Epidemiology and clinical relevance of persistent bacteraemia in patients with Gram-negative bloodstream infection: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVES: The risk factors and outcomes associated with persistent bacteraemia in Gram-negative bloodstream infection (GN-BSI) are not well described. We conducted a follow-on analysis of a retrospective population-wide cohort to characterize persistent bacteraemia in patients with GN-BSI. METHODS: We included all hospitalized patients >18 years old with GN-BSI between April 2017 and December 2021 in Ontario who received follow-up blood culture (FUBC) 2-5 days after the index positive blood culture. Persistent bacteraemia was defined as having a positive FUBC with the same Gram-negative organism as the index blood culture. We identified variables independently associated with persistent bacteraemia in a multivariable logistic regression model. We evaluated whether persistent bacteraemia was associated with increased odds of 30- and 90-day all-cause mortality using multivariable logistic regression models adjusted for potential confounders. RESULTS: In this study, 8807 patients were included; 600 (6.8%) had persistent bacteraemia. Having a permanent catheter, antimicrobial resistance, nosocomial infection, ICU admission, respiratory or skin and soft tissue source of infection, and infection by a non-fermenter or non-Enterobacterales/anaerobic organism were associated with increased odds of having persistent bacteraemia. The 30-day mortality was 17.2% versus 9.6% in those with and without persistent bacteraemia (aOR 1.65, 95% CI 1.29-2.11), while 90-day mortality was 25.5% versus 16.9%, respectively (aOR 1.53, 95% CI 1.24-1.89). Prevalence and odds of developing persistent bacteraemia varied widely depending on causative organism. CONCLUSIONS: Persistent bacteraemia is uncommon in GN-BSI but is associated with poorer outcomes. A validated risk stratification tool may be useful to identify patients with persistent bacteraemia.
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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 | 0.001 | 0.000 |
| 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".