Evaluation of Negative Pressure Dressings for Closed Surgical Incisions in Decreasing Surgical Site Infections After Emergency Laparotomy: A Randomized Controlled Study
Bibliographic record
Abstract
Objectives The aim of this study is to compare the effectiveness of negative pressure dressings (NPDs) versus conventional dressings for closed surgical incisions after emergency midline laparotomy, focusing on their impact on surgical site infection (SSI) rates, wound dehiscence, hospital stay duration, and cosmetic outcomes. Methods The randomized controlled study was conducted over 24 months, involving 80 patients aged 18-65 years who had peritonitis and underwent emergency midline laparotomies. Patients with diabetes mellitus, a BMI >35 kg/m², immunocompromised conditions, or those requiring re-exploration within 30 days of surgery were excluded. The participants were randomly assigned into two groups using a computer-generated randomization table: Group A, the case group, consisted of 40 patients who received NPDs, while Group B, the control group, included 40 patients who received conventional dressings. Data were recorded in Microsoft Excel (Microsoft Corporation, Redmond, WA, USA) and analyzed using IBM SPSS Statistics for Windows, Version 25.0 (Released 2017; IBM Corp., Armonk, NY, USA), with a p-value of <0.05 considered statistically significant. Results The overall occurrence of SSIs within the 30-day follow-up period was significantly lower in the NPD group compared to the conventional dressing group (30% vs. 70%, p < 0.05). The mean duration of hospital stay was 14.85 ± 10.43 days for the NPD group and 15.4 ± 9.75 days for the control group, with no statistically significant difference (p = 0.712). The mean Vancouver Scar Scale score was 5.3 ± 2.47 in the NPD group and 6.5 ± 2.14 in the control group, also showing no statistically significant difference (p = 0.11). Conclusions NPDs significantly reduced the incidence of SSIs compared to conventional dressings, but they did not have a significant impact on scar cosmesis or the duration of hospital stay.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".