Measurement properties of performance-based measures to assess physical function in chronic kidney disease: recommendations from a COSMIN systematic review
Bibliographic record
Abstract
Background: There is wide heterogeneity in physical function tests available for clinical and research use, hindering our ability to synthesize evidence. The aim of this review was to identify and evaluate physical function measures that could be recommended for standardized use in chronic kidney disease (CKD). Methods: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, CINAHL, Scopus and Web of Science were searched from inception to March 2022, identifying studies that evaluated a clinimetric property (validity, reliability, measurement error and/or responsiveness) of an objectively measured performance-based physical function outcomes using the COnsensus-based Standards for the selection of health Measurement Instruments (COSMIN) methodology and Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) based recommendations. Studies with individuals of all ages and of any stage of CKD were included. Results: In total, 50 studies with 21 315 participants were included. Clinimetric properties were reported for 22 different physical function tests. The short physical performance battery (SPPB), Timed-up-and-go (TUG) test and Sit-to-stand tests (STS-5 and STS-60) had favorable properties to support their use in CKD and should be integrated into routine use. However, the majority of studies were conducted in the hemodialysis population, and very few provided information regarding validity or reliability. Conclusion: The SPPB demonstrated the highest quality of evidence for reliability, measurement error and construct validity amongst transplant, CKD and dialysis patients. This review is an important step towards standardizing a core outcome set of tools to measure physical function in research and clinical settings for the CKD population.
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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 | 0.094 | 0.251 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.015 |
| Bibliometrics | 0.018 | 0.012 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".