Early Improvement of Acute Respiratory Distress Syndrome in Patients With COVID-19 in the Intensive Care Unit: Retrospective Analysis.

BACKGROUND: Since the start of the COVID-19 pandemic, there have been over 2 million deaths globally. Acute respiratory distress syndrome (ARDS) may be the main cause of death. OBJECTIVE: This study aimed to describe the clinical features, outcomes, and ARDS characteristics of patients with COVID-19 admitted to the intensive care unit (ICU) in Chongqing, China. METHODS: The epidemiology of COVID-19 from January 21, 2020, to March 15, 2020, in Chongqing, China, was analyzed retrospectively, and 75 ICU patients from two hospitals were included in this study. On day 1, 56 patients with ARDS were selected for subgroup analysis, and a modified Poisson regression was performed to identify predictors for the early improvement of ARDS (eiARDS). RESULTS: Chongqing reported a 5.3% case fatality rate for the 75 ICU patients. The median age of these patients was 57 (IQR 25-75) years, and no bias was present in the sex ratio. A total of 93% (n=70) of patients developed ARDS during ICU stay, and more than half had moderate ARDS. However, most patients (n=41, 55%) underwent high-flow nasal cannula oxygen therapy, but not mechanical ventilation. Nearly one-third of patients with ARDS improved (arterial blood oxygen partial pressure/oxygen concentration >300 mm Hg) in 1 week, which was defined as eiARDS. Patients with eiARDS had a higher survival rate and a shorter length of ICU stay than those without eiARDS. Age (<55 years) was the only variable independently associated with eiARDS, with a risk ratio of 2.67 (95% CI 1.17-6.08). CONCLUSIONS: A new subphenotype of ARDS-eiARDS-in patients with COVID-19 was identified. As clinical outcomes differ, the stratified management of patients based on eiARDS or age is highly recommended.

Construction of a competency evaluation index system for front-line nurses during the outbreak of major infectious diseases: A Delphi study.

INTRODUCTION: As the frequency of infectious diseases rises, it's more important than ever to pay attention to the competency level of front-line nurses as the primary force in front-line rescue, which has an impact on the quality of anti-epidemic response. This paper aims to construct the competency evaluation index system for front-line nurses during the outbreak of major infectious diseases. MATERIALS AND METHODS: This study combined literature review, critical incident technique interviews, and semi-structured in-depth interviews, as well as two rounds of Delphi expert correspondence, to construct a competence evaluation index system for front-line nurses during the outbreak of major infectious diseases. The study used purposive sampling to select 26 experts from 11 provinces and cities across China to conduct two rounds of Delphi expert consultation, and the indicators were selected based on the mean importance score > 3.5 and the coefficient of variation < 0.25, and the weights of the indicators were calculated by the Analytic Hierarchy Process. The effective recovery rates of the two rounds of correspondence questionnaires were 93.1% and 96%. RESULTS: The effective recovery rates of the two rounds of correspondence questionnaires were 93.1% and 96%, the authority coefficients of experts were 0.96 and 0.98, the Kendall's coordination coefficients of the first, second, and third level indexes were 0.281, 0.132, and 0.285 (P < 0.001), 0.259, 0.158, and 0.415 (P < 0.001). The final index system includes 4 primary indicators (Knowledge System of Infectious Diseases, Nursing Skills for Infectious Diseases, Related Professional Abilities for Infectious Diseases, and Comprehensive Quality), 10 secondary indicators, and 64 tertiary indicators. CONCLUSION: The competency evaluation index system of front-line nurses during the outbreak of major infectious diseases is scientific, reasonable, and practical, which can provide a scientific basis for nursing managers to accurately understand, describe, analyze, and evaluate the competence level of nursing staff and scientifically implement the allocation of human resources in the future, as well as serve as a content framework for subsequent training programs.