Negative Pressure Wound Therapy Use to Decrease Surgical Nosocomial Events in Colorectal Resections (NEPTUNE)
Bibliographic record
Abstract
OBJECTIVE: Determine if negative pressure wound therapy (NPWT) reduces surgical site infection (SSI) in primarily closed incision after open and laparoscopic-converted colorectal surgery. BACKGROUND: SSIs after colorectal surgery are a common cause of morbidity. The prophylactic effect of NPWT has not been established. We undertook this study to evaluate if, among patients undergoing open colorectal resection, NPWT, as compared with standard postoperative dressings, is associated with a reduction in the rate of postoperative SSI. METHODS: In a randomized, controlled trial, 300 patients undergoing elective open colorectal surgery were assigned to receive prophylactic NPWT or standard gauze dressing. The primary end-point was 30-day SSI, as assessed by wound care experts blinded to treatment arm. Secondary outcomes included length of stay. Statistical analysis was performed on an intention-to-treat basis. A priori subgroup analysis was planned for patients who received a stoma at the time of initial operation. RESULTS: The incidence of SSI at 30-days postoperatively was no different between experimental and control groups (32% vs 34% respectively, P = 0.68). Length of stay was also no different at a median of 7 days (IQR 5) for both groups. Among patients receiving a stoma, there was also no difference in SSI between the experimental and control groups (38% vs 33% respectively, P = 0.66). CONCLUSIONS: Prophylactic use of NPWT on primarily closed incisions after open colorectal surgery was not associated with a decrease in SSI rate when compared with standard gauze dressing. TRIAL REGISTRATION NUMBER: Clinicaltrials.gov (NCT02007018).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".