Incidence of Lateral Femoral Cutaneous Nerve Neuropraxia After Anterior Approach Hip Arthroplasty
Bibliographic record
Abstract
BACKGROUND: Although injury to the lateral femoral cutaneous nerve (LFCN) is a known complication of anterior approaches to the hip and pelvis, no study has quantified its' incidence in anterior arthroplasty procedures. QUESTIONS/PURPOSES: We therefore defined the incidence, functional impact, and natural history of LFCN neuropraxia after an anterior approach for both hip resurfacing (HR) and primary total hip arthroplasty (THA). METHODS: We followed 132 patients who underwent an anterior hip approach (55 THA; 77 HR). We administered self-reported questionnaires for sensory deficits of LFCN, neuropathic pain score (DN4), visual analog scale, as well as SF-12, UCLA, and WOMAC scores at one year postoperatively. A subset of 60 patients (30 THA; 30 HR) was evaluated at two time intervals. RESULTS: One hundred seven patients (81%) reported LFCN neuropraxia with a mean severity score of 2.32/10 and a mean DN4 score of 2.42/10. Hip resurfacing had a higher incidence of neuropraxia as compared with THA: 91% versus 67%, respectively. No functional limitations were reported on SF-12, WOMAC, or UCLA scores. Of the subset of 60 patients followed over an average of 12 months, 53 (88%) reported neuropraxia at the first followup interval with only three (6%) having complete resolution at second followup. Improvement in DN4 scores was observed over time: 3.6 versus 2.5, respectively. CONCLUSIONS: Although LFCN neuropraxia was a frequent complication after anterior approach THA, it did not lead to functional limitations in our patients. A decrease in symptoms occurred over time but only a small number of patients reported complete resolution. LEVEL OF EVIDENCE: Level III, therapeutic study. See Guidelines for Authors for a complete description of levels of evidence.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".