The association between preoperative modified frailty index and postoperative complications in Chinese elderly patients with hip fractures
Bibliographic record
Abstract
Abstract Objectives To investigate the role of a preoperative modified frailty index (mFI) based on data from medical records in predicting postoperative complications among older Chinese patients with hip fractures. Methods This retrospective cohort study included consecutive older patients with hip fracture admitted to the Department of Orthopaedics, West China Hospital, Sichuan University, from December 2010 to June 2017 who underwent surgical repair. We selected 33 variables, including characteristics of hip fracture, to construct a mFI. Each variable was coded with a value of 0 when a deficit was absent or 1 when it was present. We calculated the mFI as the proportion of positive items and defined frailty as mFI value greater than or equal to 0.21 according to threshold proposed by Hoover et al. We examined the relationship between mFI and severity of postoperative complications and the occurrence of in-hospital pneumonia including statistical adjustment for several demographics (e.g. age, gender, and marital status) and habits (smoking and alcohol intake), time from fracture to surgery in the multivariable model. Results We included 965 patients (34% male; mean age: 76.77 years; range: 60 to 100 years) with a prevalence of frailty of 13.06%. The presence of frailty was associated with a higher severity of complications (OR: 2.07; 95% CI: 1.40 to 3.05). Frail patients were more likely to develop in-hospital pneumonia than non-frail patients (OR: 2.08; 95% CI: 1.28 to 3.39). Conclusion The preoperative modified frailty index based on data from medical records proved significantly associated with postoperative complications among older patients with hip fractures undergoing hip surgery.
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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) | 0.000 | 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) | 0.006 | 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".