Comparison of instruments for screening frailty in community-dwelling older adults
Bibliographic record
Abstract
Objective: To conduct a systematic review of studies that verify the comparison between frailty assessment instruments. Methods: Systematic review conducted between January and March 2023 in an electronic database (LILACS and MEDLINE). For the construction of the search strategies, an adaptation of the acronym PICO was used, where P = population (community-dwelling elderly), I: phenomenon of interest (comparison of frailty by different instruments) and CO = context (Primary Health Care). In the searches, the terms "elderly" AND "fragility" AND "instruments" and "Elderly" AND "fragility" AND "instrument" were considered, and the final selection resulted in 13 articles. Results: The comparison between the Edmonton Frailty Scale (EFS) and the Clinical Functional Vulnerability Index (IVCF-20) showed moderate agreement and a strong positive correlation. However, the prevalence of frailty was discrepant, being higher when EFE was used. When analyzing the agreement between the Subjective Assessment of Frailty (SFA) and the IVCF-20, the results indicated weak agreement in the classification of frailty between these instruments. However, moderate agreement was found when the outcome was dichotomized into "frail" and "non-frail". Despite evaluating similar concepts, SFA and IVCF-20 are complementary and one cannot replace the other. Conclusions: Although several studies address different frailty assessment instruments, there is still a scarcity of studies investigating the agreement between these instruments and, in addition, the results presented reinforce the need for a standardized instrument to measure frailty in the elderly in Primary Health Care.
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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 | 0.033 | 0.136 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.018 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".