Prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital

Prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital Nihfadh Suleiman Tamali, Alina Peris, Funmileyi O. Awobajo, Bala Muntari, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4007813/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Diabetes mellitus and its consequences increase morbidity and mortality. Despite the significant consequences of thyroid dysfunction and diabetes mellitus on each other reported in literature, there is lack of information about the prevalence, patterns and predictors of thyroid dysfunction among adult diabetics in Uganda. This study was aimed at determining the prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital (FPRRH). Methods This was a cross sectional study conducted at FPRRH between August and October 2023. 385 Adult patients with diabetes mellitus were enrolled and assessed for thyroid dysfunction by measuring the free thyroxin (FT4), free triiodothyronine (FT3) and thyroid stimulating hormone (TSH). Thyroid dysfunction was diagnosed if any of the 3 was not in the normal ranges. The predictors of thyroid dysfunction were determined using bivariate and multivariate logistic regression analysis in SPSS version 26. Results Among the 385 patients enrolled, majority were female with a mean age of 54.4 (SD = 15.8) years. The prevalence of thyroid dysfunction was 22.1% (95% CI = 17.7–26.2%). The commonest pattern of thyroid dysfunction was subclinical hypothyroidism 42 (49.4%), followed by clinical hypothyroidism 22(25.9%), subclinical hyperthyroidism 13 (15.3%) and clinical hyperthyroidism 8 (9.4%). The significant independent predictors of thyroid dysfunction were duration of DM ≥ 6 years (aOR = 1.874, P = 0.003), presence of DM complications [peripheral neuropathy (aOR = 3.034, P < 0.001) and diabetic foot (aOR = 5.730, P < 0.001)] and having a high fasting blood sugar (aOR = 1.729, P = 0.017). Conclusion The prevalence of thyroid dysfunction was high. Routine screening for thyroid dysfunction should be done among adult patients with diabetes mellitus during their diabetes clinic in order to decrease the complications through early diagnosis and treatment. Thyroid dysfunction diabetes mellitus predictors Uganda Figures Figure 1 Background The thyroid gland produces and secretes two thyroid hormones, 3,5,3′,5′-tetraiodo-L-thyronine (T4) and 3,5,3′-triiodo-L-thyronine (T3) ( 1 ). Thyroid-stimulating hormone, which is produced by the anterior pituitary gland, activates the thyroid to produce thyroid hormones ( 1 ). Thyrotropin-releasing hormone produced by the hypothalamus, regulates TSH ( 1 ). The thyroid gland plays a vital role in human endocrine system by secreting hormones that control growth, development, and metabolism ( 2 ). Thyroid dysfunction is defined as the change of serum thyroid stimulating hormone (TSH) level with normal or altered thyroid hormones (fT3 and fT4) ( 2 ). Its spectrum can change from a subclinical condition to an overt disease, which indicates a more serious state of thyroid dysfunction ( 2 ). The consequences of thyroid dysfunction on health outcomes are significant and can affect the cardiovascular system, metabolism, bone health and mental health ( 3 ). Diabetes is a chronic condition brought on by insufficient insulin production by the pancreas or inefficient insulin utilization by the body ( 4 ). Insulin is a hormone that is responsible for controlling blood glucose levels in the body ( 4 ). Type 1 diabetes is characterized by insufficient insulin production and necessitates daily insulin administration while type 2 diabetes affects how the body uses insulin ( 4 ). This metabolic disease is marked by high blood glucose levels, which over time cause serious damage to the heart, blood vessels, eyes, kidney and nerves ( 4 ). The connection between thyroid function and T2DM has garnered more attention recently. Diabetes mellitus and thyroid conditions are frequently found together. Furthermore, it has been noted that individuals with diabetes type 1 and type 2, have a higher prevalence of thyroid dysfunction than people without diabetes ( 5 ). Decreased levels of free triiodothyronine (T3) and free thyroxine (T4) have been linked to the frequency of T2DM in the adult population ( 6 ). Numerous studies have revealed a rising prevalence of thyroid abnormalities in people with diabetes mellitus than non-diabetes, demonstrating the strong relationship between thyroid dysfunction and the disease ( 7 ). The connection between thyroid health and type 2 diabetes or sugar intolerance is more complex, encompassing both hyper- and hypothyroidism ( 5 ). Recent research indicates that thyroid autoimmune disorders and type 1 diabetes frequently co-occur, which raises the possibility that thyroid dysfunction contributes to the pathogenesis of diabetes. TPO Abs and Tg Abs are frequently found in conjunction with hypothyroidism, while thyroid-stimulating hormone receptor (TSH) antibodies are frequently found in conjunction with hyperthyroidism ( 1 ). It is important to remember that insulin resistance can result from hyperthyroidism and hypothyroidism ( 8 ). Consequently, it appears that there might be a relationship between thyroid malfunction, T2DM and insulin resistance. The commonest pattern of thyroid dysfunction seen among diabetic patients is hypothyroidism ( 7 ). The hypothyroidism seen is usually subclinical, however clinical hypothyroidism has also been reported in thyroid patients ( 9 ). Hyperthyroidism has also been reported in some cases of diabetes, but it is not as common as hypothyroidism ( 10 ). Though the pathophysiology of thyroid dysfunction in diabetes is not well understood, the main association reported between thyroid dysfunction and diabetes has been the auto immune action seen both against the pancreas and the thyroid ( 1 ). These dysfunctions in thyroid function have been reported to be exacerbated by insulin resistance ( 11 ). In type 2 diabetes mellitus patients, hyperthyroidism and thyrotoxicosis can aggravate subclinical diabetes mellitus and causes hyperglycemia, raising the possibility of diabetes complications. T2DM lowers thyroid-stimulating hormone levels and hinders the peripheral tissues' ability to convert thyroxine (T4) to triiodothyronine (T3) ( 12 ). Uncontrolled T2DM can result to insulin resistance and hyperinsulinemia, which promote thyroid tissue growth and enlarge nodules and goiters. Additionally, while metformin may be helpful for those with T2DM and thyroid disease, other diabetes medications such sulfonylureas, pioglitazone, and thiazolidinedione’s may have a detrimental effect on thyroid condition ( 12 ). In T2DM patients, antithyroid medications like methimazole can deteriorate glycemic control. To provide individualized treatment and management, thyroid vigilance in T2DM patients and diabetovigilance in thyroid dysfunction individual may be required ( 12 ). One in every ten persons worldwide had diabetes, according to the International Diabetes Federation in 2021 (537 million people have diabetes). In African, 24 million individuals had diabetes in 2021, this is expected to rise to 55 million (129%) by 2045 ( 4 ). According to a study with participants from Tanzania and Uganda, the prevalence of diabetes was 10.1% overall and was more among rural Ugandans (16.1%) ( 13 ). In Uganda an estimated 716,000 adults have diabetes ( 4 ). There is paucity of information on the prevalence of thyroid dysfunction among adult individual with diabetes mellitus in Uganda. This study aimed to determine the prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital (FPRRH). Methods Study design and period This was a cross sectional study conducted at Fort Portal Regional Referral Hospital. The data was collected for a period of 3 months (August -October 2023). Study setting The distance between FRRH and Kampala, the main city and capital of Uganda, is roughly 294 km (183 miles). FPRRH has a 333-bed capacity. Every Thursday, a team of doctors, senior house officers, medical officers, and nurses assess patients with diabetes mellitus who have made an appointment at the hospital's medical outpatient department clinic. Every Thursday, more than 50 people with diabetes mellitus are seen. Study population All adult patients (≥ 18 years) presenting to FPRRH diabetic clinic with diabetes mellitus were considered for inclusion if they consented to participate. All the patients that were taking phenobarbital, carbamazepine, amiodarone, beta-blockers, corticosteroids, phenytoin or rifampicin were excluded since these could result in altered levels of thyroid hormones. Also, patients who had thyroid surgery, pregnancy and lactating mothers were excluded (because these conditions have been reported to alter the levels of thyroid hormones). Sample size and sampling. The sample size was calculated using the Kish Leslie (1965) formula: n = Z2p(1-p) / e2. Accordingly, n is the projected minimum sample size needed, and P is the sample's proportion of the feature (50%). For the 95% Confidence Interval, Z = 1.96. E = 5%-set margin of error. A proportion of 50% was used because no study had examined the prevalence of thyroid dysfunction among diabetic adults in our area; thus, n= (1.96)2 x 0.5 (1-0.5)/ (0.05)2 = 384.2. Therefore, 385 participants made up the necessary sample size for this study. All patients who presented to the FPRRH medical outpatient clinic during the study period with diabetes mellitus were recruited if they satisfied eligibility criteria and consented via consecutive sampling until the sample size was met. Recruitment and data collection procedure Patients that full filled the eligibility criteria were explained to the role of the study and why their participation was required and if they accepted to take part in the study, they signed an informed consent form. Those patients that consented were asked questions that were relevant to achieving the objectives of the study. All patients had a clinical examination and the findings were documented in the data collection form. The clinical examination was done by the principal investigator and the study assistant who was a qualified medical doctor. During the clinical evaluation, Body mass index was determined by dividing weight (kg) by squared height (m 2 ). About 2.0 mls of blood was collected for laboratory evaluation. The samples were taken by a qualified laboratory technician. Blood samples were analyzed at Fort Portal Regional Referral Hospital laboratory and entered into the respective questionnaires. After 30 minutes, the drawn blood sample was centrifuged at 3000 rpm for 10 minutes in a thermo-stable Rotanta 960 centrifuge to separate serum from the collected blood sample. The serum was then kept at 20°C in Fort Portal Regional Referral Hospital laboratory until biochemical analysis took place. Biochemical assessments were performed with an Immunoanalyzer cobas e 411 (Roche Diagnostics GmbH, Mannheim, Germany; Hitachi High-Technology Corporation, Tokyo, Japan) using the lateral flow chromatography (immunofluorescence) for thyroid function tests (T3, T4 and TSH). Furthermore, fasting blood sugar was screened using on call plus glucometer machine. After obtaining the results, the samples were discarded using the FPRRH laboratory protocols The following normal ranges were considered, TSH: 0.270–4.20µIU/mL, FT3 : 1.30–3.10 nmol/L, and FT4: 66.0–181.0 nmol/L. Euthyroid was reported when all thyroid hormone levels were within normal ranges and thyroid dysfunction was reported when thyroid hormone levels were above or below the normal range for at least one of the hormones. The diagnostic classification for thyroid dysfunction that was referred to as patterns was as follows: Clinical hyperthyroidism (decreased TSH with raised Free T4 and /or rises Free T3), Subclinical hyperthyroidism (normal Free T4 and normal Free T3 but with decreased TSH), Clinical hypothyroidism (low FT4 and raised TSH), Subclinical hypothyroidism (normal FT4 and elevated TSH) ( 9 ). Participants found to have thyroid dysfunction were linked to the appropriate care at FPRRH. Study variables In this study, the independent variables were clinical variables like body mass index, medication and social demographic parameters such as age and gender while the presence of thyroid dysfunction was the primary outcome. The pattern (type) of thyroid dysfunction was the secondary outcome variable. Quality control The data collection tool was pretested for validity and reliability and adjustments made before starting data collection. The research protocol was explained to the research assistants during training. Every day, the principal investigator or his assistant double-checked the data to make sure it was accurate. The patients underwent thorough history-taking and physical examinations. In Fort Portal laboratory, all samples were examined, and the analyzer was calibrated in accordance with best practices. The Kampala International University Teaching Hospital laboratory re-ran every 30th sample in order to guarantee the validity of the findings. Data analysis plan Data was summarized and entered using excel sheet. To analyze the condensed data, the Statistical Package for Social Sciences was used (SPSS Inc., Chicago, USA, version 26.0 for Windows). The prevalence was calculated as the percentage of patients with thyroid dysfunction among all diabetes mellitus patients. The proportion of patients who had the various types (patterns) of thyroid dysfunction was calculated. Binary logistic regression was used to identify the factors that predicted thyroid dysfunction in diabetes mellitus individuals. Variables with p values less than or equal to 0.2 at bivariate were reanalyzed at the multivariate level. Significant factors were those with a multivariate p value of less than 0.05. Ethical considerations and consent: All methods were carried out in accordance with relevant guidelines and regulations. Ethical approval was granted by the Research and Ethics Committee of Bishop Stuart University's ( Ref No: BSU-REC-2023-125) . All participants gave written informed consent as evidenced by the participants’ signature. Results During the study period, 400 patients with diabetes mellitus (DM) were assessed for legibility to participate in the study. Of the 400, 10 were not legible for participation because they were taking B-blockers while other two had thyroid surgery. Of the remaining 388 patients, 3 declined to give consent because they were in a hurry and did not have time to participate. The 385 patients that consented to participate, responded to the questionnaire, had a blood sample taken for thyroid function tests and their results were availed. In this study, majority of the study participants were females 267(69.4%) with a mean age of 54.4 (SD = 15.8) years, from the rural areas 295(76.6%). The mean duration of debates was 5.9 (SD = 4.9) years. Only 4 (1.0%) of the participants had a goiter on examination though majority had a high fasting blood glucose 208(54.0%). The rest of the baseline characteristics are shown in Table 1 . Table 1 Baseline characteristics of study participants Characteristic Frequency Percentage Age (years) Mean = 54.4, SD = 15.8, Min = 18, Max = 90 18–30 26 6.8 31–45 90 23.4 46+ 269 69.9 Gender Male 118 30.6 Female 267 69.4 Residence Rural 295 76.6 Urban 90 23.4 Education level None 75 19.5 Primary 214 55.6 Secondary 61 15.8 Tertiary 35 9.1 Religion Christian 325 84.4 Muslim 32 8.3 Other 28 7.3 Employment Self/formally Employed 317 82.3 Un employed 68 17.7 Comorbidity None 167 43.4 Hypertension 189 49.1 HIV 18 4.7 Heart failure 11 2.9 Smoking No 381 99.0 Yes 4 1.0 Alcohol Use No 344 89.4 Yes 41 10.6 Alcohol AUDIT Low risk 344 89.4 Medium risk 22 5.7 High risk 19 4.9 DM duration (years) Mean = 5.9, SD = 4.9, Min = 1, Max = 41 ≤ 5 years 229 59.5 6 + years 156 40.5 Treatment type Oral 261 67.8 Insulin 97 25.2 Insulin + metformin 27 7.0 Medication Metformin 77 20.0 Metformin + Glibenclamide 184 47.8 Insulin 97 25.2 Insulin + metformin 27 7.0 DM complications None 165 42.9 Neuropathy 173 44.9 DKA 8 2.1 Diabetic foot 17 4.4 Others 22 5.7 BMI Mean = 26.6, SD = 5.4, Min = 16.2, Max = 53.5 Normal 142 36.9 Low 18 4.7 Overweight/obese 225 58.4 Blood pressure Normal 66 17.1 Pre-hypertensive 133 34.5 Hypertensive 186 48.3 Pulse rate Normal 291 75.6 Tachycardia 94 24.4 Goiter No 381 99.0 Yes 4 1.0 FBG (mmol/L) Mean = 9.7, SD = 5.5, Min = 2.7, Max = 33.0 Normal 170 44.2 Low 7 1.8 High 208 54.0 AUDIT = Alcohol use disorders identification test, HIV = Human immune deficiency virus, DM = Diabetes mellitus, DKA = Diabetic ketoacidosis, BMI = Body mass index, FBG = Fasting blood glucose, SD = Standard deviation, Min = Minimum, Max = Maximum. In this study, 85 of the study participants had thyroid dysfunction of different types representing a prevalence of 22.1% with a corresponding 95% confidence interval of 17.7–26.2% (Fig. 1 ). The commonest pattern of thyroid dysfunction was subclinical hypothyroidism seen in 42 participants representing 49.4% of the patients with dysfunction. This was followed by clinical hypothyroidism accounting for 22(25.9%), then subclinical hyperthyroidism 13(15.3%) and lastly clinical hyperthyroidism 8(9.4%). The rest of the details about the patterns are shown in Table 2 . Table 2 Patterns of thyroid dysfunction among patients with diabetes mellitus attending FPRRH. Pattern Frequency Percentage TSH (N = 385) Mean = 2.2, SD = 1.6, Min = 0.1, Max = 9.9 Normal 300 77.9 Low 21 5.5 High 64 16.6 FT3(nmol/L) (N = 385) Mean = 1.9, SD = 0.6, Min = 0.3, Max = 7.8 Normal 357 92.7 Low 20 5.2 High 8 2.1 FT4 (nmol/L) (N = 385) Mean = 105.7, SD = 20.1, Min = 59.0, Max = 190.5 Normal 377 97.9 Low 6 1.6 High 2 0.5 Hypo vs Hyperthyroidism (N = 385) Normal 300 77.9 Hypothyroidism 64 16.6 Hyperthyroidism 21 5.5 Patterns among those with dysfunction (N = 85) Subclinical Hypothyroidism 42 49.4 Clinical hypothyroidism 22 25.9 Subclinical hyperthyroidism 13 15.3 Clinical hyperthyroidism 8 9.4 TSH = Thyroid stimulating hormone, FT4 = Free Thyroxin, FT3 = Free Triiodothyronine, SD = Standard deviation, Min = Minimum, Max = Maximum . At bivariate level of analysis, the variables that had a p value less than 0.2, and therefore qualified for multivariate analysis were, age, residence, education level, duration of DM, Type of treatment for DM, presence of DM complication, body mass index, blood pressure category, pulse rate category and fasting blood sugar category. The details of bivariate analysis are shown in Table 3 . At multivariate level of analysis, the significant independent predictors of thyroid dysfunction were: duration of DM ≥ 6 years (aOR = 1.874, CI = 1.235–2.844, P = 0.003), presence of DM complications [neuropathy (aOR = 3.034, CI = 1.841-5.000, P < 0.001) and diabetic foot (aOR = 5.730, CI = 2.628–12.492, P < 0.001)] and having a high fasting blood sugar (aOR = 1.729, CI = 1.103–2.712, P = 0.017). A participant who had had diabetes for 6 or more years was 1.874 times more likely to have thyroid dysfunction compared to one who had it for less. A patient who had DM complications was 3.034 times more likely to have thyroid dysfunction if the complication was neuropathy and 5.730 times if the complication was diabetic foot. A patient, whose fasting blood sugar was high, was 1.729 times more likely to have thyroid dysfunction compared to one who had a normal blood sugar. The rest of findings at multivariate analysis are shown in Table 4 . Table 3 Bivariate analysis for predictors of thyroid dysfunction among patients with diabetes mellitus attending FPRRH. Characteristic Normal, N = 300 Dysfunction, N = 85 Bivariate analysis cOR 95% CI P value Age (years) 18–30 25(6.5) 1(0.3) Ref 31–45 75(19.5) 15(3.9) 5.000 0.628–39.792 0.128 46+ 200(51.9) 69(17.9) 8.625 1.147–64.851 0.036 Gender Male 91(23.6) 27(7.0) Ref Female 209(54.3) 58(15.1) 0.935 0.557–1.571 0.801 Residence Rural 235(61.0) 60(15.6) Ref Urban 65(16.9) 25(6.5) 1.506 0.877–2.589 0.138 Education level None 70(18.2) 5(1.3) 0.137 0.044–0.430 0.001 Primary 163(42.3) 51(13.2) 0.600 0.279–1.289 0.190 Secondary 44(11.4) 17(4.4) 0.741 0.303–1.812 0.510 Tertiary 23(6.0) 12(3.1) Ref Employment Self/formally Employed 248(64.4) 69(17.9) Ref Un employed 52(13.5) 16(4.2) 1.106 0.595–2.057 0.751 Comorbidity None 134(34.8) 33(8.6) Ref Hypertension 141(36.6) 48(12.5) 1.382 0.836–2.284 0.207 HIV 16(4.2) 2(0.5) 0.508 0.111–2.317 0.381 Heat failure 9(2.3) 2(0.5) 0.902 0.186–4.376 0.899 Smoking No 298(77.4) 83(21.6) Ref Yes 2(0.5) 2(0.5) 3.590 0.498–25.874 0.205 Alcohol Use No 269(69.9) 75(19.5) Yes 31(8.1) 10(2.6) 1.157 0.543–2.467 0.706 Alcohol AUDIT Low risk 269(69.9) 75(19.5) Ref Medium risk 17(4.4) 5(1.3) 1.055 0.377–2.953 0.919 High risk 14(3.6) 5(1.3) 1.281 0.447–3.670 0.645 DM duration (years) ≤ 5 years 196(50.9) 33(8.6) Ref 6 + years 104(27.0) 52(13.5) 2.970 1.807–4.881 < 0.001 Treatment type Oral 200(51.9) 61(15.8) Ref Insulin 82(21.3) 15(3.9) 0.600 0.322–1.116 0.106 Insulin + metformin 18(4.7) 9(2.3) 1.639 0.701–3.835 0.254 Medication Metformin 60(15.6) 17(4.4) Ref Metformin + Glibenclamide 140(36.4) 44(11.4) 1.109 0.587–2.096 0.749 Insulin 82(21.3) 15(3.9) 0.646 0.299–1.394 0.265 Insulin + metformin 18(4.7) 9(2.3) 1.765 0.673–4.630 0.248 DM complications None 149(38.7) 16(4.2) Ref Neuropathy 121(31.4) 52(13.5) 4.002 2.176–7.362 < 0.001 DKA 6(1.6) 2(0.5) 3.104 0.578–16.678 0.187 Diabetic foot 8(2.1) 9(2.3) 10.477 3.547–30.943 < 0.001 Others 16(4.2) 6(1.6) 3.492 1.197–10.187 0.022 BMI Normal 116(30.1) 26(6.8) Ref Low 9(2.3) 9(2.3) 4.462 0.613–12.337 0.104 Overweight/obese 175(45.5) 50(13.0) 1.275 0.751–2.163 0.368 Blood pressure Normal 57(14.8) 9(2.3) Ref Pre-hypertensive 103(26.8) 30(7.8) 1.845 0.819–4.155 0.139 Hypertensive 140(36.4) 46(11.9) 2.081 0.956–4.530 0.065 Pulse rate Normal 248(64.4) 43(11.2) Ref Tachycardia 52(13.5) 42(10.9) 4.658 0.770–7.834 0.101 Goitre No 300(77.9) 81(21.0) Ref Yes 0(0.0) 4(1.0) N/A FBG (mmol/dl) Normal 147(38.2) 23(6.0) Ref Low 5(1.3) 2(0.5) 2.557 0.468–13.962 0.279 High 148(38.4) 60(15.6) 2.591 1.522–4.411 < 0.001 Ref = Reference category, cOR = Crude odds ratio, CI = Confidence interval, AUDIT = Alcohol use disorders identification test, HIV = Human immune deficiency virus, DM = Diabetes mellitus, DKA = Diabetic ketoacidosis, BMI = Body mass index, FBG = Fasting blood glucose Table 4 Multivariate analysis for predictors of thyroid dysfunction among patients with diabetes mellitus attending FPRRH. Characteristic Bivariate analysis Multivariate analysis cOR 95% CI P value aOR 95% CI P value Age (years) 18–30 Ref 31–45 5.000 0.628–39.792 0.128 1.769 0.750–3.578 0.237 46+ 8.625 1.147–64.851 0.036 2.669 0.850–3.278 0.137 Residence Rural Ref Urban 1.506 0.877–2.589 0.138 1.669 0.850–3.278 0.137 Education level None 0.137 0.044–0.430 0.001 0.616 0.306–1.239 0.174 Primary 0.600 0.279–1.289 0.190 0.628 0.313–1.259 0.190 Secondary 0.741 0.303–1.812 0.510 0.682 0.347–1.341 0.267 Tertiary Ref DM duration (years) ≤ 5 years Ref 6 + years 2.970 1.807–4.881 < 0.001 1.874 1.235–2.844 0.003 Treatment type Oral Ref Insulin 0.600 0.322–1.116 0.106 0.534 0.276–1.031 0.062 Insulin + metformin 1.639 0.701–3.835 0.254 0.728 0.385–1.375 0.328 DM complications None Ref Neuropathy 4.002 2.176–7.362 < 0.001 3.034 1.841-5.000 < 0.001 DKA 3.104 0.578–16.678 0.187 2.058 0.654–6.481 0.217 Diabetic foot 10.477 3.547–30.943 < 0.001 5.730 2.628–12.492 < 0.001 Others 3.492 1.197–10.187 0.022 1.924 0.977–3.792 0.059 BMI Normal Ref Low 4.462 0.613–12.337 0.104 2.766 0.230–6.218 0.114 Overweight/obese 1.275 0.751–2.163 0.368 1.669 0.850–3.278 0.137 Blood pressure Normal Ref Pre-hypertensive 1.845 0.819–4.155 0.139 1.669 0.850–3.278 0.137 Hypertensive 2.081 0.956–4.530 0.065 1.959 0.986–3.891 0.055 Pulse rate Normal Ref Tachycardia 4.658 0.770–7.834 0.101 2.657 0.845–3.827 0.101 FBG (mmol/L) Normal Ref Low 2.557 0.468–13.962 0.279 2.252 0.252–20.132 0.467 High 2.591 1.522–4.411 < 0.001 1.729 1.103–2.712 0.017 aOR = Adjusted odds ratio, Ref = Reference category, CI = Confidence interval, DM = Diabetes mellitus, DKA = Diabetic ketoacidosis. Discussion This study was done to determine the prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital (FPRRH). In this study, majority of the study participants were females with a mean age of 54.4 (SD = 15.8) years which is possibly because most of the participants had type two diabetes whose onset is usually later in life. Majority of the study participants had a high fasting blood glucose 208(54.0%) which could indicate that the blood glucose control was not adequate for the majority of our participants. We noted that 85 of the study participants had thyroid dysfunction representing a prevalence of 22.08% with a corresponding 95% confidence interval of 17.7–26.2%. This prevalence was high and it could be attributed to the fact that majority of the study participants had a poorly controlled blood glucose as evidenced by the high fasting blood glucose, yet high blood glucose has been linked to an increased risk of thyroid dysfunction ( 14 ). The prevalence reported in this study was in agreement with finding by Biondi et al ( 7 ) who did a systematic review and reported that the prevalence of thyroid dysfunction among patients with diabetes mellitus ranged from 17 to 30%, as well as Mohammed Hussein & AbdElmageed ( 11 ) who reported a range of 9.9–48%. Other studies that reported comparable findings were Zhu et al ( 9 ) in China who reported a prevalence of 23.8%, and Li et al ( 15 ) who reported a prevalence of 21%. The prevalence reported in this study was higher than that reported by Kareem et al ( 10 ) in Iraq among patients with type 1 diabetes mellitus (15.7%), Abubakar et al ( 16 ) in Nigeria among type 2 diabetes patients (10.0%), and Muhame et al ( 17 ) among children and adolescents with type one diabetes in Uganda (7.3%). The possible explanation for these differences in prevalence is the differences in the study populations. The study done by Muhame et al ( 17 ) in Uganda was done among children and adolescents (1–19 years) who may have a lower risk for thyroid dysfunction but was also focused on only type 1 diabetes. Contrarily, our study enrolled patients above 18 years including both type 1 and type 2 diabetes, and the study done by Kareem et al ( 10 ) incomparable to our study may be due to the fact that we were in difference geographical area and climate (they have hot desert climate and we have warm topical climate), difference ethnic back ground, they focused only to DM type 1 ( the children and adolescents (≤ 18 years) and their sample size were small (102 patients ) compare to our study (385 patients). We also observed that, the commonest pattern of thyroid dysfunction was subclinical hypothyroidism seen in 42 participants representing 49.4% of the patients with dysfunction. This was followed by clinical hypothyroidism accounting for 22(25.9%), then subclinical hyperthyroidism 13(15.3%) and lastly clinical hyperthyroidism 8(9.4%). Our findings are comparable to findings by Kareem et al ( 10 ) in Iraq where subclinical hypothyroidism was the commonest, Karat et al ( 18 ) in India where subclinical hypothyroidism was the commonest, and Muhame et al ( 17 ) in Uganda where subclinical hypothyroidism was the commonest among children and adolescents with type 1 diabetes mellitus. Incomparable to our findings, Abdulrazaq et al ( 19 ) in Iraq reported that clinical hypothyroidism was the commonest with prevalence of 47.4%. The explanation for this difference is not certain, however is possibly because this study was done over a long duration of 11 years. Therefore, patients who could have been subclinical could progress to clinical. Lastly, the significant independent predictors of thyroid dysfunction were: duration of DM ≥ 6 years, presence of DM complications (Peripheral neuropathy and diabetic foot) and having high fasting blood glucose. A participant who had diabetes for 6 years or more was 1.874 times more likely to have thyroid dysfunction compared to one who had it for less. This is was in agreement with findings by Ogbonna & Ezeani ( 20 ) in India who reported that a duration of DM > 5 years increased odds of thyroid dysfunction by 3.3 times (OR = 3.3, p = 0.012). This is possibly because, prolonged exposure to high levels of blood glucose, has been associated with an increased risk of thyroid dysfunction ( 14 ) by suppressing the peripheral de-iodination of T4 to T3 ( 19 ). A patient who had DM complications was 3.034 times more likely to have thyroid dysfunction if the complication was neuropathy and 5.730 times if the complication was diabetic foot. This finding was similar to that reported by Ogbonna & Ezeani ( 20 ) in India where presence of neuropathy increased odds of having thyroid dysfunction, Li et al ( 15 ) in China where neuropathy and diabetic keto-acidosis increased odds of thyroid dysfunction and a review by Biondi et al ( 7 ) who reported that hospitalization in a diabetic patient increased the risk of having thyroid dysfunction. This is possibly because DM complications are as a result of poorly controlled blood glucose, the same pathway thought to result in thyroid dysfunction. A patient whose fasting blood sugar was high, was 1.729 times more likely to have thyroid dysfunction compared to one who had a normal blood sugar. This finding was in agreement with a report by Li et a ( 15 ) in China who noted that poorly controlled glucose was associated with increased risk of thyroid dysfunction. High fasting blood sugar is an indicator of inadequate blood sugar control. Since high blood sugar is linked to thyroid dysfunction ( 14 ), this could explain the association seen in this study. Study limitation In this study, HbA1c, the test that is more informative at assessing blood glucose control over a longer period of time was not used. This was a cross sectional study in which conclusions about causation cannot be made, however our findings can be used to plan larger follow up studies. Conclusion The prevalence of thyroid dysfunction among patients with diabetes mellitus was 22.08%. The commonest type of thyroid dysfunction was hypothyroidism, specifically, subclinical hypothyroidism. Duration of DM ≥ 6 years, presence of DM complications (Peripheral neuropathy and diabetic foot) and having high blood glucose independently predicted thyroid dysfunction. Routine screening for thyroid dysfunction should be done among adult patients with diabetes mellitus. The initial steps of screening should focus on those who had debates for ≥ 6 years, those with DM complications and those with poor blood glucose control. A large prospective cohort should be done to assess the causal relationship between the different factors found significant while using HbA1c to assess for glucose control. Abbreviations DM: Diabetes mellitus, FPRRH: Fort Portal Regional Referral Hospital, HbA1c: Glycated hemoglobin, IDF: International Diabetes Federation, KIU-TH: Kampala International University Teaching Hospital, T3: Tri-iodothyroxine, T4: Thyroxine , TSH: Thyroid stimulating hormone , TPO Abs: Thyroid peroxidase Antibodies, Tg Abs: Thyroglobulin Antibodies, T1DM: Type 1 diabetes mellitus, T2DM: Type 2 diabetes mellitus and WHO: World Health Organization. Declarations Ethical considerations and consent: All methods were carried out in accordance with relevant guidelines and regulations. Ethical approval was granted by the Research and Ethics Committee of Bishop Stuart University's ( Ref No: BSU-REC-2023-125) . All participants gave written informed consent as evidenced by the participants’ signature. Consent for publication: Not applicable Availability of data and materials: Data is available upon request. Requests should be sent to [email protected] (NST). Competing interests : The authors declare that they have no conflict of interest Sources of funding : This study did not receive any specific grant from funding agencies in public, commercial, or not for profit sectors. Author contribution: NST was the principle investigator, conceived and designed the study, collected data, analysed data and wrote the draft of the manuscript. AP, FOA, BM and RMP, supervised the work and revised the manuscript. WRA and JM participated in data analysis and discussion of the results as well as revising the manuscript . All authors approved the final paper. Acknowledgements: We acknowledge all study participants. References Chen C, Xie Z, Shen Y, Xia SF. The roles of thyroid and thyroid hormone in pancreas: Physiology and pathology. Int J Endocrinol. 2018;2018. Ajlouni KM, Khawaja N, EL-Khateeb M, Batieha A, Farahid O. The prevalence of thyroid dysfunction in Jordan: a national population-based survey. BMC Endocr Disord. 2022;22(1):1–9. Diab N, Daya NR, Juraschek SP, Martin SS, McEvoy JW, Schultheiß UT, et al. Prevalence and Risk Factors of Thyroid Dysfunction in Older Adults in the Community. Sci Rep. 2019;9(1):1–8. WHO. Uganda casts spotlight diabetes adopts global diabetes targets. Online [Internet]. 2023;1(1):1. Available from: https://www.afro.who.int/countries/uganda/news/uganda-casts-spotlight-diabetes-adopts-global-diabetes-targets Nishi M. Diabetes mellitus and thyroid diseases. Diabetol Int [Internet]. 2018;9(2):108–12. Available from: https://doi.org/10.1007/s13340-018-0352-4 Yu H, Li Q, Zhang M, Liu F, Pan J, Tu Y, et al. Decreased leptin is associated with alterations in thyroid-stimulating hormone levels after roux-en-y gastric bypass surgery in obese euthyroid patients with type 2 diabetes. Obes Facts. 2019;12(3):272–80. Biondi B, Kahaly GJ, Robertson RP. Thyroid Dysfunction and Diabetes Mellitus: Two Closely Associated Disorders. Vol. 40, Endocrine Reviews. 2018. 789–824 p. Kapadia K, Bhatt P, Shah: J. Association between altered thyroid state and insulin resistance. J Pharmacol Pharmacother. 2012;3:156–60. Zhu Y, Xu F, Shen J, Liu Y, Bi C, Liu J, et al. Prevalence of thyroid dysfunction in older Chinese patients with type 2 diabetes—A multicenter cross-sectional observational study across China. PLoS One. 2019;14(5):1–14. Kareem MM, Maatook MA, Atwan DI. Thyroid dysfunction in children and adolescents with type 1 diabetes mellitus in Basrah, Iraq. Biochem Cell Arch. 2020;20:3697–700. Mohammed Hussein SM, AbdElmageed RM. The Relationship Between Type 2 Diabetes Mellitus and Related Thyroid Diseases. Cureus. 2021;13(12):10–4. Kalra S, Aggarwal S, Khandelwal D. Thyroid Dysfunction and Type 2 Diabetes Mellitus: Screening Strategies and Implications for Management. Diabetes Ther [Internet]. 2019;10(6):2035–44. Available from: https://doi.org/10.1007/s13300-019-00700-4 Chiwanga FS, Njelekela MA, Diamond MB, Bajunirwe F, Guwatudde D, Nankya-Mutyoba J, et al. Urban and rural prevalence of diabetes and pre-diabetes and risk factors associated with diabetes in Tanzania and Uganda. Glob Health Action. 2016;9(1). Lambadiari V, Mitrou P, Maratou E, Raptis A, Tountas N, Raptis S, et al. Thyroid hormones are positively associated with insulin resistance early in the development of type 2 diabetes. Endocrine. 2011;39:28–32. Li Y, Yi M, Deng X, Li W, Chen Y, Zhang X. Evaluation of the Thyroid Characteristics and Correlated Factors in Hospitalized Patients with Newly Diagnosed Type 2 Diabetes. Diabetes, Metab Syndr Obes. 2022;15(March):873–84. Zainab Abubakar M, Abdulsalam K, Yahaya IA. Thyroid hormones profile of patients with type 2 diabetes mellitus in Kano, Nigeria. Ann African Med Res. 2020;3(1):33–6. Muhame RM, Mworozi EA, McAssey K, Lubega I. Thyroid autoimmunity and function among Ugandan children and adolescents with type-1 diabetes mellitus. Pan Afr Med J. 2014;19:1–7. Karat A, Radhakrishnan C, Thulaseedharan N, Kalam S. Prevalence of thyroid dysfunction and anti–thyroid peroxidase antibody in gestational diabetes mellitus. J Diabetol. 2021;12(5):98. Abdulrazaq HY, Zaboon IA, Maatook MA. Prevalence of thyroid disorders among diabetes mellitus patients in al-Basra southern of Iraq. Ann Trop Med Public Heal. 2021;24(04). Ogbonna SU, Ezeani IU. Risk factors of thyroid dysfunction in patients with type 2 diabetes mellitus. Front Endocrinol (Lausanne). 2019;10(JULY):1–8. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4007813","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":277236108,"identity":"a3269b72-6827-4738-99bc-3e7cf5ed7f9c","order_by":0,"name":"Nihfadh Suleiman Tamali","email":"","orcid":"","institution":"Kampala International University Western Campus","correspondingAuthor":false,"prefix":"","firstName":"Nihfadh","middleName":"Suleiman","lastName":"Tamali","suffix":""},{"id":277236109,"identity":"3bb9cfad-2ee7-4402-9772-b681a78974b5","order_by":1,"name":"Alina Peris","email":"","orcid":"","institution":"Kampala International University Western Campus","correspondingAuthor":false,"prefix":"","firstName":"Alina","middleName":"","lastName":"Peris","suffix":""},{"id":277236110,"identity":"9cc4f3c6-07df-4880-b3bc-364a52313d91","order_by":2,"name":"Funmileyi O. Awobajo","email":"","orcid":"","institution":"Kampala International University Western Campus","correspondingAuthor":false,"prefix":"","firstName":"Funmileyi","middleName":"O.","lastName":"Awobajo","suffix":""},{"id":277236111,"identity":"1e69fbb5-ec69-43ce-bc20-571b798e301b","order_by":3,"name":"Bala Muntari","email":"","orcid":"","institution":"Kampala International University Western Campus","correspondingAuthor":false,"prefix":"","firstName":"Bala","middleName":"","lastName":"Muntari","suffix":""},{"id":277236112,"identity":"79d506f9-c756-47a3-b5ec-1c9c99a11680","order_by":4,"name":"Ryamugwiza Muhammad Prosper","email":"","orcid":"","institution":"Kampala International University Western Campus","correspondingAuthor":false,"prefix":"","firstName":"Ryamugwiza","middleName":"Muhammad","lastName":"Prosper","suffix":""},{"id":277236113,"identity":"1f497588-1f90-4af0-9401-0e3464b5ab3a","order_by":5,"name":"Wardat Rashid Ali","email":"","orcid":"","institution":"Kampala International University Western Campus","correspondingAuthor":false,"prefix":"","firstName":"Wardat","middleName":"Rashid","lastName":"Ali","suffix":""},{"id":277236114,"identity":"7074db26-71e9-4b0f-8cd8-142a6fa1f155","order_by":6,"name":"Joshua Muhumuza","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYBACxgYGNiB1QAbM4/1nAxJrPECMFh4wj4ctDSyGVwsQoGg5DKbxamFub3/2mKfmDg8///GHD97wnLdb234YaEuNTTROh/WcMTfmOfaMR3JGjrHhHInbydvOJAK1HEvLbcClZUYOmzTQPTwGN3iADIPbyWYHgFoYGw7j0ZL+TJrn32Ee+/PHn//mSTiXbHb+ISEtCWbSvG1AWxgSzJh5DhywM7tByJaeM2aSc/ue8UjcyDGWnNuQnGB2A2hLAh6/GAJDTOLNtzty/P3HH35422Bnb3Y+/eGDDzU2uLWgSySCBRJwKAcBeXQBezyKR8EoGAWjYIQCAF/WZDcdTC3YAAAAAElFTkSuQmCC","orcid":"","institution":"Kampala International University Western Campus","correspondingAuthor":true,"prefix":"","firstName":"Joshua","middleName":"","lastName":"Muhumuza","suffix":""}],"badges":[],"createdAt":"2024-03-03 07:18:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4007813/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4007813/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52449979,"identity":"28775b1f-c00e-4df6-b295-6e10e97e5646","added_by":"auto","created_at":"2024-03-11 19:02:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21418,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePie chart showing prevalence of thyroid dysfunction among patients with diabetes mellitus attending FPRRH.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4007813/v1/771e2edc9f97d3ac03bbd5f7.png"},{"id":58300686,"identity":"0434d9aa-5735-44d9-95fb-04e1ef109ea2","added_by":"auto","created_at":"2024-06-13 16:03:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1487187,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4007813/v1/b7e3b028-9285-4bc8-a682-3644ebab3436.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital","fulltext":[{"header":"Background","content":"\u003cp\u003eThe thyroid gland produces and secretes two thyroid hormones, 3,5,3\u0026prime;,5\u0026prime;-tetraiodo-L-thyronine (T4) and 3,5,3\u0026prime;-triiodo-L-thyronine (T3) (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Thyroid-stimulating hormone, which is produced by the anterior pituitary gland, activates the thyroid to produce thyroid hormones (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Thyrotropin-releasing hormone produced by the hypothalamus, regulates TSH (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The thyroid gland plays a vital role in human endocrine system by secreting hormones that control growth, development, and metabolism (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThyroid dysfunction is defined as the change of serum thyroid stimulating hormone (TSH) level with normal or altered thyroid hormones (fT3 and fT4) (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Its spectrum can change from a subclinical condition to an overt disease, which indicates a more serious state of thyroid dysfunction (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The consequences of thyroid dysfunction on health outcomes are significant and can affect the cardiovascular system, metabolism, bone health and mental health (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDiabetes is a chronic condition brought on by insufficient insulin production by the pancreas or inefficient insulin utilization by the body (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Insulin is a hormone that is responsible for controlling blood glucose levels in the body (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Type 1 diabetes is characterized by insufficient insulin production and necessitates daily insulin administration while type 2 diabetes affects how the body uses insulin (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This metabolic disease is marked by high blood glucose levels, which over time cause serious damage to the heart, blood vessels, eyes, kidney and nerves (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe connection between thyroid function and T2DM has garnered more attention recently. Diabetes mellitus and thyroid conditions are frequently found together. Furthermore, it has been noted that individuals with diabetes type 1 and type 2, have a higher prevalence of thyroid dysfunction than people without diabetes (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Decreased levels of free triiodothyronine (T3) and free thyroxine (T4) have been linked to the frequency of T2DM in the adult population (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Numerous studies have revealed a rising prevalence of thyroid abnormalities in people with diabetes mellitus than non-diabetes, demonstrating the strong relationship between thyroid dysfunction and the disease (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe connection between thyroid health and type 2 diabetes or sugar intolerance is more complex, encompassing both hyper- and hypothyroidism (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Recent research indicates that thyroid autoimmune disorders and type 1 diabetes frequently co-occur, which raises the possibility that thyroid dysfunction contributes to the pathogenesis of diabetes. TPO Abs and Tg Abs are frequently found in conjunction with hypothyroidism, while thyroid-stimulating hormone receptor (TSH) antibodies are frequently found in conjunction with hyperthyroidism (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). It is important to remember that insulin resistance can result from hyperthyroidism and hypothyroidism (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Consequently, it appears that there might be a relationship between thyroid malfunction, T2DM and insulin resistance.\u003c/p\u003e \u003cp\u003eThe commonest pattern of thyroid dysfunction seen among diabetic patients is hypothyroidism (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The hypothyroidism seen is usually subclinical, however clinical hypothyroidism has also been reported in thyroid patients (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Hyperthyroidism has also been reported in some cases of diabetes, but it is not as common as hypothyroidism (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Though the pathophysiology of thyroid dysfunction in diabetes is not well understood, the main association reported between thyroid dysfunction and diabetes has been the auto immune action seen both against the pancreas and the thyroid (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). These dysfunctions in thyroid function have been reported to be exacerbated by insulin resistance (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn type 2 diabetes mellitus patients, hyperthyroidism and thyrotoxicosis can aggravate subclinical diabetes mellitus and causes hyperglycemia, raising the possibility of diabetes complications. T2DM lowers thyroid-stimulating hormone levels and hinders the peripheral tissues' ability to convert thyroxine (T4) to triiodothyronine (T3) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Uncontrolled T2DM can result to insulin resistance and hyperinsulinemia, which promote thyroid tissue growth and enlarge nodules and goiters. Additionally, while metformin may be helpful for those with T2DM and thyroid disease, other diabetes medications such sulfonylureas, pioglitazone, and thiazolidinedione\u0026rsquo;s may have a detrimental effect on thyroid condition (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In T2DM patients, antithyroid medications like methimazole can deteriorate glycemic control. To provide individualized treatment and management, thyroid vigilance in T2DM patients and diabetovigilance in thyroid dysfunction individual may be required (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOne in every ten persons worldwide had diabetes, according to the International Diabetes Federation in 2021 (537\u0026nbsp;million people have diabetes). In African, 24\u0026nbsp;million individuals had diabetes in 2021, this is expected to rise to 55\u0026nbsp;million (129%) by 2045 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). According to a study with participants from Tanzania and Uganda, the prevalence of diabetes was 10.1% overall and was more among rural Ugandans (16.1%) (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In Uganda an estimated 716,000 adults have diabetes (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). There is paucity of information on the prevalence of thyroid dysfunction among adult individual with diabetes mellitus in Uganda. This study aimed to determine the prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital (FPRRH).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003eStudy design and period\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis was a cross sectional study conducted at Fort Portal Regional Referral Hospital. The data was collected for a period of 3 months (August -October 2023).\u003c/p\u003e\n\u003ch3\u003eStudy setting\u003c/h3\u003e\n\u003cp\u003eThe distance between FRRH and Kampala, the main city and capital of Uganda, is roughly 294 km (183 miles). FPRRH has a 333-bed capacity. Every Thursday, a team of doctors, senior house officers, medical officers, and nurses assess patients with diabetes mellitus who have made an appointment at the hospital's medical outpatient department clinic. Every Thursday, more than 50 people with diabetes mellitus are seen.\u003c/p\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eAll adult patients (\u0026ge;\u0026thinsp;18 years) presenting to FPRRH diabetic clinic with diabetes mellitus were considered for inclusion if they consented to participate. All the patients that were taking phenobarbital, carbamazepine, amiodarone, beta-blockers, corticosteroids, phenytoin or rifampicin were excluded since these could result in altered levels of thyroid hormones. Also, patients who had thyroid surgery, pregnancy and lactating mothers were excluded (because these conditions have been reported to alter the levels of thyroid hormones).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSample size and sampling.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe sample size was calculated using the Kish Leslie (1965) formula: n\u0026thinsp;=\u0026thinsp;Z2p(1-p) / e2. Accordingly, n is the projected minimum sample size needed, and P is the sample's proportion of the feature (50%). For the 95% Confidence Interval, Z\u0026thinsp;=\u0026thinsp;1.96. E\u0026thinsp;=\u0026thinsp;5%-set margin of error. A proportion of 50% was used because no study had examined the prevalence of thyroid dysfunction among diabetic adults in our area; thus, n= (1.96)2 x 0.5 (1-0.5)/ (0.05)2\u0026thinsp;=\u0026thinsp;384.2. Therefore, 385 participants made up the necessary sample size for this study.\u003c/p\u003e \u003cp\u003eAll patients who presented to the FPRRH medical outpatient clinic during the study period with diabetes mellitus were recruited if they satisfied eligibility criteria and consented via consecutive sampling until the sample size was met.\u003c/p\u003e\n\u003ch3\u003eRecruitment and data collection procedure\u003c/h3\u003e\n\u003cp\u003ePatients that full filled the eligibility criteria were explained to the role of the study and why their participation was required and if they accepted to take part in the study, they signed an informed consent form. Those patients that consented were asked questions that were relevant to achieving the objectives of the study. All patients had a clinical examination and the findings were documented in the data collection form. The clinical examination was done by the principal investigator and the study assistant who was a qualified medical doctor. During the clinical evaluation, Body mass index was determined by dividing weight (kg) by squared height (m\u003csup\u003e2\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eAbout 2.0 mls of blood was collected for laboratory evaluation. The samples were taken by a qualified laboratory technician. Blood samples were analyzed at Fort Portal Regional Referral Hospital laboratory and entered into the respective questionnaires. After 30 minutes, the drawn blood sample was centrifuged at 3000 rpm for 10 minutes in a thermo-stable Rotanta 960 centrifuge to separate serum from the collected blood sample. The serum was then kept at 20\u0026deg;C in Fort Portal Regional Referral Hospital laboratory until biochemical analysis took place. Biochemical assessments were performed with an \u003cb\u003eImmunoanalyzer cobas e 411\u003c/b\u003e (Roche Diagnostics GmbH, Mannheim, Germany; Hitachi High-Technology Corporation, Tokyo, Japan) using the lateral flow chromatography (immunofluorescence) for thyroid function tests (T3, T4 and TSH). Furthermore, fasting blood sugar was screened using on call plus glucometer machine. After obtaining the results, the samples were discarded using the FPRRH laboratory protocols\u003c/p\u003e \u003cp\u003eThe following normal ranges were considered, TSH: 0.270\u0026ndash;4.20\u0026micro;IU/mL, FT3 : 1.30\u0026ndash;3.10 nmol/L, and FT4: 66.0\u0026ndash;181.0 nmol/L. Euthyroid was reported when all thyroid hormone levels were within normal ranges and thyroid dysfunction was reported when thyroid hormone levels were above or below the normal range for at least one of the hormones. The diagnostic classification for thyroid dysfunction that was referred to as patterns was as follows: Clinical hyperthyroidism (decreased TSH with raised Free T4 and /or rises Free T3), Subclinical hyperthyroidism (normal Free T4 and normal Free T3 but with decreased TSH), Clinical hypothyroidism (low FT4 and raised TSH), Subclinical hypothyroidism (normal FT4 and elevated TSH) (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Participants found to have thyroid dysfunction were linked to the appropriate care at FPRRH.\u003c/p\u003e\n\u003ch3\u003eStudy variables\u003c/h3\u003e\n\u003cp\u003eIn this study, the independent variables were clinical variables like body mass index, medication and social demographic parameters such as age and gender while the presence of thyroid dysfunction was the primary outcome. The pattern (type) of thyroid dysfunction was the secondary outcome variable.\u003c/p\u003e\n\u003ch3\u003eQuality control\u003c/h3\u003e\n\u003cp\u003eThe data collection tool was pretested for validity and reliability and adjustments made before starting data collection. The research protocol was explained to the research assistants during training. Every day, the principal investigator or his assistant double-checked the data to make sure it was accurate. The patients underwent thorough history-taking and physical examinations. In Fort Portal laboratory, all samples were examined, and the analyzer was calibrated in accordance with best practices. The Kampala International University Teaching Hospital laboratory re-ran every 30th sample in order to guarantee the validity of the findings.\u003c/p\u003e\n\u003ch3\u003eData analysis plan\u003c/h3\u003e\n\u003cp\u003eData was summarized and entered using excel sheet. To analyze the condensed data, the Statistical Package for Social Sciences was used (SPSS Inc., Chicago, USA, version 26.0 for Windows). The prevalence was calculated as the percentage of patients with thyroid dysfunction among all diabetes mellitus patients. The proportion of patients who had the various types (patterns) of thyroid dysfunction was calculated. Binary logistic regression was used to identify the factors that predicted thyroid dysfunction in diabetes mellitus individuals. Variables with p values less than or equal to 0.2 at bivariate were reanalyzed at the multivariate level. Significant factors were those with a multivariate p value of less than 0.05.\u003c/p\u003e\n\u003ch3\u003eEthical considerations and consent:\u003c/h3\u003e\n\u003cp\u003e All methods were carried out in accordance with relevant guidelines and regulations. Ethical approval was granted by the Research and Ethics Committee of Bishop Stuart University's (\u003cb\u003eRef No: BSU-REC-2023-125)\u003c/b\u003e. All participants gave written informed consent as evidenced by the participants\u0026rsquo; signature.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDuring the study period, 400 patients with diabetes mellitus (DM) were assessed for legibility to participate in the study. Of the 400, 10 were not legible for participation because they were taking B-blockers while other two had thyroid surgery. Of the remaining 388 patients, 3 declined to give consent because they were in a hurry and did not have time to participate. The 385 patients that consented to participate, responded to the questionnaire, had a blood sample taken for thyroid function tests and their results were availed. In this study, majority of the study participants were females 267(69.4%) with a mean age of 54.4 (SD\u0026thinsp;=\u0026thinsp;15.8) years, from the rural areas 295(76.6%). The mean duration of debates was 5.9 (SD\u0026thinsp;=\u0026thinsp;4.9) years. Only 4 (1.0%) of the participants had a goiter on examination though majority had a high fasting blood glucose 208(54.0%). The rest of the baseline characteristics are shown in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBaseline characteristics of study participants\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eCharacteristic\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFrequency\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePercentage\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;=\u0026thinsp;54.4, SD\u0026thinsp;=\u0026thinsp;15.8, Min\u0026thinsp;=\u0026thinsp;18, Max\u0026thinsp;=\u0026thinsp;90\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u0026ndash;30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u0026ndash;45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e46+\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e269\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e69.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e118\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e30.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e267\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e69.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRural\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e295\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e76.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUrban\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e90\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e23.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrimary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e214\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e55.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSecondary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTertiary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eReligion\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eChristian\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e325\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e84.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMuslim\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOther\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEmployment\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSelf/formally Employed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e317\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e82.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUn employed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eComorbidity\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e167\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e43.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e189\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHIV\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHeart failure\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e381\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e99.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAlcohol Use\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e344\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e89.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAlcohol AUDIT\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e344\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e89.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMedium risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDM duration (years)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;=\u0026thinsp;5.9, SD\u0026thinsp;=\u0026thinsp;4.9, Min\u0026thinsp;=\u0026thinsp;1, Max\u0026thinsp;=\u0026thinsp;41\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;5 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e229\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e59.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e156\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e40.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTreatment type\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e261\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e67.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin\u0026thinsp;+\u0026thinsp;metformin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMedication\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMetformin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e77\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMetformin\u0026thinsp;+\u0026thinsp;Glibenclamide\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e184\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e47.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin\u0026thinsp;+\u0026thinsp;metformin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDM complications\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e165\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeuropathy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e173\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDKA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetic foot\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOthers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;=\u0026thinsp;26.6, SD\u0026thinsp;=\u0026thinsp;5.4, Min\u0026thinsp;=\u0026thinsp;16.2, Max\u0026thinsp;=\u0026thinsp;53.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e142\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e36.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOverweight/obese\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e225\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e58.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBlood pressure\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e17.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-hypertensive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e133\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertensive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e186\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e48.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePulse rate\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e291\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e75.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTachycardia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e94\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e24.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eGoiter\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e381\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e99.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eFBG (mmol/L)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;=\u0026thinsp;9.7, SD\u0026thinsp;=\u0026thinsp;5.5, Min\u0026thinsp;=\u0026thinsp;2.7, Max\u0026thinsp;=\u0026thinsp;33.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e170\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e208\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e54.0\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\"\u003e\u003cem\u003eAUDIT\u0026thinsp;=\u0026thinsp;Alcohol use disorders identification test, HIV\u0026thinsp;=\u0026thinsp;Human immune deficiency virus, DM\u0026thinsp;=\u0026thinsp;Diabetes mellitus, DKA\u0026thinsp;=\u0026thinsp;Diabetic ketoacidosis, BMI\u0026thinsp;=\u0026thinsp;Body mass index, FBG\u0026thinsp;=\u0026thinsp;Fasting blood glucose, SD\u0026thinsp;=\u0026thinsp;Standard deviation, Min\u0026thinsp;=\u0026thinsp;Minimum, Max\u0026thinsp;=\u0026thinsp;Maximum.\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eIn this study, 85 of the study participants had thyroid dysfunction of different types representing a prevalence of 22.1% with a corresponding 95% confidence interval of 17.7\u0026ndash;26.2% (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The commonest pattern of thyroid dysfunction was subclinical hypothyroidism seen in 42 participants representing 49.4% of the patients with dysfunction. This was followed by clinical hypothyroidism accounting for 22(25.9%), then subclinical hyperthyroidism 13(15.3%) and lastly clinical hyperthyroidism 8(9.4%). The rest of the details about the patterns are shown in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003ePatterns of thyroid dysfunction among patients with diabetes mellitus attending FPRRH.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePattern\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eFrequency\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ePercentage\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTSH (N\u0026thinsp;=\u0026thinsp;385)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;=\u0026thinsp;2.2, SD\u0026thinsp;=\u0026thinsp;1.6, Min\u0026thinsp;=\u0026thinsp;0.1, Max\u0026thinsp;=\u0026thinsp;9.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e300\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e77.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eFT3(nmol/L) (N\u0026thinsp;=\u0026thinsp;385)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;=\u0026thinsp;1.9, SD\u0026thinsp;=\u0026thinsp;0.6, Min\u0026thinsp;=\u0026thinsp;0.3, Max\u0026thinsp;=\u0026thinsp;7.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e357\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e92.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eFT4 (nmol/L) (N\u0026thinsp;=\u0026thinsp;385)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;=\u0026thinsp;105.7, SD\u0026thinsp;=\u0026thinsp;20.1, Min\u0026thinsp;=\u0026thinsp;59.0, Max\u0026thinsp;=\u0026thinsp;190.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e377\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e97.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eHypo vs Hyperthyroidism (N\u0026thinsp;=\u0026thinsp;385)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e300\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e77.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypothyroidism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e16.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHyperthyroidism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePatterns among those with dysfunction (N\u0026thinsp;=\u0026thinsp;85)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSubclinical Hypothyroidism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e49.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eClinical hypothyroidism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e25.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSubclinical hyperthyroidism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e15.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eClinical hyperthyroidism\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e9.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\"\u003e\u003cem\u003eTSH\u0026thinsp;=\u0026thinsp;Thyroid stimulating hormone, FT4\u0026thinsp;=\u0026thinsp;Free Thyroxin, FT3\u0026thinsp;=\u0026thinsp;Free Triiodothyronine, SD\u0026thinsp;=\u0026thinsp;Standard deviation, Min\u0026thinsp;=\u0026thinsp;Minimum, Max\u0026thinsp;=\u0026thinsp;Maximum\u003c/em\u003e.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAt bivariate level of analysis, the variables that had a p value less than 0.2, and therefore qualified for multivariate analysis were, age, residence, education level, duration of DM, Type of treatment for DM, presence of DM complication, body mass index, blood pressure category, pulse rate category and fasting blood sugar category. The details of bivariate analysis are shown in Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. At multivariate level of analysis, the significant independent predictors of thyroid dysfunction were: duration of DM\u0026thinsp;\u0026ge;\u0026thinsp;6 years (aOR\u0026thinsp;=\u0026thinsp;1.874, CI\u0026thinsp;=\u0026thinsp;1.235\u0026ndash;2.844, P\u0026thinsp;=\u0026thinsp;0.003), presence of DM complications [neuropathy (aOR\u0026thinsp;=\u0026thinsp;3.034, CI\u0026thinsp;=\u0026thinsp;1.841-5.000, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and diabetic foot (aOR\u0026thinsp;=\u0026thinsp;5.730, CI\u0026thinsp;=\u0026thinsp;2.628\u0026ndash;12.492, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)] and having a high fasting blood sugar (aOR\u0026thinsp;=\u0026thinsp;1.729, CI\u0026thinsp;=\u0026thinsp;1.103\u0026ndash;2.712, P\u0026thinsp;=\u0026thinsp;0.017). A participant who had had diabetes for 6 or more years was 1.874 times more likely to have thyroid dysfunction compared to one who had it for less. A patient who had DM complications was 3.034 times more likely to have thyroid dysfunction if the complication was neuropathy and 5.730 times if the complication was diabetic foot. A patient, whose fasting blood sugar was high, was 1.729 times more likely to have thyroid dysfunction compared to one who had a normal blood sugar. The rest of findings at multivariate analysis are shown in Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eBivariate analysis for predictors of thyroid dysfunction among patients with diabetes mellitus attending FPRRH.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCharacteristic\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eNormal, N\u0026thinsp;=\u0026thinsp;300\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eDysfunction, N\u0026thinsp;=\u0026thinsp;85\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eBivariate analysis\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ecOR\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e95% CI\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAge (years)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u0026ndash;30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e25(6.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1(0.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u0026ndash;45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e75(19.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15(3.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.628\u0026ndash;39.792\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.128\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e46+\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e200(51.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e69(17.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.625\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.147\u0026ndash;64.851\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.036\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e91(23.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27(7.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e209(54.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e58(15.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.935\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.557\u0026ndash;1.571\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.801\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRural\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e235(61.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e60(15.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUrban\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e65(16.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e25(6.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.506\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.877\u0026ndash;2.589\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.138\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e70(18.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5(1.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.137\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.044\u0026ndash;0.430\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrimary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e163(42.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e51(13.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.600\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.279\u0026ndash;1.289\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.190\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSecondary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e44(11.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17(4.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.741\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.303\u0026ndash;1.812\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.510\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTertiary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23(6.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e12(3.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEmployment\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSelf/formally Employed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e248(64.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e69(17.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eRef\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUn employed\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e52(13.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16(4.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.106\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.595\u0026ndash;2.057\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.751\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eComorbidity\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e134(34.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e33(8.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertension\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e141(36.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e48(12.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.382\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.836\u0026ndash;2.284\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.207\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHIV\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16(4.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2(0.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.508\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.111\u0026ndash;2.317\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.381\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHeat failure\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9(2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2(0.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.902\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.186\u0026ndash;4.376\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.899\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e298(77.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e83(21.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2(0.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2(0.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.590\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.498\u0026ndash;25.874\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.205\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAlcohol Use\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e269(69.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e75(19.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e31(8.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10(2.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.157\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.543\u0026ndash;2.467\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.706\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAlcohol AUDIT\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e269(69.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e75(19.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMedium risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e17(4.4)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5(1.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.055\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.377\u0026ndash;2.953\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.919\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh risk\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e14(3.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5(1.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.281\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.447\u0026ndash;3.670\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.645\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDM duration\u003c/strong\u003e (years)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;5 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e196(50.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e33(8.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e6\u0026thinsp;+\u0026thinsp;years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e104(27.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e52(13.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.970\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.807\u0026ndash;4.881\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTreatment type\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e200(51.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e61(15.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e82(21.3)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15(3.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.600\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.322\u0026ndash;1.116\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.106\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin\u0026thinsp;+\u0026thinsp;metformin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18(4.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9(2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.639\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.701\u0026ndash;3.835\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.254\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eMedication\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMetformin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e60(15.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e17(4.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMetformin\u0026thinsp;+\u0026thinsp;Glibenclamide\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e140(36.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e44(11.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.109\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.587\u0026ndash;2.096\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.749\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e82(21.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15(3.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.646\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.299\u0026ndash;1.394\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.265\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin\u0026thinsp;+\u0026thinsp;metformin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e18(4.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9(2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.765\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.673\u0026ndash;4.630\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.248\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDM complications\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e149(38.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16(4.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNeuropathy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e121(31.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e52(13.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.176\u0026ndash;7.362\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDKA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6(1.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2(0.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.104\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.578\u0026ndash;16.678\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.187\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiabetic foot\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e8(2.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9(2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10.477\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e3.547\u0026ndash;30.943\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOthers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16(4.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6(1.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.492\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.197\u0026ndash;10.187\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.022\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e116(30.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e26(6.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9(2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9(2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.462\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.613\u0026ndash;12.337\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.104\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOverweight/obese\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e175(45.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e50(13.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.275\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.751\u0026ndash;2.163\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.368\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBlood pressure\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e57(14.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9(2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-hypertensive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e103(26.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e30(7.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.845\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.819\u0026ndash;4.155\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.139\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertensive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e140(36.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e46(11.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.081\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.956\u0026ndash;4.530\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.065\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePulse rate\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e248(64.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e43(11.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTachycardia\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e52(13.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e42(10.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.658\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.770\u0026ndash;7.834\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.101\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eGoitre\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e300(77.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e81(21.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0(0.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4(1.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eN/A\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eFBG (mmol/dl)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e147(38.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23(6.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e5(1.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2(0.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.557\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.468\u0026ndash;13.962\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.279\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e148(38.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e60(15.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.591\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.522\u0026ndash;4.411\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"6\"\u003e\u003cem\u003eRef\u0026thinsp;=\u0026thinsp;Reference category, cOR\u0026thinsp;=\u0026thinsp;Crude odds ratio, CI\u0026thinsp;=\u0026thinsp;Confidence interval, AUDIT\u0026thinsp;=\u0026thinsp;Alcohol use disorders identification test, HIV\u0026thinsp;=\u0026thinsp;Human immune deficiency virus, DM\u0026thinsp;=\u0026thinsp;Diabetes mellitus, DKA\u0026thinsp;=\u0026thinsp;Diabetic ketoacidosis, BMI\u0026thinsp;=\u0026thinsp;Body mass index, FBG\u0026thinsp;=\u0026thinsp;Fasting blood glucose\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eMultivariate analysis for predictors of thyroid dysfunction among patients with diabetes mellitus attending FPRRH.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eCharacteristic\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eBivariate analysis\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eMultivariate analysis\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ecOR\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e95% CI\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eaOR\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e95% CI\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAge (years)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e18\u0026ndash;30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e31\u0026ndash;45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e5.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.628\u0026ndash;39.792\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.128\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.769\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.750\u0026ndash;3.578\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.237\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e46+\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8.625\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.147\u0026ndash;64.851\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.036\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.669\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.850\u0026ndash;3.278\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.137\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRural\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eUrban\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.506\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.877\u0026ndash;2.589\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.138\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.669\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.850\u0026ndash;3.278\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.137\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.137\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.044\u0026ndash;0.430\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.616\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.306\u0026ndash;1.239\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.174\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrimary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.600\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.279\u0026ndash;1.289\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.190\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.628\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.313\u0026ndash;1.259\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.190\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSecondary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.741\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.303\u0026ndash;1.812\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.510\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.682\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.347\u0026ndash;1.341\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.267\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTertiary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDM duration (years)\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026le;\u0026thinsp;5 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e6\u0026thinsp;+\u0026thinsp;years\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.970\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.807\u0026ndash;4.881\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.874\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.235\u0026ndash;2.844\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTreatment type\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOral\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.600\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.322\u0026ndash;1.116\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.106\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.534\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.276\u0026ndash;1.031\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.062\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin\u0026thinsp;+\u0026thinsp;metformin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.639\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.701\u0026ndash;3.835\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.254\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.728\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.385\u0026ndash;1.375\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.328\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDM complications\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNone\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eNeuropathy\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e4.002\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.176\u0026ndash;7.362\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e3.034\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.841-5.000\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDKA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.104\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.578\u0026ndash;16.678\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.187\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.058\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.654\u0026ndash;6.481\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.217\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDiabetic foot\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e10.477\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e3.547\u0026ndash;30.943\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e5.730\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.628\u0026ndash;12.492\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOthers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e3.492\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.197\u0026ndash;10.187\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.022\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.924\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.977\u0026ndash;3.792\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.059\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eLow\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.462\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.613\u0026ndash;12.337\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.104\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.766\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.230\u0026ndash;6.218\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.114\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOverweight/obese\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.275\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.751\u0026ndash;2.163\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.368\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.669\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.850\u0026ndash;3.278\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.137\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBlood pressure\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePre-hypertensive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1.845\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.819\u0026ndash;4.155\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.139\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.669\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.850\u0026ndash;3.278\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.137\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHypertensive\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.081\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.956\u0026ndash;4.530\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.065\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.959\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.986\u0026ndash;3.891\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.055\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePulse rate\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTachycardia\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e4.658\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.770\u0026ndash;7.834\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.101\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.657\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.845\u0026ndash;3.827\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.101\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFBG (mmol/L)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRef\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eLow\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e2.557\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.468\u0026ndash;13.962\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.279\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.252\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.252\u0026ndash;20.132\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.467\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eHigh\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e2.591\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.522\u0026ndash;4.411\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.729\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e1.103\u0026ndash;2.712\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"7\"\u003e\u003cem\u003eaOR\u0026thinsp;=\u0026thinsp;Adjusted odds ratio, Ref\u0026thinsp;=\u0026thinsp;Reference category, CI\u0026thinsp;=\u0026thinsp;Confidence interval, DM\u0026thinsp;=\u0026thinsp;Diabetes mellitus, DKA\u0026thinsp;=\u0026thinsp;Diabetic ketoacidosis.\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study was done to determine the prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital (FPRRH). In this study, majority of the study participants were females with a mean age of 54.4 (SD\u0026thinsp;=\u0026thinsp;15.8) years which is possibly because most of the participants had type two diabetes whose onset is usually later in life. Majority of the study participants had a high fasting blood glucose 208(54.0%) which could indicate that the blood glucose control was not adequate for the majority of our participants.\u003c/p\u003e \u003cp\u003eWe noted that 85 of the study participants had thyroid dysfunction representing a prevalence of 22.08% with a corresponding 95% confidence interval of 17.7\u0026ndash;26.2%. This prevalence was high and it could be attributed to the fact that majority of the study participants had a poorly controlled blood glucose as evidenced by the high fasting blood glucose, yet high blood glucose has been linked to an increased risk of thyroid dysfunction (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe prevalence reported in this study was in agreement with finding by Biondi \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) who did a systematic review and reported that the prevalence of thyroid dysfunction among patients with diabetes mellitus ranged from 17 to 30%, as well as Mohammed Hussein \u0026amp; AbdElmageed (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) who reported a range of 9.9\u0026ndash;48%. Other studies that reported comparable findings were Zhu \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) in China who reported a prevalence of 23.8%, and Li \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) who reported a prevalence of 21%.\u003c/p\u003e \u003cp\u003eThe prevalence reported in this study was higher than that reported by Kareem \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) in Iraq among patients with type 1 diabetes mellitus (15.7%), Abubakar et al (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) in Nigeria among type 2 diabetes patients (10.0%), and Muhame \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) among children and adolescents with type one diabetes in Uganda (7.3%). The possible explanation for these differences in prevalence is the differences in the study populations. The study done by Muhame \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) in Uganda was done among children and adolescents (1\u0026ndash;19 years) who may have a lower risk for thyroid dysfunction but was also focused on only type 1 diabetes. Contrarily, our study enrolled patients above 18 years including both type 1 and type 2 diabetes, and the study done by Kareem \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) incomparable to our study may be due to the fact that we were in difference geographical area and climate (they have hot desert climate and we have warm topical climate), difference ethnic back ground, they focused only to DM type 1 ( the children and adolescents (\u0026le;\u0026thinsp;18 years) and their sample size were small (102 patients ) compare to our study (385 patients).\u003c/p\u003e \u003cp\u003eWe also observed that, the commonest pattern of thyroid dysfunction was subclinical hypothyroidism seen in 42 participants representing 49.4% of the patients with dysfunction. This was followed by clinical hypothyroidism accounting for 22(25.9%), then subclinical hyperthyroidism 13(15.3%) and lastly clinical hyperthyroidism 8(9.4%). Our findings are comparable to findings by Kareem \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) in Iraq where subclinical hypothyroidism was the commonest, Karat \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) in India where subclinical hypothyroidism was the commonest, and Muhame \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) in Uganda where subclinical hypothyroidism was the commonest among children and adolescents with type 1 diabetes mellitus.\u003c/p\u003e \u003cp\u003eIncomparable to our findings, Abdulrazaq \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e) in Iraq reported that clinical hypothyroidism was the commonest with prevalence of 47.4%. The explanation for this difference is not certain, however is possibly because this study was done over a long duration of 11 years. Therefore, patients who could have been subclinical could progress to clinical.\u003c/p\u003e \u003cp\u003eLastly, the significant independent predictors of thyroid dysfunction were: duration of DM\u0026thinsp;\u0026ge;\u0026thinsp;6 years, presence of DM complications (Peripheral neuropathy and diabetic foot) and having high fasting blood glucose. A participant who had diabetes for 6 years or more was 1.874 times more likely to have thyroid dysfunction compared to one who had it for less. This is was in agreement with findings by Ogbonna \u0026amp; Ezeani (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) in India who reported that a duration of DM\u0026thinsp;\u0026gt;\u0026thinsp;5 years increased odds of thyroid dysfunction by 3.3 times (OR\u0026thinsp;=\u0026thinsp;3.3, p\u0026thinsp;=\u0026thinsp;0.012). This is possibly because, prolonged exposure to high levels of blood glucose, has been associated with an increased risk of thyroid dysfunction (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) by suppressing the peripheral de-iodination of T4 to T3 (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA patient who had DM complications was 3.034 times more likely to have thyroid dysfunction if the complication was neuropathy and 5.730 times if the complication was diabetic foot. This finding was similar to that reported by Ogbonna \u0026amp; Ezeani (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) in India where presence of neuropathy increased odds of having thyroid dysfunction, Li \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) in China where neuropathy and diabetic keto-acidosis increased odds of thyroid dysfunction and a review by Biondi \u003cem\u003eet al\u003c/em\u003e (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) who reported that hospitalization in a diabetic patient increased the risk of having thyroid dysfunction. This is possibly because DM complications are as a result of poorly controlled blood glucose, the same pathway thought to result in thyroid dysfunction.\u003c/p\u003e \u003cp\u003eA patient whose fasting blood sugar was high, was 1.729 times more likely to have thyroid dysfunction compared to one who had a normal blood sugar. This finding was in agreement with a report by Li \u003cem\u003eet a\u003c/em\u003e (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) in China who noted that poorly controlled glucose was associated with increased risk of thyroid dysfunction. High fasting blood sugar is an indicator of inadequate blood sugar control. Since high blood sugar is linked to thyroid dysfunction (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), this could explain the association seen in this study.\u003c/p\u003e\n\u003ch3\u003eStudy limitation\u003c/h3\u003e\n\u003cp\u003eIn this study, HbA1c, the test that is more informative at assessing blood glucose control over a longer period of time was not used. This was a cross sectional study in which conclusions about causation cannot be made, however our findings can be used to plan larger follow up studies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe prevalence of thyroid dysfunction among patients with diabetes mellitus was 22.08%. The commonest type of thyroid dysfunction was hypothyroidism, specifically, subclinical hypothyroidism. Duration of DM\u0026thinsp;\u0026ge;\u0026thinsp;6 years, presence of DM complications (Peripheral neuropathy and diabetic foot) and having high blood glucose independently predicted thyroid dysfunction.\u003c/p\u003e \u003cp\u003eRoutine screening for thyroid dysfunction should be done among adult patients with diabetes mellitus. The initial steps of screening should focus on those who had debates for \u0026ge;\u0026thinsp;6 years, those with DM complications and those with poor blood glucose control. A large prospective cohort should be done to assess the causal relationship between the different factors found significant while using HbA1c to assess for glucose control.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDM: Diabetes mellitus, FPRRH: Fort Portal Regional Referral Hospital, HbA1c: Glycated hemoglobin, IDF: International Diabetes Federation, KIU-TH: Kampala International University Teaching Hospital, T3: Tri-iodothyroxine, T4: Thyroxine , TSH: Thyroid stimulating hormone , TPO Abs: Thyroid peroxidase Antibodies, Tg Abs: Thyroglobulin Antibodies, T1DM: Type 1 diabetes mellitus, T2DM: Type 2 diabetes mellitus and WHO: World Health Organization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical considerations and consent:\u003c/strong\u003e All methods were carried out in accordance with relevant guidelines and regulations. Ethical approval was granted by the Research and Ethics Committee of Bishop Stuart University\u0026apos;s (\u003cstrong\u003eRef No: BSU-REC-2023-125)\u003c/strong\u003e. All participants gave written informed consent as evidenced by the participants\u0026rsquo; signature.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eData is available upon request. Requests should be sent to [email protected] (NST).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e: The authors declare that they have no conflict of interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSources of funding\u003c/strong\u003e: This study did not receive any specific grant from funding agencies in public, commercial, or not for profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution: NST\u0026nbsp;\u003c/strong\u003ewas the principle investigator, conceived and designed the study, collected data, analysed data and wrote the draft of the manuscript. \u003cstrong\u003eAP, FOA, BM and RMP,\u0026nbsp;\u003c/strong\u003esupervised the work and revised the manuscript. \u003cstrong\u003eWRA and JM\u0026nbsp;\u003c/strong\u003eparticipated in data analysis and discussion of the results as well as revising the manuscript\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eAll authors approved the final paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe acknowledge all study participants.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eChen C, Xie Z, Shen Y, Xia SF. The roles of thyroid and thyroid hormone in pancreas: Physiology and pathology. Int J Endocrinol. 2018;2018. \u003c/li\u003e\n\u003cli\u003eAjlouni KM, Khawaja N, EL-Khateeb M, Batieha A, Farahid O. The prevalence of thyroid dysfunction in Jordan: a national population-based survey. BMC Endocr Disord. 2022;22(1):1\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eDiab N, Daya NR, Juraschek SP, Martin SS, McEvoy JW, Schulthei\u0026szlig; UT, et al. Prevalence and Risk Factors of Thyroid Dysfunction in Older Adults in the Community. Sci Rep. 2019;9(1):1\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eWHO. Uganda casts spotlight diabetes adopts global diabetes targets. Online [Internet]. 2023;1(1):1. Available from: https://www.afro.who.int/countries/uganda/news/uganda-casts-spotlight-diabetes-adopts-global-diabetes-targets\u003c/li\u003e\n\u003cli\u003eNishi M. Diabetes mellitus and thyroid diseases. Diabetol Int [Internet]. 2018;9(2):108\u0026ndash;12. Available from: https://doi.org/10.1007/s13340-018-0352-4\u003c/li\u003e\n\u003cli\u003eYu H, Li Q, Zhang M, Liu F, Pan J, Tu Y, et al. Decreased leptin is associated with alterations in thyroid-stimulating hormone levels after roux-en-y gastric bypass surgery in obese euthyroid patients with type 2 diabetes. Obes Facts. 2019;12(3):272\u0026ndash;80. \u003c/li\u003e\n\u003cli\u003eBiondi B, Kahaly GJ, Robertson RP. Thyroid Dysfunction and Diabetes Mellitus: Two Closely Associated Disorders. Vol. 40, Endocrine Reviews. 2018. 789\u0026ndash;824 p. \u003c/li\u003e\n\u003cli\u003eKapadia K, Bhatt P, Shah: J. Association between altered thyroid state and insulin resistance. J Pharmacol Pharmacother. 2012;3:156\u0026ndash;60. \u003c/li\u003e\n\u003cli\u003eZhu Y, Xu F, Shen J, Liu Y, Bi C, Liu J, et al. Prevalence of thyroid dysfunction in older Chinese patients with type 2 diabetes\u0026mdash;A multicenter cross-sectional observational study across China. PLoS One. 2019;14(5):1\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eKareem MM, Maatook MA, Atwan DI. Thyroid dysfunction in children and adolescents with type 1 diabetes mellitus in Basrah, Iraq. Biochem Cell Arch. 2020;20:3697\u0026ndash;700. \u003c/li\u003e\n\u003cli\u003eMohammed Hussein SM, AbdElmageed RM. The Relationship Between Type 2 Diabetes Mellitus and Related Thyroid Diseases. Cureus. 2021;13(12):10\u0026ndash;4. \u003c/li\u003e\n\u003cli\u003eKalra S, Aggarwal S, Khandelwal D. Thyroid Dysfunction and Type 2 Diabetes Mellitus: Screening Strategies and Implications for Management. Diabetes Ther [Internet]. 2019;10(6):2035\u0026ndash;44. Available from: https://doi.org/10.1007/s13300-019-00700-4\u003c/li\u003e\n\u003cli\u003eChiwanga FS, Njelekela MA, Diamond MB, Bajunirwe F, Guwatudde D, Nankya-Mutyoba J, et al. Urban and rural prevalence of diabetes and pre-diabetes and risk factors associated with diabetes in Tanzania and Uganda. Glob Health Action. 2016;9(1). \u003c/li\u003e\n\u003cli\u003eLambadiari V, Mitrou P, Maratou E, Raptis A, Tountas N, Raptis S, et al. Thyroid hormones are positively associated with insulin resistance early in the development of type 2 diabetes. Endocrine. 2011;39:28\u0026ndash;32. \u003c/li\u003e\n\u003cli\u003eLi Y, Yi M, Deng X, Li W, Chen Y, Zhang X. Evaluation of the Thyroid Characteristics and Correlated Factors in Hospitalized Patients with Newly Diagnosed Type 2 Diabetes. Diabetes, Metab Syndr Obes. 2022;15(March):873\u0026ndash;84. \u003c/li\u003e\n\u003cli\u003eZainab Abubakar M, Abdulsalam K, Yahaya IA. Thyroid hormones profile of patients with type 2 diabetes mellitus in Kano, Nigeria. Ann African Med Res. 2020;3(1):33\u0026ndash;6. \u003c/li\u003e\n\u003cli\u003eMuhame RM, Mworozi EA, McAssey K, Lubega I. Thyroid autoimmunity and function among Ugandan children and adolescents with type-1 diabetes mellitus. Pan Afr Med J. 2014;19:1\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eKarat A, Radhakrishnan C, Thulaseedharan N, Kalam S. Prevalence of thyroid dysfunction and anti\u0026ndash;thyroid peroxidase antibody in gestational diabetes mellitus. J Diabetol. 2021;12(5):98. \u003c/li\u003e\n\u003cli\u003eAbdulrazaq HY, Zaboon IA, Maatook MA. Prevalence of thyroid disorders among diabetes mellitus patients in al-Basra southern of Iraq. Ann Trop Med Public Heal. 2021;24(04). \u003c/li\u003e\n\u003cli\u003eOgbonna SU, Ezeani IU. Risk factors of thyroid dysfunction in patients with type 2 diabetes mellitus. Front Endocrinol (Lausanne). 2019;10(JULY):1\u0026ndash;8. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Thyroid dysfunction, diabetes mellitus, predictors, Uganda","lastPublishedDoi":"10.21203/rs.3.rs-4007813/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4007813/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eDiabetes mellitus and its consequences increase morbidity and mortality. Despite the significant consequences of thyroid dysfunction and diabetes mellitus on each other reported in literature, there is lack of information about the prevalence, patterns and predictors of thyroid dysfunction among adult diabetics in Uganda. This study was aimed at determining the prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital (FPRRH).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis was a cross sectional study conducted at FPRRH between August and October 2023. 385 Adult patients with diabetes mellitus were enrolled and assessed for thyroid dysfunction by measuring the free thyroxin (FT4), free triiodothyronine (FT3) and thyroid stimulating hormone (TSH). Thyroid dysfunction was diagnosed if any of the 3 was not in the normal ranges. The predictors of thyroid dysfunction were determined using bivariate and multivariate logistic regression analysis in SPSS version 26.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong the 385 patients enrolled, majority were female with a mean age of 54.4 (SD\u0026thinsp;=\u0026thinsp;15.8) years. The prevalence of thyroid dysfunction was 22.1% (95% CI\u0026thinsp;=\u0026thinsp;17.7\u0026ndash;26.2%). The commonest pattern of thyroid dysfunction was subclinical hypothyroidism 42 (49.4%), followed by clinical hypothyroidism 22(25.9%), subclinical hyperthyroidism 13 (15.3%) and clinical hyperthyroidism 8 (9.4%). The significant independent predictors of thyroid dysfunction were duration of DM\u0026thinsp;\u0026ge;\u0026thinsp;6 years (aOR\u0026thinsp;=\u0026thinsp;1.874, P\u0026thinsp;=\u0026thinsp;0.003), presence of DM complications [peripheral neuropathy (aOR\u0026thinsp;=\u0026thinsp;3.034, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and diabetic foot (aOR\u0026thinsp;=\u0026thinsp;5.730, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)] and having a high fasting blood sugar (aOR\u0026thinsp;=\u0026thinsp;1.729, P\u0026thinsp;=\u0026thinsp;0.017).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe prevalence of thyroid dysfunction was high. Routine screening for thyroid dysfunction should be done among adult patients with diabetes mellitus during their diabetes clinic in order to decrease the complications through early diagnosis and treatment.\u003c/p\u003e","manuscriptTitle":"Prevalence, patterns and predictors of thyroid dysfunction among adult patients with diabetes mellitus attending Fort Portal Regional Referral Hospital","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-11 19:02:41","doi":"10.21203/rs.3.rs-4007813/v1","editorialEvents":[{"type":"communityComments","content":1}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8424e111-3420-4aeb-b5fb-3ad87bcb42c4","owner":[],"postedDate":"March 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-13T15:47:23+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-11 19:02:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4007813","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4007813","identity":"rs-4007813","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}