The prevalence and trajectory of frailty in older surgical patients: A longitudinal multicentre cohort study
Bibliographic record
Abstract
BACKGROUND: Frailty is a state of increased vulnerability and decreased physiological reserve, which can reduce one's capacity to cope with external stressors such as a major surgery. We aimed to (1) investigate the preoperative and postoperative prevalence of frailty in older surgical patients; and (2) evaluate preoperative risk factors associated with postoperative frailty. METHODS: This multicentre prospective study included 307 non-cardiac surgical patients aged ≥65 years. Clinical frailty was assessed online using the five-item FRAIL scale (Fatigue, Resistance, Ambulation, Illness, weight-Loss) preoperatively and postoperatively at 30, 90, and 180 days. Trajectories of FRAIL scores were assessed with linear mixed-effects models, stratified by preoperative frailty. Preoperative risk factors associated with frailty at 180 days were explored by logistic regression. RESULTS: Preoperatively, 36% of patients were robust, 52% were prefrail, and 12% were frail. Frail patients experienced a significant improvement in frailty by 90 and 180 days. Prefrail patients experienced a transient worsening of frailty level with subsequent improvement by 180 days. Robust patients experienced similar worsening in frailty but remained clinically robust, despite a small absolute difference in FRAIL score. Preoperative frailty and functional disability were both associated with greater odds of 180-day frailty (aOR 2.65, 95% CI [1.51, 4.97] and aOR 4.71, 95% CI [1.41, 15.65], respectively). CONCLUSIONS: The prevalence of preoperative prefrailty and frailty was high among older surgical patients. A high preoperative FRAIL score and severe functional disability were associated with greater odds of postoperative 180-day frailty. Preoperative frailty assessment can risk-stratify patients and inform postoperative targets. REGISTRATION: The trial was registered on www. CLINICALTRIALS: gov on April 7, 2021 (NCT04850833).
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| 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".