Natural Regression of Frailty Among Community-Dwelling Older Adults: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Frailty is a dynamic process with potential transitions over time. However, there is limited understanding of the patterns of frailty improvement. We conducted a systematic review and meta-analysis to estimate the natural rate of frailty regression among community-dwelling older adults aged at least 60 years. RESEARCH DESIGN AND METHODS: Systematic searches for studies reporting frailty improvement were performed in 5 databases (Medline, Embase, CINAHL plus, Web of Science, and PsycINFO) from inception until January 2019. RESULTS: Twenty-five studies from 26 countries were included. Among a baseline population of more than 50,000 individuals, the pooled prevalence of pre-frailty and frailty was 50.5% (95% confidence interval [CI] 47.8-53.3) and 12.8% (95% CI 9.1-17.0), respectively. During a median follow-up of 3.0 (range 1-10.0) years, 23.3% of surviving pre-frail individuals regressed to a robust state and 35.2% of surviving frail individuals reversed to a pre-frail or robust state. The pooled remission rates among people with pre-frailty and frailty were 80.4 (95% CI 61.7-104.6) and 135.3 (95% CI 98.1-186.5) per 1,000 person-years, respectively. Frailty and pre-frailty improvement rates varied by sex, diagnostic criteria, study region, and follow-up duration. The remission rates were significantly reduced when accounting for progressions to death. The heterogeneity of included studies was high which reflected considerable differences in methodological approach. DISCUSSION AND IMPLICATIONS: Although frailty is highly prevalent in older people, natural remission is possible and common. Improved understanding of the factors that confer increased likelihood of frailty regression may support the design of interventions to reduce the burden of frailty.
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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 | 0.020 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.037 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".