A Comparison of Acute Complications and Mortality Between Geriatric Knee and Hip Fractures: A Matched Cohort Study
Bibliographic record
Abstract
INTRODUCTION: To compare acute complication and mortality rates for operatively treated, closed, isolated, low-energy geriatric knee fractures (distal femur [DFF] or tibial plateau [TPF]) with hip fractures (HFs). METHODS: This is a retrospective cohort study using the American College of Surgeons National Surgical Quality Improvement Program. We identified all patients ≥ 70 years from 2011 to 2016 who underwent surgery for DFF, TPF, or HF. We recorded patient demographics, functional status, complications, and mortality. We matched DFF:TPF:HF patients on a 1:1:10 ratio based on age, sex, body mass index, baseline functional status, and comorbidity. We used the chi square, Fisher exact, and Mann Whitney U tests to compare unadjusted differences between groups and multivariable logistic regression to compare the risk of complications, readmission, or death while adjusting for relevant covariates. RESULTS: When compared with HF, patients in the DFF and TPF groups had longer length of stay and time to index surgery and were more likely to be discharged home. The rate of deep vein thrombosis was significantly higher in the TPF group (TPF = 3.9%, DFF = 1.3%, and HF = 1.2%, P = 0.005). CONCLUSION: Geriatric knee fractures pose a similar risk of acute complications, mortality, and readmission compared with patients with HF. Future studies investigating strategies to decrease risk in this patient cohort are warranted. LEVEL OF EVIDENCE: Therapeutic Level III.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".