Predicting bacteremia in patients attended for infections in an emergency department: the 5MPB-Toledo model
Objectives. To develop a simple risk score to predict bacteremia in patients in our hospital emergency department for infection. Methods. Retrospective observational cohort study of all blood cultures ordered in the emergency department for adults (aged 18 or older) from July 1, 2018, to March 31, 2...
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Veröffentlicht in: | Emergencias 2020-04, Vol.32 (2), p.81-89 |
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Zusammenfassung: | Objectives. To develop a simple risk score to predict bacteremia in patients in our hospital emergency department for infection.
Methods. Retrospective observational cohort study of all blood cultures ordered in the emergency department for adults (aged 18 or older) from July 1, 2018, to March 31, 2019. We gathered data on 38 independent variables (demographic, comorbidity, functional status, and laboratory findings) that might predict bacteremia. Univariate and multiple logistic regression analyses were applied to the data and a risk scale was developed.
Results. A total of 2181 blood samples were cultured. True cases of bacteremia were confirmed in 262 (12%). The remaining 1919 cultures (88%) were negative. No growth was observed in 1755 (80.5%) of the negative cultures, and 164 (7.5%) were judged to be contaminated. The 5MPB-Toledo model identified 5 predictors of bacteremia: temperature higher than 38.3 degrees C (1 point), a Charlson comorbidity index of 3 or more (1 point), respiratory frequency of at least 22 breaths/min (1 point), leukocyte count greater than 12 000/mm(3) (1 point), and procalcitonin concentration of 0.51 ng/mL or higher (4 points). Low risk for bacteremia was indicated by a score of 0 to 2 points, intermediate risk by 3 to 5 points, and high risk by 6 to 8 points. Bacteremia in these 3 risk groups was predicted for 1.1%, 10.5%, and 77%, respectively. The model's area under the receiver operating characteristic curve was 0.946 (95% CI, 0.922-0.969).
Conclusion. The 5MPB-Toledo score could be useful for predicting bacteremia in patients attended in hospital emergency departments for infection. |
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ISSN: | 1137-6821 2386-5857 |