Frailty Assessment Tools in Chronic Kidney Disease: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
Rationale & Objective: Frailty represents a loss of physiologic reserve across multiple biological systems, confers a higher risk of adverse health outcomes, and is highly prevalent among people with chronic kidney disease (CKD). We evaluated the measurement properties of frailty tools used in CKD and summarized the association of frailty with death and hospitalization. Study Design: Systematic review and meta-analysis. Setting & Study Populations: Studies assessing multidimensional frailty tools in adults at any stage of CKD and evaluating a measurement property of interest as per the Consensus-based Standards for the Selection of Health Measurement Instruments taxonomy. Selection Criteria for Studies: Observational studies and randomized trials. Data Extraction: Risk and precision measurements; measurement properties. Analytical Approach: The Comprehensive Geriatric Assessment was the clinical standard for frailty identification. We pooled data using random effects models or summarized with narrative synthesis when data were too heterogenous to pool. Results: = 66%) in frail versus non-frail. The Fatigue, Resistance, Ambulation, Illness, and Loss of weight scale showed consistent discriminative validity for higher mortality in non-dialysis CKD. The modified FFP (self-reported) showed acceptable discriminative validity and agreement with the FFP in patients with KF. In CKD and KF populations, agreement between clinicians' subjective impression of frailty and frailty tools was low. Limitations: Few studies compared the accuracy of frailty tools to the Comprehensive Geriatric Assessment. Only 1 study reported reliability. Studies were of overall low-moderate quality. Conclusions: The FFP and Clinical Frailty Scale showed acceptable discriminant validity for clinical outcomes, and the modified FFP is an alternative tool to use if direct measurements are not feasible. The evidence does not support the use of clinicians' subjective impression to identify 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 | 0.022 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.032 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".