Evaluation of Hospital and Patient Factors that Influence the effective Administration of Surgical Antimicrobial Prophylaxis
Bibliographic record
Abstract
OBJECTIVE: To analyze and model the patient and healthcare system factors that may interfere with the appropriate administration of surgical antimicrobial prophylaxis. DESIGN: Between 1994 and 1998, surgical-site surveillance data were collected prospectively for a cohort of eligible surgical patients. For all cases, and each individual procedure (cardiothoracic, colonic, gynecologic, orthopedic, or vascular), forward stepwise multiple logistic regression was applied to relate key hospital and patient factors to an effective first prophylactic dose (ie, appropriate administration time, dose, route, and drug). SETTING: A 450-bed, tertiary-care teaching hospital in Canada. PATIENTS: A total of 4,835 patients admitted for surgical procedures who required antimicrobial prophylaxis. RESULTS: Factors positive for an effective first prophylactic dose for all cases were when an order was written (OR, 19.7; CI95, 9.1-42.7; P < .001) and given in the operating room (OR, 13.9; CI95, 7.5-25.6; P < .001). Factors negative for an effective first prophylactic dose were beta-lactam allergy (OR, 0.49; CI95, 0.4-0.61; P < .001) and same-day surgery (OR, 0.57; CI95, 0.4-0.82; P < .001). CONCLUSIONS: With few exceptions, the four factors included in the procedure models showed that when a preoperative order was written or the antibiotic was given in the operating room, a patient was more likely to receive an effective first prophylactic dose. Conversely, when a patient had a beta-lactam allergy or the surgery was performed on the day the patient was admitted, the administration of an effective first prophylactic dose was less likely.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".