Duration of Antimicrobial Treatment for Bacteremia in Canadian Critically Ill Patients*
Bibliographic record
Abstract
OBJECTIVES: The optimum duration of antimicrobial treatment for patients with bacteremia is unknown. Our objectives were to determine duration of antimicrobial treatment provided to patients who have bacteremia in ICUs, to assess pathogen/patient factors related to treatment duration, and to assess the relationship between treatment duration and survival. DESIGN: Retrospective cohort study. SETTINGS: Fourteen ICUs across Canada. PATIENTS: Patients with bacteremia and were present in the ICU at the time culture reported positive. INTERVENTIONS: Duration of antimicrobial treatment for patients who had bacteremia in ICU. MEASUREMENTS AND MAIN RESULTS: Among 1,202 ICU patients with bacteremia, the median duration of treatment was 14 days, but with wide variability (interquartile range, 9-17.5). Most patient characteristics were not associated with treatment duration. Coagulase-negative staphylococci were the only pathogens associated with shorter treatment (odds ratio, 2.82; 95% CI, 1.51-5.26). The urinary tract was the only source of infection associated with a trend toward lower likelihood of shorter treatment (odds ratio, 0.67; 95% CI, 0.42-1.08); an unknown source of infection was associated with a greater likelihood of shorter treatment (odds ratio, 2.14; 95% CI, 1.17-3.91). The association of treatment duration and survival was unstable when analyzed based on timing of death. CONCLUSIONS: Critically ill patients who have bacteremia typically receive long courses of antimicrobials. Most patient/pathogen characteristics are not associated with treatment duration; survivor bias precludes a valid assessment of the association between treatment duration and survival. A definitive randomized controlled trial is needed to compare shorter versus longer antimicrobial treatment in patients who have bacteremia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.005 |
| 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 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".