Background: The value of procalcitonin (PCT) in the diagnosis of bacterial infections and for determining antibiotic usage among patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD) is currently unclear. Methods: We systematically reviewed the literature and selected studies that evaluated PCT as a biomarker for predicting bacterial infection and compared PCT-based protocols to determine its application in the initiation or discontinuation of antibiotics. Guidance for systematic reviews from Cochrane and the GRADE were followed to perform this study. Data were pooled and analyzed by using a random-effects or a fixed-effects model based on the heterogeneity. Results: The pooled sensitivity and specificity of PCT in diagnosing respiratory bacterial infections were 0.60 and 0.76, respectively, with the area under the summary receiver operating characteristic curve of 0.77. Subgroup analysis showed that the sensitivity and specificity of PCT for patients in ICU were 0.48 and 0.69, respectively. PCT-based protocols decreased antibiotic prescription (relative risk = 0.66, 95% CI: 0.62-0.71) and total antibiotic exposure (mean difference = -2.60, 95% CI: -4.48-0.72), without affecting clinical outcomes such as treatment failure, length of hospitalization and rates of re-exacerbation or overall mortality. Conclusions: PCT has a moderate ability to distinguish bacterial respiratory infection in patients with AECOPD. PCT-guided algorithm can reduce unnecessary administration of antibiotics without increasing adverse outcomes. However, for patients requiring admission in the ICU, PCT may have a poor diagnostic value, and the PCT-guided algorithm may not effectively and safely reduce the antibiotic exposure.
Background: The value of procalcitonin (PCT) in the diagnosis of bacterial infections and for determining antibiotic usage among patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD) is currently unclear. Methods: We systematically reviewed the literature and selected studies that evaluated PCT as a biomarker for predicting bacterial infection and compared PCT-based protocols to determine its application in the initiation or discontinuation of antibiotics. Guidance for systematic reviews from Cochrane and the GRADE were followed to perform this study. Data were pooled and analyzed by using a random-effects or a fixed-effects model based on the heterogeneity. Results: The pooled sensitivity and specificity of PCT in diagnosing respiratory bacterial infections were 0.60 and 0.76, respectively, with the area under the summary receiver operating characteristic curve of 0.77. Subgroup analysis showed that the sensitivity and specificity of PCT for patients in ICU were 0.48 and 0.69, respectively. PCT-based protocols decreased antibiotic prescription (relative risk = 0.66, 95% CI: 0.62-0.71) and total antibiotic exposure (mean difference = -2.60, 95% CI: -4.48-0.72), without affecting clinical outcomes such as treatment failure, length of hospitalization and rates of re-exacerbation or overall mortality. Conclusions: PCT has a moderate ability to distinguish bacterial respiratory infection in patients with AECOPD. PCT-guided algorithm can reduce unnecessary administration of antibiotics without increasing adverse outcomes. However, for patients requiring admission in the ICU, PCT may have a poor diagnostic value, and the PCT-guided algorithm may not effectively and safely reduce the antibiotic exposure.
Authors: Anna Maria Azzini; Romolo Marco Dorizzi; Piersandro Sette; Marta Vecchi; Ilaria Coledan; Elda Righi; Evelina Tacconelli Journal: Ann Transl Med Date: 2020-05