Use of the FRAIL Questionnaire in Patients With End-Stage Kidney Disease
Bibliographic record
Abstract
Background: Frailty is a clinical phenotype of decreased physiologic reserve that is associated with increased morbidity and mortality. The most meaningful way to assess frailty in patients with end-stage kidney disease (ESKD) is unknown. Objective: To assess the prevalence of frailty in ESKD patients using the easy-to-administer FRAIL scale and, to determine its association with mortality, transplantation, and hospitalization. Design: A cohort study was used. Setting: The Ottawa Hospital, Ottawa, Ontario, Canada, was the setting of this study. Patients: All eligible adult ESKD patients treated with dialysis from August to November 2017 at The Ottawa Hospital were invited to participate. Measurements: The FRAIL scale. Methods: Eligible patients completed an exercise survey with FRAIL questions embedded within the instrument. Number of comorbid illnesses was determined from the electronic medical record and weight loss was calculated from target weight in the patients’ dialysis prescription. Mortality, transplant status, and hospitalizations were ascertained from the electronic medical record 18 months later; differences by frailty status were evaluated using descriptive statistics. Kaplan-Meier and Cox regression models were used to examine the association between frailty and transplant. Results: Of 476 ESKD patients screened, 261 participated; 101 receiving peritoneal dialysis, 135 intermittent hemodialysis, and 25 home hemodialysis. Thirty-nine, 145, and 77 were frail, pre-frail, and not frail, respectively. Employment status, ethnicity, and comorbid illnesses differed significantly by frailty status, but mortality did not. In univariate analysis, frail patients were less likely to be listed for ( P = .05) and to receive a kidney transplant ( P = .02). However, after adjusting for age and modality, frailty was not statistically associated with a decreased likelihood of transplant (Hazard Ratio: 0.15; confidence interval [CI], 0.02-1.15; P = .068). The results were similar when accounting for the competing risk of death ( P = .060). Frail patients were more likely to be hospitalized ( P = .01) and spend more time in the hospital ( P = .04). Limitations: Single-center design with a relatively short follow-up and small sample size limiting the number of variables that could be assessed in analysis. We also excluded patients who were unable to communicate in English or French and those patients with physical limitations such as amputations, potentially affecting generalizability. Conclusions: Frail ESKD patients as identified by the FRAIL scale are less likely to receive a renal transplant; this association diminished statistically after adjusting for age and modality and when accounting for the competing risk of death. Frail patients were at increased risk of hospitalization. Further study with larger patient numbers and longer follow-up is needed to determine the usefulness of the FRAIL scale in predicting adverse outcomes. Trial registration: Not required as this was an 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 | 0.002 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".