Implant Removal After Internal Fixation of a Femoral Neck Fracture
Bibliographic record
Abstract
OBJECTIVES: The effect of implant removal after internal fixation of a femoral neck fracture on physical functioning was analyzed. Characteristics of patients who had their implant removed were studied, as it is currently unknown from which type of patients implants are removed and what effect removal has on function. DESIGN: Secondary cohort study alongside a randomized controlled trial. SETTING: Multicenter study in 14 hospitals. PATIENTS AND INTERVENTION: Patients who had their implant removed after internal fixation of a femoral neck fracture are compared with patients who did not. MAIN OUTCOME MEASUREMENTS: Patient characteristics and quality of life (Short Form 12, Western Ontario McMaster Osteoarthritis Index) were compared. Matched pairs were selected based on patient/fracture characteristics and prefracture physical functioning. RESULTS: Of 162 patients, 37 (23%) had their implant removed. These patients were younger (median age: 67 vs. 72 years, P = 0.024) and more often independently ambulatory prefracture (100% vs. 84%, P = 0.008) than patients who did not. They more often had evident implant back-out on x-rays (54% vs. 34%, P = 0.035), possibly related to a higher rate of Pauwels 3 fractures (41% vs. 22%, P = 0.032). In time, quality of life improved more in implant removal patients [+2 vs. -4 points, Short Form 12 (physical component), P = 0.024; +9 vs. 0 points, Western Ontario McMaster Osteoarthritis Index, P = 0.019]. CONCLUSIONS: Implant removal after internal fixation of a femoral neck fracture positively influenced quality of life. Implant removal patients were younger and more often independently ambulatory prefracture, more often had a Pauwels 3 fracture, and an evident implant back-out. Implant removal should be considered liberally for these patients if pain persists or functional recovery is unsatisfactory. LEVEL OF EVIDENCE: Therapeutic Level II. See Instructions for Authors for a complete description of levels of evidence.
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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 | 0.001 |
| 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".