Avoiding Short-term Femoral Neck Fracture With Imageless Computer Navigation for Hip Resurfacing
Bibliographic record
Abstract
BACKGROUND: Femoral neck fracture in hip resurfacing has been attributed to technical error during femoral head preparation. In the absence of fracture, several radiographic findings have been speculated to increase the risk of femoral component failure. QUESTIONS/PURPOSES: We examined whether (1) the use of navigation to reduce technical errors during femoral head preparation reduces the incidence of femoral neck fractures in the short-term followup period; and (2) alignment of the femoral component with the use of computer navigation reduces the incidence of femoral neck thinning, femoral stem radiolucencies, and stem migration. METHODS: We retrospectively reviewed the first 100 Birmingham Hip Resurfacings performed in 94 prospectively followed patients between October 2005 and November 2007. We examined all radiographs on last followup. Eighty-six patients of the 94 patients had a minimum followup of 2 years (mean, 2.5 years; range, 2-4.1 years). RESULTS: There were no cases of femoral neck notching, varus femoral component alignment, or femoral neck fractures in the series. Neck thinning of greater than 10% was observed in three patients and perimetaphyseal stem lucencies were noted in 10 patients. In three patients, the metaphyseal stem showed varus migration relative to the postoperative stem-shaft angle at latest followup. There was one revision to a total hip arthroplasty for deep sepsis. The overall survivorship at 4 years was 99%. CONCLUSIONS: The use of imageless computer navigation to reduce technical errors in hip resurfacing may reduce the incidence of femoral neck fracture in the short-term. However, neck thinning, stem radiolucencies, and stem migration remain radiographic sequelae of hip resurfacing despite the use of navigation for placement of the femoral component.
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| 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".