RESUMO
INTRODUCTION: Azithromycin is an effective treatment for various respiratory conditions but its effect on cough is poorly understood. We synthesised data from randomised controlled trials (RCTs) and noncomparative studies (NCT) examining its effect on objective and subjective cough. METHODS: After prospective registration on PROSPERO, we searched MEDLINE, EMBASE, and CENTRAL for both RCTs and NCT trials examining the effect azithromycin on cough in respiratory disease. RESULTS: We identified 1240 studies of which 6 (4 RCTs and 2 NCT studies) were included in the meta-analysis, with a total of 275 patients. Azithromycin was associated with significant improvement in Leicester Cough Questionnaire scores at follow-up when compared to baseline scores (SMD = 0.62 [95% CI 0.12 to 1.12], p = 0.01). However, when only RCTs were synthesised, no significant effect was observed (SMD = 0.12 [95% CI - 0.36 to 0.60], p = 0.62). There was no significant reduction in cough severity VAS score (SMD = - 0.39 [95% CI - 0.92 to 0.14], p = 0.15). There was no significant reduction in objective cough count (SMD = - 0.41 [95% CI - 1.04 to 0.32], p = 0.09). CONCLUSION: Azithromycin therapy improves cough-related quality of life in various chronic respiratory diseases; however, there was no significant effect on cough outcomes when only data from RCTs were synthesised. We believe that to accurately identify which patients whose cough would benefit from azithromycin a large-scale clinical trial of patients with a broad spectrum of respiratory diseases, with sufficiently severe cough, should be undertaken with subgroup analysis of individual disease areas.
RESUMO
There have been numerous reports of patients initially misdiagnosed in the 2009 H1N1 influenza and coronavirus disease 2019 (COVID-19) pandemics within the literature. A systematic review was undertaken to collate misdiagnoses during the H1N1 and COVID-19 pandemics and identify which cognitive biases may contribute to this. MEDLINE, Embase, Cochrane and MedRxiv databases were searched for misdiagnoses or cognitive biases resulting in misdiagnosis, occurring during the H1N1 or COVID-19 virus pandemics. Eligible studies were assessed for quality using JBI criteria; primary outcome was the final diagnosis. Sixty-nine studies involving 2551 participants were included. We identified 686 cases of misdiagnosis, categorized as viral respiratory infection, other respiratory infection, non-respiratory infection, and non-infective. Misdiagnoses are listed and relevant investigations are offered. No article described prospective assessment of decision making in the pandemic setting or debiasing diagnostic thinking. Further research is required to understand why misdiagnoses occur and harm arises and how clinicians can be assisted in their decision making in a pandemic context.
