Duration of Antibiotic Therapy for Critically Ill Patients with Bloodstream Infections: A Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: The optimal duration of antibiotic treatment for bloodstream infections is unknown and understudied. METHODS: A retrospective cohort study of critically ill patients with bloodstream infections diagnosed in a tertiary care hospital between March 1, 2010 and March 31, 2011 was undertaken. The impact of patient, pathogen and infectious syndrome characteristics on selection of shorter (≤10 days) or longer (>10 days) treatment duration, and on the number of antibiotic-free days, was examined. The time profile of clinical response was evaluated over the first 14 days of treatment. Relapse, secondary infection and mortality rates were compared between those receiving shorter or longer treatment. RESULTS: Among 100 critically ill patients with bloodstream infection, the median duration of antibiotic treatment was 11 days, but was highly variable (interquartile range 4.5 to 17 days). Predictors of longer treatment (fewer antibiotic-free days) included foci with established requirements for prolonged treatment, underlying respiratory tract focus, and infection with Staphylococcus aureus or Pseudomonas species. Predictors of shorter treatment (more antibiotic-free days) included vascular catheter source and bacteremia with coagulase-negative staphylococci. Temperature improvements plateaued after the first week; white blood cell counts, multiple organ dysfunction scores and vasopressor dependence continued to decline into the second week. Among 72 patients who survived to 10 days, clinical outcomes were similar between those receiving shorter and longer treatment. CONCLUSION: Antibiotic treatment durations for patients with bloodstream infection are highly variable and often prolonged. A randomized trial is needed to determine the duration of treatment that will maximize cure while minimizing adverse consequences of antibiotics.
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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 | 0.000 | 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 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".