Impact of hospital infections on patients outcomes undergoing cardiac surgery at Santa Casa de Misericórdia de Marília
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: This study aimed to determine the incidence of nosocomial infections, the risk factors and the impact of these infections on mortality among patients undergoing to cardiac surgery. METHODS: Retrospective cohort study of 2060 consecutive patients from 2006 to 2012 at the Santa Casa de Misericórdia de Marília. RESULTS: 351 nosocomial infections were diagnosed (17%), 227 non-surgical infections and 124 surgical wound infections. Major infections were mediastinitis (2.0%), urinary tract infection (2.8%), pneumonia (2.3%), and bloodstream infection (1.7%). The in-hospital mortality was 6.4%. Independent variables associated with non-surgical infections were age > 60 years (OR 1.59, 95% CI 1.09 to 2.31), ICU stay > 2 days (OR 5, 49, 95% CI 2.98 to 10, 09), mechanical ventilation > 2 days (OR11, 93, 95% CI 6.1 to 23.08), use of urinary catheter > 3 days (OR 4.85 95% CI 2.95 -7.99). Non-surgical nosocomial infections were more frequent in patients with surgical wound infection (32.3% versus 7.2%, OR 6.1, 95% CI 4.03 to 9.24). Independent variables associated with mortality were age greater than 60 years (OR 2.0; 95% CI 1.4 t o3.0), use of vasoactive drugs (OR 3.4, 95% CI 1.9 to 6, 0), insulin use (OR 1.8; 95% CI 1.2 to 2.8), surgical reintervention (OR 4.4; 95% CI 2.1 to 9.0) pneumonia (OR 4.3; 95% CI 2.1 to 8.9) and bloodstream infection (OR = 4.7, 95% CI 2.0 to 11.2). CONCLUSION: Non-surgical hospital infections are common in patients undergoing cardiac surgery; they increase the chance of surgical wound infection and mortality.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.009 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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