Management and outcomes in patients with Staphylococcus aureus bacteremia after implementation of mandatory infectious diseases consult: a before/after study
Bibliographic record
Abstract
BACKGROUND: Infectious disease (ID) consultations have been shown to increase adherence to guidelines and decrease mortality for patients with Staphylococcus aureus bacteremia (SAB). Here, we assessed the impact of a mandatory ID consultation policy for SAB. METHODS: We retrospectively reviewed all consecutive adult patients with SAB at two tertiary care teaching hospitals in Hamilton, ON, Canada. Mandatory ID consults for SAB were implemented on January 1(st) 2012. We compared SAB cases in 2011 (control group) with those in 2012 (intervention group). Outcomes included adherence to the Infectious Diseases Society of America guidelines and patient outcomes. RESULTS: We reviewed 128 SAB cases in 2011 and 124 in 2012. The majority of S. aureus were methicillin-susceptible (97/128, 75.8 % in 2011 and 100/124, 80.6 % in 2012). ID involvement increased significantly from 93/128 (72.7 %) in 2011, to 103/124 (83.1 %) in 2012 (odds ratio [OR] 1.9, 95 % confidence interval [CI] 1.1-3.3, p = 0.047). There was also a significant decrease in the median time to ID involvement from 2 days to 1 (p = 0.001). In patients who survived the minimum treatment course (greater than 13 days), there was a significant improvement in adherence to IDSA guidelines in 2012 (65/102, 63.7 % vs. 77/96, 80.2 %; OR 2.3, 95 % CI 1.2-4.4, p = 0.01). Mortality and SAB relapse rates were similar in both groups. CONCLUSIONS: Creating an automated ID consultation for SAB led to an increase in involvement of ID, a significant decrease in time to ID involvement, and better adherence to IDSA guidelines. The study was not sufficiently powered to detect significant changes in mortality and SAB relapse rates.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".