%) and 2(40.0%) respectively and among 3 persons that are living near the textile industry, the count (percentages) for male and female were 2(66.7%) and 1(33.3%) and 5 persons that are living near the steel mill, the count (percentages) for male and female were 1(20.0) and 4(80.0%) respectively and among 12 persons are living near the other industries, the count (percentages) for male and female were 4(33.3) and 8(66.7%) respectively. Figure 3 shows that of out of 1000 respondents, 27(27.0%) persons that their area sanitary system is very good and 45(45.0%) persons that their area sanitary system is good and 17(17.0%) persons that there area sanitary system is bad and 11(11.0%) persons that their area sanitary system is very bad. Among persons that their area sanitary system is very good, the count (percentages) for male and female were 4(14.8%) and 23(85.2%) respectively and among 45 persons that their area sanitary system is good, the count (percentages) for males and females were 27(60.0%) and 18(40.0%) respectively and among persons that there area sanitary system is bad, the count (percentages) for male and female were 7(41.2%) and 10(58.8%) and 11 persons that their area sanitary system is very bad, the count (percentages) for male and female were 1(9.1) and 10(90.9%) respectively. Figure 3 shows that of out of 1000 respondents, 60(60.0%) persons that taking pills in medicine, 20(20.0%) persons that are taking insulin in medicine and 20(20.0%) persons that taking combination of pills and insulin in medicine. Among 60 persons that taking pills in medicine, the count (percentages) for male and female were 24(41.4%) and 34(58.6%) respectively and among 20 persons that are taking insulin in medicine, the count (percentages) for males and females were 24(40.0%) and 36(60.0%) respectively and among 20 persons that taking combination of pills and insulin in medicine, the count (percentages) for male and female were 5(25.0%) and 15(75.0%) respectively.

Figure 3 shows that of out of 1000 respondents, 77(77.0%) persons that taking medicine regularly, 17(17.0%) persons that are not taking medicine and 6(6.0%) persons that miss sometime medicine. Among 77 persons that taking medicine regularly, the count (percentages) for male and female were 25(32.5%) and 52(67.5%) respectively and among 17 %) persons that are not taking medicine, the count (percentages) for males and females were 10(58.8%) and 7(41.2%) respectively and among 6 persons that miss sometime medicine, the count (percentages) for male and female were 4(66.7%) and 2(33.3%) respectively. Figure 3 shows that of out of 1000 respondents, 56(56.0%) persons that use of vitamins or supplements, 43(43.0%) persons that are not use of vitamins or supplements and 1(1.0%) persons that sometime use of vitamins or supplements. Among 56 that use of vitamins or supplements, the count (percentages) for male and female were 20(35.7%) and 36(64.3%) respectively and 43 persons that are not use of vitamins or supplements, the count (percentages) for males and females were 18(41.9%) and 25(58.1%) respectively among 1 persons that sometime use of vitamins or supplements, the count (percentages) for males and females were 1(100.0%) and 0(0.0%) respectively . Figure 3 shows that of out of 1000 respondents, 5(5.0%) persons that meet their doctor weekly, 70(70.0%) persons that meet their doctor monthly and 25(25.0%) persons that meet their doctor yearly. Among 5 that persons that meet their doctor weekly, the count (percentages) for male and female were 2(40.0%) and 3(60.0%) respectively and 70 persons that meet their doctor monthly, the count (percentages) for males and females were 28(40.0%) and 42(60.0%) respectively among persons that meet their doctor yearly, the count (percentages) for males and females were 9(36.0%) and 16(64.0%) respectively . Figure 3 shows that of out of 1000 respondents, 86(86.0%) persons that discuss problem in detail with doctor, 6(6.0%) persons that are not discuss problem in detail with doctor and 8(8.0%) persons that answer is don’t know means they don’t want to share that discuss in detail with doctor or not. Among 86 persons that discuss problem in detail with doctor, the count (percentages) for male and female were 34(39.5%) and 52(60.5%) respectively and among 6%) persons that are not discuss problem in detail with doctor, the count (percentages) for males and females were 2(33.3%) and 4(66.7%) respectively and among 8 persons that answer is don’t know means they don’t want to share that discuss in detail with doctor or not, the count (percentages) for male and female were 3(37.5%) and 5(62.5%) respectively.

Figure 3 shows that of out of 1000 respondents, 78(78.0%) persons that satisfied with their treatment, 12(12.0%) persons that are not satisfied with their treatment and 10(10.0%) persons that response is don’t know means they don’t want to share that are satisfied or not. Among 78 persons that satisfied with their treatment, the count (percentages) for male and female were 28(35.9%) and 50(64.1%) respectively and among 12 persons that are not satisfied with their treatment, the count (percentages) for males and females were 6(50.0%) and 6(50.0%) respectively and among 10 persons that response is don’t know means they don’t want to share that are satisfied or not, the count (percentages) for male and female were 5(50.0%) and 5(50.0%) respectively

Descriptive Analysis

In this section the frequency and percentages of the demographic, different variable of diabetes will be discussed with respect to diabetes gender. We will discuss here the frequency and percentages of demographic variables There are 1000 subjects. The debate of the results will base on the frequency, percentages.

Discussion

There were 39 males and 61 female’s people in sample of 1000. Percentage of male persons=39.0%, Percentage of female persons=61.0%. Out of 1000 respondents the number(percentage) of marital status in single and married group was 25(25.0%) and 75(75.0%) respectively. Out of 1000 respondents the number(percentage) of family members in 1-5, 6-10, 11-15 and 16-20 group was 37(37.0%),47(47.0%),12(12.0%) and 4(4.0%). Out of 1000 respondents the number(percentage) of other diabetic patient in family in 1-2, 3-4, 5-6 and No group was 34(34.0%), 8(8.0%), 3(3.0%) and 55(55.0%) respectively. Out of 1000 respondents the number(percentage) of Persons address in towns, local areas and out of Lahore group was 54(54.0%), 35(35.0%) and 11(11.0%) respectively. Out of 1000 respondents the number(percentage) of persons that following any exercise in yes and no group was 80(80.0%) and 20(20.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that have skin problem after diabetes in yes, no and don’t know group was 17(17.0%), 79(79.0%) and 4(4.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that have wound healing problem after diabetes in yes, no and don’t know group was 36(36.0%), 56(56.0%) and 8(8.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that have kidney problem after diabetes in yes, no and don’t know group was 18(18.0%), 74(74.0%) and 8(8.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that have vision problem after diabetes in yes, no and don’t know group was 66(66.0%), 29(29.0%) and 5(5.0%) respectively. Out of 1000 respondents the number(percentage) of Persons have weight loss after diabetes in yes, no and don’t know group was 47(47.0%), 39(39.0%) and 14(14.0%) respectively. Out of 1000 respondents the number(percentage) of Persons have weight gain after diabetes in yes, no and don’t know group was 20(20.0%), 66(66.0%) and 16(16.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that hoteling in yes and no group was 37(37.0%), 63(63.0%) respectively.

Out of 1000 respondents the number(percentage) of Persons that taking kind of meal in Wheat, Rice and Fiber group was 84(84.0%), 13(13.0%) and 3(3.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that number of taken meal in a day in 1, 2, 3 and 4 group were 1(1.0%) 19(19.0%), 71(71.0%) and 9(9.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that are frequently hoteling in Never, Sometimes, Normally and Frequently group was 64(64.0%), 23(23.0%) ,8(8.0%) and 5(5.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that regularly test their blood sugar level in yes, no and don’t know group was 51(51.0%), 42(42.0%) and 7(7.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that check their sugar in a day in once a day, twice a day, Weekly and Monthly group was 8(8.08%), 20(20.0%), 46(46.0) and 26(26.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that fluctuate their sugar in never, sometimes and every time group was 28(28.0%), 45(45.0%), 27(27.0) respectively. Out of 1000 respondents the number(percentage) of Persons living in industrial area Yes and NO group was 25(25.0%) and 75(75.0%) respectively. Out of 100 respondents the number(percentage) of Persons living near the which factory in None, Tyre industry, Textile industry, Steel and Others group was 75(75.0%), 5(5.0%), 3(3.0%), 5(5.0%), 12(12.0%) respectively .Out of 1000 respondents the number(percentage) of Persons living area in rural area and urban area group was 23(23.0%) and 77(77.0%) respectively.

Out of 1000 respondents the number(percentage) of Persons satisfied their sanitary system in very good, good, bad and very bad group was 27(27.0%), 45(45.0%), 17(17.0%) and 11(11.0%) respectively .Out of 1000 respondents the number(percentage) of Persons that use which type of water in tap and filter group was 42(42.0%), 58(58.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that taking kind of medicine pills, insulin and combination group was 60(60.0%), 20(20.0%) and 20(20.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that regularly take medicine in yes, no and miss sometimes group was 77(77.0%), 17(17.0%) and 6(6.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that are used vitamin or supplements in yes, no and sometime group was 56(56.0%), 43(43.0%) and 1(1.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that meet their doctor in Weekly, Monthly, and yearly group was 5(5.0%), 70(70.0%) and 25(25.0%) respectively. Out of 1000 respondents the number(percentage) of Persons take alcohol in yes and no group was 6(6.0%) and 94(94.0%). Out of 1000 respondents the number(percentage) of Persons smoking in yes and no group was 22(22.0%) and 78(78.0%). Out of 1000 respondents the number(percentage) of Persons that are going for daily walk in yes, no and do not know group was 79(79.0%), 21(21.0%) respectively.

Out of 1000 respondents the number(percentage) of Persons that think the exercise is necessary for diabetic patients in yes, no and do not know group was 80(80.0%), 17(17.0%) and 3(3.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that think routine walk is helpful for diabetic patients in yes, no and do not know group was 88(88.0%), 9(9.0%) and 3(3.0%) respectively. Out of 1000 respondents the number(percentage) of Persons follow doctor regarding exercise in yes, no and don’t know group was 67(67.0%), 32(32.0%) and 1(1.0%) respectively Out of 1000 respondents the number(percentage) of Persons that take proper fruit in yes, no and sometime group was 41(41.0%), 20(20.0%) and 39(39.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that take milk regularly in yes, no, and sometime group was 48(48.0%), 43(43.0%) and 34(34.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that skip their meal in yes, no and sometime group was 37(37.0%), 34(34.0%) and 29(29.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that take care of their diet in yes, no and don’t know group was 71(71.0%), 20(20.0%) and 9(9.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that affected their daily life from diabetes in yes, no and don’t know group was 47(47.0%), 35(35.0%) and 18(18.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that their household chores affected form health in yes, no and don’t know group was 55(55.0%), 32(32.0%) and 13(13.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that spend the day for exercise in morning, afternoon, evening and no group was 42(42.0%), 4(4.0%).31(31.0) and 23(23.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that walking time in morning, afternoon, evening and no group was 52(52.0%), 4(4.0%). 23(23.0) and 21(21.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that record their sugar levels in yes, no and do not know group was 52(52.0%), 32(32.0%) and 16(16.0%) respectively. Out of 1000 respondents the number(percentage) of persons that their sugar remains normal in yes, no and don’t know group was 43(43.0%), 39(39.0%) and 18(18.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that think diabetes become hindrance in their daily walk activities in yes, no and do not know group was 52(52.0%), 31(31.0%) and 17(17.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that their health interferes in their hobbies and recreational activities in yes, no and don’t know group was 52(52.0%), 32(32.0%) and 18(18.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that their social life affected from diabetes in yes, no and don’t know group was 47(47.0%), 35(35.0%) and 18(18.0%) respectively. Out of 1000 respondents the number(percentage) of Persons that are frequently use alcohol in daily, weekly, monthly and none group was 0(0.0%), 2(2.0%),5(5.0%) and 93(93.0%) respectively. Out of 100 0respondents the number(percentage) of Persons that discuss their problems in detail with the doctor in yes, no and don’t know group was 86(86.0%), 6(6.0%) and 8(8.0%) respectively.

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