Closed incision negative pressure wound therapy following pancreaticoduodenectomy for prevention of surgical site infections in high-risk patients
Bibliographic record
Abstract
BACKGROUND: Surgical site infection (SSI) is one of the most common sources of morbidity after pancreaticoduodenectomy. Surgical site infections are associated with readmissions, prolonged length of stay, delayed initiation of adjuvant chemotherapy and negative effects on quality of life. Incisional vacuum-assisted closure (iVAC) devices applied on closed incisions may reduce SSI rates. The objective of this retrospective review is to evaluate the impact of iVAC on SSI rate after pancreaticoduodenectomy. METHODS: A cohort of patients undergoing pancreaticoduodenectomy at a single institution who had at least 1 risk factor for SSI and who received an iVAC were compared with a historical cohort of high-risk patients who received conventional dressings after pancreaticoduodenectomy. The primary outcome was incidence of SSI within 30 days, abstracted from chart review. Secondary outcomes were 30-day readmission, 90-day mortality, rate of postoperative pancreatic fistula and rate of delayed gastric emptying. RESULTS: In total, 175 patients were included, of whom 61 received an iVAC. The incidence of SSI was 13% (8 of 61 patients) and 16% (18 of 114 patients) in the iVAC and conventional dressing groups, respectively (odds ratio 0.81, 95% confidence interval 0.33-1.98). Preoperative biliary drainage was the most frequent SSI risk factor. Binary logistic regression using SSI as the outcome demonstrated no significant association with iVAC use when adjusted for SSI risk factors. There were no differences in rates of postoperative pancreatic fistula, delayed gastric emptying or 90-day mortality. CONCLUSION: This report describes the outcomes of the integration of iVAC devices into routine clinical practice at a high-volume institution. Application of this device after pancreaticoduodenectomy for patients at elevated risk of SSI was not associated with a reduction in the rate of SSIs.
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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 | 0.000 | 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) | 0.001 | 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".