Assessment of frailty and outcome of an ethnogeriatric population in periurban slums of Delhi, India – An interventional strategy in a primary health care setting
Bibliographic record
Abstract
INTRODUCTION: The burden of frailty and aging will have a profound impact on the economy along with the deteriorating clinical condition of the olds. AIM: This study aim was to assess frailty of an ethnogeriatric cohort and associate it with domains of quality of life in Delhi along with a follow-up outcome assessment. METHOD: Edmonton frail scale on an ethnogeriatric cohort of 200 individuals in periurban slums of Delhi was used and associated with quality of life, calculated by the WHO-BREF -QOL questionnaire. An interventional strategy for healthy aging was adopted, and a follow-up outcome assessment was done to look out for mortality or morbidity. RESULT: There were 37% frail with a mean score of 60 and 25% prefrails beyond 60 years with a significant increase in frailty with age. Females, single, working, and illiterate elderly were frailer as compared to their counterparts. Social domain followed by psychological domain of the QOL had least scores in the frail elderly. Olds, away from their place of origin were 25 times more likely to be frail and had lesser family integration, assessed by regression analysis. Nearly 6% died, with 21% of hospital readmissions after a 6-month follow-up. DISCUSSION: An earlier start of assessment would give us more time to react and respond and be pro-active for healthy aging besides taking into consideration the diverse ethnography in our country. CONCLUSION: Cross-cultural variations need the physicians to address the health care disparities and language barriers so as to make interventions more convenient.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".