Litcius/Paper detail

Clinical Features of Fatalities in Patients With COVID-19

Ya-Jun Sun, Yi-Jin Feng, Jing Chen, Bo Li, Zhong‐Cheng Luo, Pei-Xi Wang

2020Disaster Medicine and Public Health Preparedness28 citationsDOIOpen Access PDF

Abstract

OBJECTIVES: The novel coronavirus disease 2019 (COVID-19) pandemic has spread to over 213 countries and territories. We sought to describe the clinical features of fatalities in patients with severe COVID-19. METHODS: We conducted an Internet-based retrospective cohort study through retrieving the clinical information of 100 COVID-19 deaths from nonduplicating incidental reports in Chinese provincial and other governmental websites between January 23 and March 10, 2020. RESULTS: Approximately 6 of 10 COVID-19 deaths were males (64.0%). The average age was 70.7 ± 13.5 y, and 84% of patients were elderly (over age 60 y). The mean duration from admission to diagnosis was 2.2 ± 3.8 d (median: 1 d). The mean duration from diagnosis to death was 9.9 ± 7.0 d (median: 9 d). Approximately 3 of 4 cases (76.0%) were complicated by 1 or more chronic diseases, including hypertension (41.0%), diabetes (29.0%) and coronary heart disease (27.0%), respiratory disorders (23.0%), and cerebrovascular disease (12.0%). Fever (46.0%), cough (33.0%), and shortness of breath (9.0%) were the most common first symptoms. Multiple organ failure (67.9%), circulatory failure (20.2%), and respiratory failure (11.9%) are the top 3 direct causes of death. CONCLUSIONS: COVID-19 deaths are mainly elderly and patients with chronic diseases especially cardiovascular disorders and diabetes. Multiple organ failure is the most common direct cause of death.

Topics & Concepts

Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PandemicVirologyBetacoronavirusMedical emergencyMEDLINECoronavirus InfectionsMedicineBiologyOutbreakPathologyDiseaseInfectious disease (medical specialty)BiochemistryCOVID-19 Clinical Research StudiesCOVID-19 and healthcare impactsData-Driven Disease Surveillance