Association Between Infectious Diseases Consultation and Mortality in Hospitalized Patients With Gram-negative Bloodstream Infection: A Retrospective Population-wide Cohort Study
Bibliographic record
Abstract
OBJECTIVES: Data supporting routine infectious diseases (ID) consultation in gram-negative bloodstream infection (GN-BSI) are limited. We evaluated the association between ID consultation and mortality in patients with GN-BSI in a retrospective population-wide cohort study in Ontario using linked health administrative databases. METHODS: Hospitalized adult patients with GN-BSI between April 2017 and December 2021 were included. The primary outcome was time to all-cause mortality censored at 30 days, analyzed using a mixed effects Cox proportional hazards model with hospital as a random effect. ID consultation 1-10 days after the first positive blood culture was treated as a time-varying exposure. RESULTS: Of 30 159 patients with GN-BSI across 53 hospitals, 11 013 (36.5%) received ID consultation. Median prevalence of ID consultation for patients with GN-BSI across hospitals was 35.0% with wide variability (range 2.7%-76.1%, interquartile range 19.6%-41.1%). In total, 1041 (9.5%) patients who received ID consultation died within 30 days, compared to 1797 (9.4%) patients without ID consultation. In the fully adjusted multivariable model, ID consultation was associated with mortality benefit (adjusted hazard ratio [HR] 0.82, 95% confidence interval [CI] .77-.88, P < .0001; translating to absolute risk reduction of -3.8% or number needed to treat [NNT] of 27). Exploratory subgroup analyses of the primary outcome showed that ID consultation could have greater benefit in patients with high-risk features (nosocomial infection, polymicrobial or non-Enterobacterales infection, antimicrobial resistance, or non-urinary tract source). CONCLUSIONS: Early ID consultation was associated with reduced mortality in patients with GN-BSI. If resources permit, routine ID consultation for this patient population should be considered to improve patient outcomes.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".