Timing of hip hemiarthroplasty and the influence on prosthetic joint infection
Bibliographic record
Abstract
INTRODUCTION: Previous research suggested that patients have increased risk of infection with increased time from presentation with a femoral neck fracture to treatment with a hip hemiarthroplasty (HHA). The purpose of this study was to determine if rates of prosthetic joint infections within 3 months of surgery was affected by the time from patient presentation with a femoral neck fracture to the time of treatment with HHA. MATERIALS AND METHODS: Acute hip fractures treated with HHA between 2005 and 2017 at three centres in Norway were enrolled in the study. Multi-trauma patients were excluded. Univariable analysis was performed to determine any significant effect of pre-operative waiting time on infection rate. Two pre-planned analyses dichotomizing pre-operative waiting time cut-offs were performed. RESULTS: There were 2300 patients with an average age of 82 (range, 48-100) years included of which 3.4% experienced a prosthetic joint infection within 3 months. The primary analysis found no significant difference in infection rate depending on time to surgery (OR = 1.06 (95% CI 0.94-1.20, p = 0.33)). The secondary analyses showed no significant differences in infection rates when comparing pre-operative waiting time of <24 hours vs ≥24 hours (OR = 0.92 (95% CI 0.58-1.46, p = 0.73)) and <48 hours vs ≥48 hours (OR = 1.39 (95% CI 0.81-2.38, p = 0.23)). CONCLUSION: Based off of a large retrospective Norwegian database of hip fractures there did not appear to be a significant difference in infection rate based on pre-operative wait time to surgery.
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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 | 0.000 |
| 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".