PS-P11-2: THE PATTERN OF PHYSICAL DISABILITY AND DETERMINANTS OF ACTIVITIES OF DAILY LIVING AMONG DIABETIC PATIENTS IN BANGLADESH: A CROSS-SECTIONAL ANALYSIS.
Bibliographic record
Abstract
Objective: Diabetes mellitus is a known predictor of physical disability and decline in activities of daily living (ADL); however, there are existing controversies about the factors explaining the association between diabetes and disability. Therefore, we assessed the proportion of physical disabilities and possible factors associated with ADL decline among diabetic patients in Bangladesh. Design and Methods: We conducted a cross-sectional study among 480 diabetic individuals from a tertiary level hospital in Dhaka, Bangladesh, aged between 40 and 85 years. For determining the ADL decline, we used the Katz Index Scoring, the highest score of 6 indicates no ADL decline. We divided patients into two groups depending on ADL impairment to compare the population characteristics using the unpaired Students t-test or Wilcoxon rank-sum test for continuous variables and the chi-squared test for categorical variables. Age, sex, educational attainment, household expenditure, BMI, HbA1c, hypertension, and medication adherence to anti-diabetic drugs were included in the statistical models. We defined any ADL decline as an event, and multivariable logistic regression was performed to assess the factors associated with ADL decline. Results: The mean age of the participants was 59.0 (standard deviation [SD], 7.0) years. The majority of the participants (76.3%) had at least some sort of physical disability. Age, educational attainment, household expenditure, systolic blood pressure, waist circumference, quality of life, and comorbidities were different among the groups stratified by ADL impairment status. In multivariable logistic regression analysis after adjusting for all covariates simultaneously, age (OR, 95% CI: 1.35, 1.20–1.75), lower educational attainment (0.97, 0.94–0.99), BMI (1.40, 1.12–1.75), existing comorbidities (2.79, 1.48–5.25) and uncontrolled diabetes (1.35,1.10–1.45) were independently associated with ADL decline among diabetic population. Conclusions: Physical disability was common, and ADL decline was associated with age, educational attainment, BMI, comorbidities, and uncontrolled diabetes among diabetic patients in Bangladesh.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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 | 0.001 |
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".