Reducing surgical site infections in patients undergoing pancreatic resection: a quality improvement initiative
Bibliographic record
Abstract
BACKGROUND: Surgical site infections (SSIs) represent a significant source of morbidity during pancreaticoduodenectomy. The use of piperacillin-tazobactam (pip-tazo) has been shown to significantly reduce the incidence of SSI in this patient population. We thus elected to perform a quality improvement (QI) project to reduce superficial and deep SSI rates by ensuring all patients received pip-tazo as antibiotic prophylaxis. METHODS: We collected baseline retrospective data on a historical cohort of patients undergoing pancreaticoduodenectomy or total pancreatectomy from 1 January 2022 to 31 December 2022. We then launched our QI project on 1 January 2023, consisting of a multidisciplinary team creation and numerous outreach activities. The project had two Plan, Do, Study, Act (PDSA) cycles and ran until April 2024. The Standards for Quality Improvement Reporting Excellence guidelines were used to report results. RESULTS: Baseline cohort data included 64 patients, with 32% receiving pip-tazo and 39% developing an SSI. During phase one of our QI project (1 January 2023-31 August 2023), 54 patients underwent surgery, 90.7% received pip-tazo and 27.8% developed an SSI. Those who had undergone preoperative biliary stenting had a higher SSI rate (46.9% vs 4.4%). We thus added a second SSI reduction measure to patients with biliary stents: the ringed wound protector. During the second phase of our QI project (1 September 2023-1 April 2024), 51 patients underwent surgery, 98.0% received pip-tazo and 65.0% had a wound protector placed. SSI rates in this group were 9.8%. CONCLUSION: We describe a QI project whereby we increased the rates of correct antibiotic dosing in patients undergoing pancreatectomy to 98.0%. Although pip-tazo reduced SSI rates, the addition of a ringed wound protector in patients at high risk further reduced rates of SSI. We thus suggest the use of pip-tazo and ringed wound protectors as an effective strategy to reduce SSI rates in patients undergoing pancreatectomy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".