Abstract
BackgroundInappropriate antibiotics use in lower respiratory tract infections (LRTI) is a major contributor to resistance. We aimed to design an algorithm based on clinical signs and host biomarkers to identify bacterial community-acquired pneumonia (CAP) among patients with LRTI.MethodsParticipants with LRTI were selected in a prospective cohort of febrile (≥ 38 °C) adults presenting to outpatient clinics in Dar es Salaam. Participants underwent chest X-ray, multiplex PCR for respiratory pathogens, and measurements of 13 biomarkers. We evaluated the predictive accuracy of clinical signs and biomarkers using logistic regression and classification and regression tree analysis.ResultsOf 110 patients with LRTI, 17 had bacterial CAP. Procalcitonin (PCT), interleukin-6 (IL-6) and soluble triggering receptor expressed by myeloid cells-1 (sTREM-1) showed an excellent predictive accuracy to identify bacterial CAP (AUROC 0.88, 95%CI 0.78–0.98; 0.84, 0.72–0.99; 0.83, 0.74–0.92, respectively). Combining respiratory rate with PCT or IL-6 significantly improved the model compared to respiratory rate alone (p = 0.006, p = 0.033, respectively). An algorithm with respiratory rate (≥ 32/min) and PCT (≥ 0.25 μg/L) had 94% sensitivity and 82% specificity.ConclusionsPCT, IL-6 and sTREM-1 had an excellent predictive accuracy in differentiating bacterial CAP from other LRTIs. An algorithm combining respiratory rate and PCT displayed even better performance in this sub-Sahara African setting.
Highlights
Inappropriate antibiotics use in lower respiratory tract infections (LRTI) is a major contributor to resist‐ ance
Among 519 patients prospectively enrolled in the fever aetiology cohort, 110 patients with a clinical LRTI and no exclusion criteria were included in this study (Fig. 1): 17 in group 1, 8 in group 2, 7 in group 3 (CAP of unknown origin) and 78 in group 4
Additional file 1: Tables S1 and S2 shows additional analyses supporting the accuracy of our bacterial communityacquired pneumonia (CAP) definition
Summary
Inappropriate antibiotics use in lower respiratory tract infections (LRTI) is a major contributor to resist‐ ance. We aimed to design an algorithm based on clinical signs and host biomarkers to identify bacterial communityacquired pneumonia (CAP) among patients with LRTI. Most antibiotics are prescribed in outpatient clinics and lower respiratory tract infections (LRTI) account for the majority of unnecessary prescriptions [3, 4]. Community-acquired pneumonia (CAP), usually of bacterial origin, requires antibiotic treatment according to guidelines while other LRTIs such as bronchitis are Hogendoorn et al BMC Infectious Diseases (2022) 22:39 generally self-resolving [5]. The presence of a new infiltrate on chest X-ray remains the gold standard to decide on antibiotic prescription among patients with LRTIs, even though it has a limited performance and cannot differentiate viral from bacterial aetiologies [6]. The proportion of patients with viral CAP is even higher during outbreaks, such as the ongoing SARSCoV-2 pandemic, highlighting the need for easy-toperform diagnostic tools to support clinicians in patient management and allow rational antibiotic use
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