Preinjury Aerobic Fitness Predicts Postoperative Outcome and Activity Level After Acetabular Fracture Fixation
Bibliographic record
Abstract
OBJECTIVES: To investigate whether aerobic fitness as determined by preoperative metabolic equivalents (METS) better predicts postoperative functional outcomes after open reduction and internal fixation (ORIF) of acetabular fractures than chronologic age. DESIGN: Retrospective review. SETTING: Level 1 Trauma Center. PATIENTS/PARTICIPANTS: A total of 157 patients underwent open surgical treatment for acetabular fracture between January 2005 and December 2013 with age ≥18 years and minimum 1-year follow-up inclusive of imaging, functional outcome scores, and complications. INTERVENTION: ORIF of acetabular fracture. MAIN OUTCOME MEASUREMENTS: Final postoperative functional outcomes as assessed with the University of California Los Angeles activity score and the Western Ontario and McMaster Universities Osteoarthritis Index. RESULTS: Multivariate logistic regression analysis demonstrated elevated preinjury METS, female gender, and lower injury severity score (<18) to be significant independent factors predictive of improved functional outcome per the University of California Los Angeles score. Similarly, preinjury METS were identified as significant predictors for improved Western Ontario and McMaster Universities Osteoarthritis Index scores for both the stiffness and physical function components. Chronologic age was not a significant predictor for any functional outcome score. Furthermore, a Pearson correlation analysis demonstrated a weak relationship between preoperative METS and chronologic age (r = -0.346). CONCLUSIONS: Pre-operative aerobic fitness as determined by METS may prove to be a superior prognostic factor for predicting postoperative functional outcome after acetabular fracture fixation than chronologic age. Consideration of aerobic fitness, in addition to other established prognostic factors, may be useful to patients and surgeons for injury counseling purposes. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".