Predicting pathogen-positive blood culture episodes at two hours using electronic health record data

Most blood cultures obtained early in hospitalization do not yield a pathogen. We evaluated prediction 2 h after the first blood-culture record using MIMIC-IV. Adults with an initial routine culture record within 24 h of hospital presentation were eligible if alive and still receiving care at prediction. The cohort included 145,914 encounters, 99.3% eventually admitted, and 6,404 pathogen-positive episodes (4.39%). Comparisons at 2, 4 and 6 h supported the earliest tested prediction time because later gains were small and uncertain. The primary XGBoost model was evaluated in 11,523 test encounters; 242 episodes were positive (2.10%). AUROC was 0.819 (95% CI 0.792–0.844), average precision 0.124 (0.096–0.167), and Brier score 0.0201. The top 5% of predicted risk contained 81 positives among 577 encounters, giving 14.0% positivity and 6.68-fold enrichment. Laboratory values, particularly lymphocyte percentage, contributed most to prediction. Secondary analyses assessed the added value of previous culture results. Mean predicted risk was 3.78%, compared with 2.10% observed. This 2-h model was able to concentrate pathogen-positive episodes in higher-risk groups, but calibration and transportability require further validation before clinical use.

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Publication Details

Journal
Scientific Reports
Published
2026-10-15
DOI
https://doi.org/10.1038/s41598-026-75707-6
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00

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article

Predicting pathogen-positive blood culture episodes at two hours using electronic health record data

Radu C. Grovu, Sean F. Monaghan, Hala Soomro, Michael Rossi et al.
Scientific Reports
Machine Learning in Healthcare
article

Predicting pathogen-positive blood culture episodes at two hours using electronic health record data

Radu C. Grovu, Sean F. Monaghan, Hala Soomro, Michael Rossi, Nathan Gelinas
article en

Abstract

Most blood cultures obtained early in hospitalization do not yield a pathogen. We evaluated prediction 2 h after the first blood-culture record using MIMIC-IV. Adults with an initial routine culture record within 24 h of hospital presentation were eligible if alive and still receiving care at prediction. The cohort included 145,914 encounters, 99.3% eventually admitted, and 6,404 pathogen-positive episodes (4.39%). Comparisons at 2, 4 and 6 h supported the earliest tested prediction time because later gains were small and uncertain. The primary XGBoost model was evaluated in 11,523 test encounters; 242 episodes were positive (2.10%). AUROC was 0.819 (95% CI 0.792–0.844), average precision 0.124 (0.096–0.167), and Brier score 0.0201. The top 5% of predicted risk contained 81 positives among 577 encounters, giving 14.0% positivity and 6.68-fold enrichment. Laboratory values, particularly lymphocyte percentage, contributed most to prediction. Secondary analyses assessed the added value of previous culture results. Mean predicted risk was 3.78%, compared with 2.10% observed. This 2-h model was able to concentrate pathogen-positive episodes in higher-risk groups, but calibration and transportability require further validation before clinical use.

Scientific Reports
Providence Health Care (CA), Brown University (US), Rhode Island Hospital (US)
Combating Antibiotic-Resistant Bacteria Biopharmaceutical Accelerator, National Institutes of Health
Good health and well-being
Openalex Percentile: Top 13%
Machine Learning in Healthcare
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