Modes of failure of hip hemiarthroplasty for femoral neck fracture
Bibliographic record
Abstract
<h3>Background:</h3> Hemiarthroplasty is a common treatment for displaced femoral neck fractures, but limited Canadian data are available about hemiarthroplasty failure. We evaluated the frequency and predictors of hemiarthroplasty failure in Manitoba. <h3>Methods:</h3> In this retrospective multicentre province-wide study, billing and joint registry databases showed 4693 patients who had hemiarthroplasty for treatment of femoral neck fracture in Manitoba over an 11-year period (2005–2015), including 155 hips with subsequent reoperations (open or closed) for treatment of hemiarthroplasty failure. Hospital records were reviewed to identify modes of hemiarthroplasty failure, comorbidities and reoperations. Data were analyzed using χ<sup>2</sup> test and Poisson and γ regression models. <h3>Results:</h3> During our study period, 155 hips (154 patients [3%]) underwent 230 reoperations. Of these, 131 hips (85%) initially had an uncemented unipolar modular implant. Indications for first-time reoperation included periprosthetic femur fracture (49 hips [32%]), dislocation (45 hips [29%]), acetabular wear (28 hips [18%]) and infection (26 hips [17%]). There were 46 hips (30%) that had 2 or more reoperations. Reoperation for dislocation was associated with presence of dementia; acetabular wear was associated with absence of dementia. Time from hemiarthroplasty to reoperation was associated inversely with age at hemiarthroplasty, dislocation and dementia and was directly associated with acetabular wear. The risk of having 2 or more reoperations was associated independently with dislocation, infection, and alcohol abuse. <h3>Conclusion:</h3> Hemiarthroplasty for femoral neck fracture in Manitoba had a low frequency of failure. Risk factors for multiple reoperations included dislocation, infection and alcohol abuse.
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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) | 0.001 | 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 | 0.000 |
| 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 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".