Incisional Negative Pressure Wound Therapy Decreases the Frequency of Postoperative Perineal Surgical Site Infections
Bibliographic record
Abstract
BACKGROUND: Abdominoperineal resection is a procedure associated with high rates of perineal surgical site infections, causing distress to the patient, costs to the hospital system, and delays in further treatment. OBJECTIVE: The aim of this study was to investigate the role of incisional negative pressure wound therapy in decreasing the rates of perineal surgical site infection. DESIGN: This retrospective cohort study had a historical, consecutively sampled control group. SETTINGS: This study was conducted at a single-institution tertiary care academic institution. PATIENTS: All patients undergoing an abdominoperineal resection between 2008 and 2012 were assessed. INTERVENTIONS: Perineal incisional negative pressure wound therapy was applied to all patients following an abdominoperineal resection between 2010 and 2012 at 125 mmHg continuous suction for 5 days postoperatively. MAIN OUTCOME MEASURES: The development of a perineal surgical site infection within the first 30 days postoperatively was the primary outcome measured. RESULTS: Fifty-nine patients were included: 27 in the incisional negative pressure wound therapy group and 32 in the control group. A statistically lower proportion of perineal surgical site infections were detected in the incisional negative pressure wound therapy group than in the standard dressing group (15% vs 41%; p = 0.02). Both populations were similar in perioperative risk factors, with the exception of increased levels of blood urea nitrogen, a higher proportion of hypertensive patients, and a longer mean operative time in the incisional negative pressure wound therapy group. Additionally, an increased length of stay was observed in the incisional negative pressure wound therapy group (11 vs 8 days; p = 0.03). After adjusting for confounders, including the type of perineal dissection, incisional negative pressure wound therapy was found to be an independent predictor of not developing an surgical site infection (adjusted OR, 0.11; 95% CI, 0.04-0.66; p = 0.01). LIMITATIONS: The study's retrospective nature limits the results because of the risk of interpreter bias, although this was addressed in part by reviewing data in duplicate. We controlled for the potential for selection bias with our consecutive sampling model. CONCLUSIONS: Our study demonstrates a role for incisional negative pressure wound therapy in decreasing rates of perineal surgical site infection following abdominoperineal resection. Prospective randomized trials will be required to further investigate this intervention.
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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 | 0.000 | 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 | 0.000 | 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 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".