Characteristics and risk factors for COVID-19 diagnosis and adverse outcomes in Mexico: an analysis of 89,756 laboratory–confirmed COVID-19 cases

Abstract

AbstractBackgroundThere is insufficient information about risk factors for COVID-19 diagnosis and adverse outcomes from low and middle-income countries (LMICs).ObjectivesWe estimated the association between patients’ characteristics and COVID-19 diagnosis, hospitalization and adverse outcome in Mexico.MethodsThis retrospective case series used a publicly available nation-level dataset released on May 31, 2020 by the Mexican Ministry of Health, with patients classified as suspected cases of viral respiratory disease. Patients with COVID-19 were laboratory-confirmed. Their profile was stratified by COVID-19 diagnosis or not. Differences among COVID-19 patients based on two separate clinical endpoints, hospitalization and adverse outcome, were examined. Multivariate logistic regressions examined the associations between patient characteristics and hospitalization and adverse outcome.ResultsOverall, 236,439 patients were included, with 89,756 (38.0%) being diagnosed with COVID-19. COVID-19 patients were disproportionately older, males and with increased prevalence of one or more comorbidities, particularly diabetes, obesity, and hypertension. Age, male gender, diabetes, obesity and having one or more comorbidities were independently associated with laboratory-confirmed COVID-19. Current smokers were 23% less likely to be diagnosed with COVID-19 compared to non-smokers. Of all COVID-19 patients, 34.8% were hospitalized and 13.0% experienced an adverse outcome. Male gender, older age, having one or more comorbidities, and chronic renal disease, diabetes, obesity, COPD, immunosuppression and hypertension were associated with hospitalization and adverse outcome. Current smoking was not associated with adverse outcome.ConclusionThis largest ever case series of COVID-19 patients identified risk factors for COVID-19 diagnosis, hospitalization and adverse outcome. The findings could provide insight for the priorities the need to be set, especially by LMICs, to tackle the pandemic.