Application value of different frailty assessment tools in older patients undergoing major abdominal surgery
Bibliographic record
Abstract
BACKGROUND: Multiple frailty assessment tools are available for clinical practice, but the optimal tool remains unclear. This study aimed to compare the diagnostic performance of frail scale (FS), frailty phenotype (FP),11-item modified frailty index (mFI-11), Edmonton Frail Scale (EFS), and Tilburg Frailty Indicator (TFI) for frailty taking the comprehensive geriatric assessment (CGA) as the gold standard, and their ability to predict 30-day postoperative complications and prolonged length of stay (PLOS). METHODS: This study recruited older patients (≥ 65 years) undergoing elective major abdominal surgery. The receiver operating characteristic (ROC) curves, technique for order preference by similarity to ideal solution (TOPSIS), and decision analysis curve (DCA) were used to validate the diagnostic, comprehensive, and predictive performance of 5 tools in frailty, complications, and PLOS. RESULTS: EFS presented moderate consistency with CGA (Kappa = 0.544, P < 0.001), excellent performance in diagnosing frailty (area under the ROC curve (AUC) = 0.881, P < 0.001), and high clinical net benefit within the risk threshold ranging from 0.8 % to 57.44 %. Although EFS had the largest AUC for predicting complications (AUC = 0.612) and PLOS (AUC = 0.642) and showed high clinical net benefit, its predictive performance was poor (AUC < 0.7). The TOPSIS indicated that EFS required optimization in multiple aspects (closeness coefficient (Ci) < 0.8). CONCLUSION: EFS has excellent diagnostic performance and clinical net benefit for frailty. However, further research is required to identify optimal tools or combine EFS with additional indicators to enhance its comprehensive and predictive performance for complications and PLOS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".