Prevalence of Type 2 Diabetes Mellitus among Hypertensive Patients Attending in A Tertiary Level Hospital in Bangladesh
Bibliographic record
Abstract
This cross-sectional, descriptive study was conducted in the Department of Cardiology of Community Based Medical College, Bangladesh (CBMC,B) Hospital, Mymensingh, Bangladesh, between January and June of 2023, among the hypertensive patients to estimate the prevalence of type 2 diabetes mellitus and pre-diabetes (PD). A total of 93 patients with hypertension were purposively selected. Previously diagnosed diabetic patients were excluded from the study. Sociodemographic data were collected by face-to-face interview by using a pre-tested questionnaire. Fasting blood glucose and 2 hours after 75 gm glucose load were estimated by auto analyzer. Age, gender, weight and height and blood pressure were estimated. Body mass index (BMI) was estimated from body weight and height of the patients. Overall, DM was 21.5% and PD was 10.8% (IFG 1.1%, IGT 9.7%) evident in this study. Male showed higher prevalence of type 2 diabetes compare to female. Sex, age, occupation, education, sedentary lifestyle, increase frequency of rice eating showed no statistical significance with DM. All stages of hypertension, middle class economic status, overweight, depressives, family history of diabetes and smoking showed positive association with diabetes. Hypertension and PD showed no significant association. CBMJ 2025 July: vol. 14 no. 02 P:121-125
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".