Publication date: Sep 18, 2023

Knowing the probability that patients have a bloodstream infection (BSI) could influence the ordering of blood cultures and interpretation of their preliminary results. Many previous BSI probability models have limited applicability and accuracy. This study used currently recommended modeling techniques and a large sample to derive and validate the Ottawa BSI Model. At a tertiary care teaching hospital, we retrieved a random sample of 4180 adults having blood cultures in our emergency department or during the initial 48 h of the encounter. Variable selection was based on clinical experience and a systematic review of previous model performance. Model performance was measured in a temporal external validation group of 4680 patients. A total of 327 derivation patients had a BSI (8. 0%). BSI risk increased with increased number of culture sets (2 sets: adjusted odds ratio [aOR] 1. 52 [1. 10-2. 11]; 3 sets: 1. 99 [0. 86-4. 58]); with indwelling catheter (aOR 2. 07 [1. 34-3. 20); with increasing temperature, heart rate, and neutrophil-lymphocyte ratio; and with decreasing systolic blood pressure, platelet count, urea-creatinine ratio, and estimated glomerular filtration rate. In the temporal external validation group, model discrimination was good (c-statistic 0. 71 [0. 69-0. 74]) and calibration was very good (integrated calibration index .016 [. 010-. 024]). Exclusion of validation patients with acute SARS-CoV-2 infection improved discrimination slightly (c-statistic 0. 73 [0. 69-0. 76]). The Ottawa BSI Model uses commonly available data to return an expected BSI probability for acutely ill patients. However, it cannot exclude BSI and its complexity requires computational assistance to use.

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