The Effect of Total Hip Arthroplasty on the Sciatic Nerve: an Electrodiagnostic Evidence Study.
Bibliographic record
Abstract
OBJECTIVE: Objectively evaluate the incidence of sciatic nerve injury after a total hip arthroplasty (THA) performed through a posterolateral approach. METHODS: Patients scheduled to undergo THA were evaluated preoperatively and postoperatively with electrophysiologic studies, the Western Ontario and McMaster Universities Osteoarthritis index (WOMAC) questionnaire and other methods described in the study. Patients older than 21 years with any of the following preoperative diagnoses: primary or secondary osteoarthritis, aseptic avascular necrosis, rheumatoid arthritis, and posttraumatic arthritis were included. Variables used for analysis were sex, age, and body mass index (BMI). The Mann-Whitney U and Wilcoxon tests and, Pearson and Spearman correlation statistics were used for analysis of categorical and continuous data respectively. RESULTS: Electrodiagnostic data showed alterations in 17 patients (70.8%). No signs of sciatic nerve injury. The mean preoperative and postoperative WOMAC scores were 40 and 74, respectively (p = 0.0001). Statistical differences were noted in sural sensory amplitude (SSA) and distal amplitude of the tibialis motor nerve in the female group (p=0.007; p=0.036, respectively). The SSA also demonstrated differences in the obese group (p=0.008). In terms of age, both the SSA (Pearson p=0.010 and Spearman p=0.024) and the proximal latency of the peroneal motor nerve (Pearson p=0.026 and Spearman p=0.046) demonstrated a decrease in amplitude and an increase in latency that was inversely related with age. CONCLUSION: According to our subclinical electrophysiological findings, surgeons that use the posterolateral approach in THA procedures must be conscious of the sciatic nerve's vulnerability to reduce possible clinical complications.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".