High rate of reoperation and conversion to total hip arthroplasty after internal fixation of young femoral neck fractures: a population-based study of 796 patients
Bibliographic record
Abstract
Background and purpose - Most often, the goal of non-geriatric femoral neck fracture surgery is to preserve the native hip joint. However, reoperations for painful implants, osteonecrosis, and nonunion are common. We determined the reoperation rate and time-to-reoperation following internal fixation of these fractures in a large population cohort. Patients and methods - This retrospective cohort study included patients between the ages of 18 and 50 years old who underwent internal fixation for a femoral neck fracture during 1997-2013. Patients were followed until December 2013. Primary outcomes were reoperation rate and time-to-reoperation. Time-to-event analysis was performed to estimate the rate of any reoperation and for THA specifically, while testing the dependency of time-to-reoperation on secondary variables. Results - 796 young femoral neck fracture patients were treated with internal fixation during the study period (median age 43 years, 39% women). Median follow-up was 8 years (IQR 4-13). One-third underwent at least 1 reoperation at a median 16 months after the index surgery (IQR 8-31). Half of reoperations were for implant removal, followed by conversion to total hip arthroplasty. 14% of the cohort were converted to THA. The median time to conversion was 2 years (IQR 1-4). Neither female sex nor older age had a statistically significant effect on time-to-reoperation or time-to-THA conversion. Interpretation - Following internal fixation of young femoral neck fracture, 1 in 3 patients required a reoperation, and 1 in 7 were converted to THA. These data should be considered by patients and surgeons during treatment decision-making.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".