Eloisa Sofia Tanzarella, Joel Vargas, Marco Menghini, Stefania Postorino, Francesca Pozzana, Maria Sole Vallecoccia, Francesco Lorenzo De Matteis, Federico Franchi, Amato Infante, Luigi Larosa, Maria Antonietta Mazzei, Salvatore Lucio Cutuli, Domenico Luca Grieco, Alessandra Bisanti, Simone Carelli, Gianmarco Lombardi, Edoardo Piervincenzi, Gabriele Pintaudi, Tommaso Pirronti, Mario Tumbarello, Massimo Antonelli, Gennaro De Pascale

An Observational Study to Develop a Predictive Model for Bacterial Pneumonia Diagnosis in Severe COVID-19 Patients—C19-PNEUMOSCORE

  • General Medicine
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In COVID-19 patients, antibiotics overuse is still an issue. A predictive scoring model for the diagnosis of bacterial pneumonia at intensive care unit (ICU) admission would be a useful stewardship tool. We performed a multicenter observational study including 331 COVID-19 patients requiring invasive mechanical ventilation at ICU admission; 179 patients with bacterial pneumonia; and 152 displaying negative lower-respiratory samplings. A multivariable logistic regression model was built to identify predictors of pulmonary co-infections, and a composite risk score was developed using β-coefficients. We identified seven variables as predictors of bacterial pneumonia: vaccination status (OR 7.01; 95% CI, 1.73–28.39); chronic kidney disease (OR 3.16; 95% CI, 1.15–8.71); pre-ICU hospital length of stay ≥ 5 days (OR 1.94; 95% CI, 1.11–3.4); neutrophils ≥ 9.41 × 109/L (OR 1.96; 95% CI, 1.16–3.30); procalcitonin ≥ 0.2 ng/mL (OR 5.09; 95% CI, 2.93–8.84); C-reactive protein ≥ 107.6 mg/L (OR 1.99; 95% CI, 1.15–3.46); and Brixia chest X-ray score ≥ 9 (OR 2.03; 95% CI, 1.19–3.45). A predictive score (C19-PNEUMOSCORE), ranging from 0 to 9, was obtained by assigning one point to each variable, except from procalcitonin and vaccine status, which gained two points each. At a cut-off of ≥3, the model exhibited a sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 84.9%, 55.9%, 69.4%, 75.9%, and 71.6%, respectively. C19-PNEUMOSCORE may be an easy-to-use bedside composite tool for the early identification of severe COVID-19 patients with pulmonary bacterial co-infection at ICU admission. Its implementation may help clinicians to optimize antibiotics administration in this setting.

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