Spontaneous healing of lateral femoral cutaneous nerve injury and improved quality of life after total hip arthroplasty via a direct anterior approach
Bibliographic record
Abstract
PURPOSE: How the symptomatology of lateral femoral cutaneous nerve (LFCN) injury changes after total hip arthroplasty (THA) via direct anterior approach (DAA) is not known. Our hypothesis was that the symptoms of LFCN injury after THA via DAA in longer follow-up periods would resolve spontaneously, leading to an improved quality of life (QOL). The aims of this study were to investigate how the symptom LFCN injury changed after DAA-THA, and how those changes affected QOL. METHODS: We investigated the incidence of LFCN injury after DAA-THA using self-reported questionnaires at two time points (initial survey: August 2014, present survey: August 2015). QOL was assessed by the Western Ontario and McMaster Universities Osteoarthritis Index, the Japanese Orthopaedic Association Hip Disease Evaluation Questionnaire, and the Forgotten Joint Score-12 (FJS-12). Types (dysesthesia or hypesthesia) and changes of the symptom were surveyed. RESULTS: About 122 hips at average12.8 months postoperatively (initial survey), and of those, 89 hips at average 26.2 months postoperatively (present survey) were analyzed. The incidence of LFCN injury decreased significantly, from 31.9% to 11.2% ( p < 0.001). Spontaneous improvement of symptoms was seen in 96%. The difference of FJS-12 between patients with and without LFCN injury at the initial survey disappeared at the present survey. The dysesthesia group showed significant correlations between rate of improvement in LFCN injury and increase of QOL. CONCLUSION: Most symptoms of LFCN injury resolved spontaneously with longer follow-up periods. In particular, improvement of dysesthesia as a symptom of LFCN injury was associated with better QOL.
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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 | 0.000 |
| 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".