Incidence and Risk Factors for and the Effect of a Program To Reduce the Incidence of Surgical Site Infection after Cardiac Surgery
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Surgical site infection (SSI) after cardiac surgery (CS) is a serious complication that increases hospital length of stay (LOS), has a substantial financial impact, and increases mortality. The study described here was done to evaluate the effect of a program to reduce SSI after CS. METHODS: In January 2007, a multi-disciplinary CS infection-prevention team developed guidelines and implemented bundled tactics for reducing SSI. Data for all patients who underwent CS from 2006-2008 were used to determine whether there was: 1) A difference in the incidence of SSI in white patients and those belonging to minority groups; 2) a reduction in SSI after intervention; and 3) a statistically significant difference in the incidence of SSI in the third quarter of each year as compared with the other quarters of the year. RESULTS: Of 3,418 patients who underwent CS; 1,125 (32.9%) were members of minority groups and 2,293 (67.1%) were white. Eighty (2.3%) patients developed SSI. There was no significant difference in the incidence of SSI in non-Hispanic white patients and all others (2.1% vs. 2.8%, p=0. 42). The incidence of SSI decreased significantly from 2006 (3.0%) to 2007 (2.5%) and 2008 (1.4%), (p=0.03). Surgical site infection occurred more often in the third quarter of each of the years of the study than in other quarters of each year (3.3 vs. 2.0%, p=0.038). CONCLUSIONS: Implementation of a program to reduce SSI after CS was associated with a lower incidence of SSI across all racial and ethnic groups and over time, but was not associated with a lower incidence of SSI in the third quarter of each year than in the other quarters.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it