Randomized Controlled Trial of Incisional Negative Pressure Following High-Risk Direct Anterior Total Hip Arthroplasty
Bibliographic record
Abstract
Background The direct anterior (DA) approach to total hip arthroplasty (THA) is associated with higher rates of surgical site complications (SSCs) compared to other approaches, particularly among high-risk patients. Closed incision negative pressure therapy (ciNPT) is effective in reducing SSCs and surgical site infections (SSIs) in other populations. We asked whether ciNPT could decrease SSCs in high-risk patients undergoing DA THA. Methods This prospective randomized controlled trial (RCT) enrolled high-risk DA THA patients at 3 centers. Patients were offered enrollment if they had previously identified risk factors for SSC: Body mass index (BMI) >30 kg/m 2 , diabetes, active smoking, or before hip surgery. Patients were randomized after closure to either an occlusive (control) dressing or ciNPT dressing for 7 days. All 90-day SSCs were recorded. A priori power analysis demonstrated 116 patients were required to identify a 4.5x relative reduction in SSCs. Chi-square tests were used to evaluate probability of complications. Results One hundred and twenty two patients enrolled; 120 completed data collection. SSCs occurred in 18.3% (11/60) of control patients compared to 8.3% (5/60) of ciNPT patients (χ 2 = 2.60, P = .107). SSCs included dehiscence to the subcutaneous level (13) and prolonged drainage (3). Nine control (15.0%) and 2 ciNPT (3.3%) patients met CDC criteria for superficial SSI (χ 2 = 4.90, P = .027). Fifteen of 16 SSCs resolved with local wound care. One in the ciNPT group required reoperation for acute PJI. Conclusion Among patients at risk of surgical site complications undergoing DA THA, we identified a significant reduction in superficial SSIs and a trend toward lower overall SSCs with ciNPT.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".