Predictors of progression from pre-frailty to frailty in older people: a systematic review and meta-analysis protocol
Bibliographic record
Abstract
INTRODUCTION: Frailty is a global health issue, particularly among older adults, and is strongly associated with adverse health outcomes. The intermediate stage of pre-frailty, which represents a transition from robust health to frailty, has garnered growing concern due to its potential reversibility. This systematic review and meta-analysis will aim to identify predictors associated with the progression from pre-frailty to frailty in older adults. METHODS AND ANALYSIS: A comprehensive literature search will be conducted in PubMed, Web of Science, Embase, Cochrane Library, CINAHL, PsycINFO, CNKI, Wanfang Database, China Science and Technology Journal Database, and China Biomedical Literature Database from inception to the most recent search date. Eligible studies will report predictors of frailty progression among older adults with pre-frailty at baseline. Two reviewers will independently screen the studies, extract relevant data and assess methodological quality using the Newcastle Ottawa Scale. Meta-analysis and meta-regression will be performed to estimate pooled effect sizes and explore potential predictors. Subgroup analyses will be conducted to investigate possible sources of heterogeneity. ETHICS AND DISSEMINATION: Ethical approval will not be required, as this study will not involve primary data collection. The findings will be submitted for publication in a peer-reviewed scientific journal. PROSPERO REGISTRATION NUMBER: CRD42024594175.
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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 | 0.068 | 0.081 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.022 | 0.022 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.067 | 0.008 |
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".