Frailty, Age, and Postdialysis Recovery Time in a Population New to Hemodialysis
Bibliographic record
Abstract
Background: Frailty, a phenotype characterized by decreased physiologic reserve and the inability to recover following confrontation with a stressor like hemodialysis, may help identify which patients on incident hemodialysis will experience longer postdialysis recovery times. Recovery time is associated with downstream outcomes, including quality of life and mortality. We characterized postdialysis recovery times among patients new to hemodialysis and quantified the association between frailty and hemodialysis recovery time. Methods: Among 285 patients on hemodialysis enrolled in the Predictors of Arrhythmic and Cardiovascular Risk in End Stage Renal Disease (PACE) study, frailty was measured using the Fried phenotype. Self-reported recovery time was obtained by telephone interview. We estimated the association of frailty (intermediately frail and frail versus nonfrail) and postdialysis recovery time using adjusted negative binomial regression. Results: Median time between dialysis initiation and study enrollment was 3.4 months (IQR, 2.7-4.9), and that between initiation and recovery time assessment was 11 months (IQR, 9.3-15). Mean age was 55 years, 24% were >65 years, and 73% were Black; 72% of individuals recovered in ≤1 hour, 20% recovered in 1-6 hours, 5% required 6-12 hours to recover, and <5% required >12 hours to recover. Those with intermediate frailty, frailty, and age ≤65 years had 2.56-fold (95% CI, 1.45 to 4.52), 1.72-fold (95% CI, 1.03 to 2.89), and 2.35-fold (95% CI, 1.44 to 3.85) risks, respectively, of longer recovery time independent of demographic characteristics, comorbidity, and dialysis-related factors. Conclusions: In adults new to hemodialysis, frailty was independently associated with prolonged postdialysis recovery. Future studies should assess the effect of frailty-targeted interventions on recovery time to improve clinical outcomes.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".