Frailty in Diabetic Population: A Study From Northern India
Bibliographic record
Abstract
Introduction Frailty, a key issue in geriatric health, signifies heightened vulnerability due to the decline in various physiological systems, exacerbated by conditions such as diabetes. Diabetes and frailty together lead to significant disabilities and higher mortality, necessitating early screening and targeted interventions. The relationship between frailty and diabetes remains under-researched, prompting this study to explore their association in individuals over 50 years of age using the Edmonton Frail Scale (EFS). Methods and materials The study was an observational cross-sectional study conducted at MM Institute of Medical Sciences & Research (MMIMSR), Mullana, India, among 102 diabetic and 100 non-diabetic individuals aged more than 50 years, with data collected through interviews using a pre-validated proforma. Frailty was assessed using the EFS, categorizing patients into fit, vulnerable, and various levels of frailty based on their scores. Results The study found a higher prevalence and severity of frailty among diabetic individuals (61.8%) compared to non-diabetics (29%), with frailty being more pronounced across all age groups and both genders in diabetics. The severity of frailty increased with the duration of diabetes but showed no significant correlation with glycemic control (HbA1c). Strengths and limitations The study prospectively collected data, including middle-aged participants starting from age 50, and uniquely used the EFS to assess frailty in diabetic patients, excluding those with other chronic diseases (end-stage renal disease (ESRD), malignancy, etc.). However, limitations included a small sample size, recruitment from a single institution in India, and some EFS questions being less relevant to the Indian diabetic population. Conclusion The study found a 61.8% prevalence of frailty in diabetics compared to 29% in non-diabetics, with frailty being more severe and positively correlated with the duration of diabetes but not with glycemic control (HbA1c).
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".