Daily Incision Cleansing with Alcohol Reduces the Rate of Surgical Site Infections: A Pilot Study
Bibliographic record
Abstract
Surgical site infections (SSIs) represent a significant source of preventable patient morbidity and hospital expense. Our objective was to assess the role of postoperative incisional alcohol cleansing in decreasing the rates of SSI as compared with standard care (control). Patients undergoing clean-contaminated abdominal operations at a single center were included. Prospectively collected data on control patients were compared with patients treated with daily postoperative alcohol-based surgical site cleansing (70% isopropyl alcohol) for the primary outcome of an SSI within the first 30 postoperative days. A total of 93 patients were included, 56 managed with standard care and 37 managed with the addition of daily alcohol cleansing. A significantly lower rate of SSI in the group managed with daily alcohol cleansing was observed (13% vs 32%, P = 0.04). This study suggests a role for adding daily incisional alcohol cleansing to further reduce the rate of SSIs.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".