The Effect of Inadequate Initial Empiric Antimicrobial Treatment on Mortality in Critically Ill Patients with Bloodstream Infections: A Multi-Centre Retrospective Cohort Study
Why this work is in the frame
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Bibliographic record
Abstract
Hospital mortality rates are elevated in critically ill patients with bloodstream infections. Given that mortality may be even higher if appropriate treatment is delayed, we sought to determine the effect of inadequate initial empiric treatment on mortality in these patients. A retrospective cohort study was conducted across 13 intensive care units in Canada. We defined inadequate initial empiric treatment as not receiving at least one dose of an antimicrobial to which the causative pathogen(s) was susceptible within one day of initial blood culture. We evaluated the association between inadequate initial treatment and hospital mortality using a random effects multivariable logistic regression model. Among 1,190 patients (1,097 had bacteremia and 93 had candidemia), 476 (40%) died and 266 (22%) received inadequate initial treatment. Candidemic patients more often had inadequate initial empiric therapy (64.5% versus 18.8%), as well as longer delays to final culture results (4 vs 3 days) and appropriate therapy (2 vs 0 days). After adjustment, there was no detectable association between inadequate initial treatment and mortality among bacteremic patients (Odds Ratio (OR): 1.02, 95% Confidence Interval (CI) 0.70-1.48); however, candidemic patients receiving inadequate treatment had nearly three times the odds of death (OR: 2.89, 95% CI: 1.05-7.99). Inadequate initial empiric antimicrobial treatment was not associated with increased mortality in bacteremic patients, but was an important risk factor in the subgroup of candidemic patients. Further research is warranted to improve early diagnostic and risk prediction methods in candidemic patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 it