ABSTRACT
Background: Extracorporeal membrane oxygenation (ECMO) is a rapidly evolving therapy for acute lung and/or heart failure. However, information on the application of ECMO in severe coronavirus disease 2019 (COVID-19) is limited, such as the initiation time, especially in the ECMO instrument shortages period and regions, not all the listed patients could be treated with ECMO in time. This study aims to investigate and clear the timing of ECMO initiation related to the prognosis of severe COVID-19 patients. And emphasize the initiation time of ECOM application no more than 24 hours, when the ECMO completion trigger is tripped.Methods: In this retrospective, multi-center cohort study, we enrolled all ECMO patients with confirmed COVID-19 at three hospitals between Dec 29, 2019 and Apr 5, 2020. Demographic data, clinical presentation, laboratory profile, clinical course, treatments, complications and outcomes were collected. The primary outcomes were analyzed by ECMO weaning rate and 60-day mortality after ECMO.Results: A total of 31 patients were included in the analysis, 60-day mortality rate after ECMO was 71% and ECMO weaning rate was 26%. Due to ECMO instrument shortages, patients were divided into delayed ECMO groups (3 [IQR, 2-5] days) and early ECMO groups (0.5 [IQR, 0-1] days) based on the initiation time of ECMO. There were 14 patients in the early treatment group and 17 patients in the delayed group. Early initiation of ECMO was associated with decreased 60-day mortality after ECMO (50% vs. 88%, P=0.044) and increased ECMO weaning rate (50% vs. 6%, P=0.011).Conclusions: In the ECMO supported COVID-19 patients, delayed initiation of ECMO is a risk factor and associated with a poorer prognosis for these patients.Trial Registration: Chinese Clinical Trial Registry identifier: ChiCTR2000030947.Funding Statement: Not applicable.Declaration of Interests: The authors declare that they have no competing interests.Ethics Approval Statement: The study was approved by Jinyintan Hospital ethics board.
Subject(s)
COVID-19 , Heart FailureABSTRACT
Background: COVID-19 pandemic has developed rapidly and the ability to stratify the most vulnerable patients is vital. However, routinely used severity scoring systems are often low on diagnosis, even in non-survivors. Therefore, clinical prediction models for mortality are urgently required. Methods: We developed and internally validated a multivariable logistic regression model to predict inpatient mortality in COVID-19 positive patients using data collected retrospectively from Tongji Hospital, Wuhan (299 patients). External validation was conducted using a retrospective cohort from Jinyintan Hospital, Wuhan (145 patients). Nine variables commonly measured in these acute settings were considered for model development, including age, biomarkers and comorbidities. Backwards stepwise selection and bootstrap resampling were used for model development and internal validation. We assessed discrimination via the C statistic, and calibration using calibration-in-the-large, calibration slopes and plots. Findings: The final model included age, lymphocyte count, lactate dehydrogenase and SpO2 as independent predictors of mortality. Discrimination of the model was excellent in both internal (c=0.89) and external (c=0.98) validation. Internal calibration was excellent (calibration slope=1). External validation showed some over-prediction of risk in low-risk individuals and under-prediction of risk in high-risk individuals prior to recalibration. Recalibration of the intercept and slope led to excellent performance of the model in independent data. Interpretation: COVID-19 is a new disease and behaves differently from common critical illnesses. This study provides a new prediction model to identify patients with lethal COVID-19. Its practical reliance on commonly available parameters should improve usage of limited healthcare resources and patient survival rate.