Instability after hip hemiarthroplasty for femoral neck fracture: an unresolved problem
Bibliographic record
Abstract
Background: The dislocated hip hemiarthroplasty (HA) remains a difficult condition to treat owing to frailty, comorbidity, poor quality of bone and soft tissues. We aimed to identify parameters contributing to instability following hip HA and describe the operative management and patient outcomes. Methods: We retrospectively reviewed consecutive cases of all patients with hip fracture treated between 2004 and 2019 at a single tertiary care institution. We propensity matched patients with and without hip dislocations on a 1:2 basis for age, sex, and approach. We reviewed risk factors for HA dislocation, performed radiographic measurements, and recorded management of dislocation and further complications. Results: Of the 1472 patients treated with HA, we included 18 patients (1.2%) who sustained at least 1 dislocation in our analysis. Of the dislocations identified, 13 and 17 occurred within 1 and 3 months postoperative, respectively. The presence of dementia and low preoperative lateral centre-edge angle were associated with increased risk of dislocation. The 2-year mortality rate was significantly higher in the dislocation group (n = 9) than the control group (n = 2) (p = 0.0003). Nine of 18 (50%) patients were treated with an initial closed reduction; 5 of these 9 (56%) sustained further dislocations and required additional treatment. Six of 18 cases were treated with a total hip arthroplasty after their first dislocation. By final follow-up, 2 of 18 patients had Girdlestone procedures. Conclusion: This study highlights patient factors associated with increased dislocation risk following hip HA. A thorough preoperative assessment is indicated when presented with dislocated HA to prevent further complications.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".