FP761SIMPLE FRAIL SCALE OUTPERFORMS OTHER FRAILTY INSTRUMENTS REGARDING DIALYSIS COMPLICATIONS IN RURAL CHRONIC DIALYSIS PATIENTS
Bibliographic record
Abstract
Introduction and Aims: Frailty has been recognized as an important geriatric outcome predictor. However, few studies focus on its influence on rural patients undergoing chronic dialysis. Comparison of different self-report questionnaires for frailty assessment among these patients has not been attempted before. Methods: A prospectively enrolled rural chronic dialysis cohort was used for analysis. Six types of self-report questionnaires were administered to these patients. Correlation analyses between questionnaire results and clinical parameters/dialysis complications, including anemia, inflammation, and dyselectrolytemia were performed. Variables demonstrating significant correlations were further tested in multiple regression analyses to determine their associations. Results: Six types of questionnaire (Strawbridge questionnaire, Edmonton Frail Scale, simple FRAIL scale, Groningen Frail Indicator, G8 questionnaire, and Tilburg Frail Indicator) were provided to rural patients undergoing chronic dialysis. Scores from each questionnaire were significantly associated with each other, except the G8 questionnaire. Scores from the simple FRAIL scale correlated significantly with age (p = 0.02), female gender (p = 0.03), higher Liu’s comorbidity index (p = 0.02), lower serum albumin (p = 0.03) and creatinine levels (p < 0.01), and higher ferritin levels (p = 0.02) (figure). The other 5 questionnaires did not show consistently significant relationships with important dialysis-related complications. Multivariate linear regression analysis confirmed an independently negative association between serum albumin and the simple FRAIL scale scores (p = 0.01).
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".