Frailty and the Kidney Transplant Wait List: Protocol for a Multicenter Prospective Study
Bibliographic record
Abstract
BACKGROUND: Understanding how frailty affects patients listed for transplantation has been identified as a priority research need. Frailty may be associated with a high risk of death or wait-list withdrawal, but this has not been evaluated in a large multicenter cohort of Canadian wait-listed patients. OBJECTIVE: The primary objective is to evaluate whether frailty is associated with death or permanent withdrawal from the transplant wait list. Secondary objectives include assessing whether frailty is associated with hospitalization, quality of life, and the probability of being accepted to the wait list. DESIGN: Prospective cohort study. SETTING: Seven sites with established renal transplant programs that evaluate patients for the kidney transplant wait list. PATIENTS: Individuals who are being considered for the kidney transplant wait list. MEASUREMENTS: We will assess frailty using the Fried Phenotype, a frailty index, the Short Physical Performance Battery, and the Clinical Frailty Scale at the time of listing for transplantation. We will also assess frailty at the time of referral to the wait list and annually after listing in a subgroup of patients. METHODS: The primary outcome of the composite of time to death or permanent wait-list withdrawal will be compared between patients who are frail and those who are not frail and will account for the competing risks of deceased and live donor transplantation. Secondary outcomes will include number of hospitalizations and length of stay, and in a subset, changes in frailty severity over time, change in quality of life, and the probability of being listed. Recruitment of 1165 patients will provide >80% power to identify a relative hazard of ≥1.7 comparing patients who are frail to those who are not frail for the primary outcome (2-sided α = .05), whereas a more conservative recruitment target of 624 patients will provide >80% power to identify a relative hazard of ≥2.0. RESULTS: Through December 2019, 665 assessments of frailty (inclusive of those for the primary outcome and all secondary outcomes including repeated measures) have been completed. LIMITATIONS: There may be variation across sites in the processes of referral and listing for transplantation that will require consideration in the analysis and results. CONCLUSIONS: This study will provide a detailed understanding of the association between frailty and outcomes for wait-listed patients. Understanding this association is necessary before routinely measuring frailty as part of the wait-list eligibility assessment and prior to ascertaining the need for interventions that may modify frailty. TRIAL REGISTRATION: Not applicable as this is a protocol for a prospective observational study.
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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 | 0.052 | 0.033 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.048 | 0.010 |
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".