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- Title
Predictive model for bacterial co-infection in patients hospitalized for COVID-19: a multicenter observational cohort study.
- Authors
Giannella, Maddalena; Rinaldi, Matteo; Tesini, Giulia; Gallo, Mena; Cipriani, Veronica; Vatamanu, Oana; Campoli, Caterina; Toschi, Alice; Ferraro, Giuseppe; Horna, Clara Solera; Bartoletti, Michele; Ambretti, Simone; Violante, Francesco; Viale, Pierluigi; Curti, Stefania
- Abstract
Objective: The aim of our study was to build a predictive model able to stratify the risk of bacterial co-infection at hospitalization in patients with COVID-19. Methods: Multicenter observational study of adult patients hospitalized from February to December 2020 with confirmed COVID-19 diagnosis. Endpoint was microbiologically documented bacterial co-infection diagnosed within 72 h from hospitalization. The cohort was randomly split into derivation and validation cohort. To investigate risk factors for co-infection univariable and multivariable logistic regression analyses were performed. Predictive risk score was obtained assigning a point value corresponding to β-coefficients to the variables in the multivariable model. ROC analysis in the validation cohort was used to estimate prediction accuracy. Results: Overall, 1733 patients were analyzed: 61.4% males, median age 69 years (IQR 57–80), median Charlson 3 (IQR 2–6). Co-infection was diagnosed in 110 (6.3%) patients. Empirical antibiotics were started in 64.2 and 59.5% of patients with and without co-infection (p = 0.35). At multivariable analysis in the derivation cohort: WBC ≥ 7.7/mm3, PCT ≥ 0.2 ng/mL, and Charlson index ≥ 5 were risk factors for bacterial co-infection. A point was assigned to each variable obtaining a predictive score ranging from 0 to 5. In the validation cohort, ROC analysis showed AUC of 0.83 (95%CI 0.75–0.90). The optimal cut-point was ≥2 with sensitivity 70.0%, specificity 75.9%, positive predictive value 16.0% and negative predictive value 97.5%. According to individual risk score, patients were classified at low (point 0), intermediate (point 1), and high risk (point ≥ 2). CURB-65 ≥ 2 was further proposed to identify patients at intermediate risk who would benefit from early antibiotic coverage. Conclusions: Our score may be useful in stratifying bacterial co-infection risk in COVID-19 hospitalized patients, optimizing diagnostic testing and antibiotic use.
- Subjects
BACTERIAL disease risk factors; ANTIBIOTICS; RESEARCH; STATISTICS; COVID-19; SCIENTIFIC observation; PREDICTIVE tests; MULTIVARIATE analysis; RISK assessment; MIXED infections; HOSPITAL care; DESCRIPTIVE statistics; PREDICTION models; LOGISTIC regression analysis; STATISTICAL correlation; RECEIVER operating characteristic curves; SENSITIVITY &; specificity (Statistics); LONGITUDINAL method; COMORBIDITY; DISEASE risk factors
- Publication
Infection, 2022, Vol 50, Issue 5, p1243
- ISSN
0300-8126
- Publication type
Article
- DOI
10.1007/s15010-022-01801-2