Longitudinal Measures of Short Physical Performance Battery and Risk for CKD Progression and Death
Bibliographic record
Abstract
Background: We aimed to characterize physical performance using the Short Physical Performance Battery (SPPB) and test whether physical performance is associated with incident kidney failure and death in a cohort of adults with chronic kidney disease (CKD). Methods: Using data from the Chronic Renal Insufficiency Cohort (CRIC) Study, we calculated SPPB scores from three performance measures (standing balance, gait speed, chair stands). SPPB scores were categorized into peformance levels using validated cut-offs: low (0-6), moderate (7-9), and high (10-12). We estimated the associations of baseline SPPB and longidutinal SPPB change, modelled continuously and by performance category, with incident kidney failure and death using multivariable Cox models. Results: Among 3,038 participants, mean age was 64 years, 40% were Black, 52% had diabetes and mean eGFR was 52 ml/min/1.73m^2. Median (IQR) follow up was 8.5 years (7-10). The baseline median (IQR) SPPB score was 10 (8-11), indicating median high performance. In fully adjusted models, lower baseline SPPB scores (per 1-unit) and low and moderate performance categories were associated with increased risk of death (Table). As a linear measure, SPPB declines were associated with higher risk of death; and a >2 point decline was associated with 78% higher mortality risk compared to no change (Table). Baseline and SPPB change were not associated with incident kidney failure. Conclusion: Baseline physical peformance and its changes over time, as measured by the SPPB, are independently associated with death. The SPPB may be a useful tool for risk assessment in this population. Funding: NIDDK Support
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".