ObjectivesPredictive algorithms to inform risk management decisions are needed for patients with COVID-19, although the traditional risk scores have not been adequately assessed in Asian patients. We aimed to evaluate the performance of a COVID-19-specific prediction model, the 4C (Coronavirus Clinical Characterisation Consortium) Mortality Score, along with other conventional critical care risk models in Japanese nationwide registry data.DesignRetrospective cohort study.Setting and participantsHospitalised patients with COVID-19 and cardiovascular disease or coronary risk factors from January to May 2020 in 49 hospitals in Japan.Main outcome measuresTwo different types of outcomes, in-hospital mortality and a composite outcome, defined as the need for invasive mechanical ventilation and mortality.ResultsThe risk scores for 693 patients were tested by predicting in-hospital mortality for all patients and composite endpoint among those not intubated at baseline (n=659). The number of events was 108 (15.6%) for mortality and 178 (27.0%) for composite endpoints. After missing values were multiply imputed, the performance of the 4C Mortality Score was assessed and compared with three prediction models that have shown good discriminatory ability (RISE UP score, A-DROP score and the Rapid Emergency Medicine Score (REMS)). The area under the receiver operating characteristic curve (AUC) for the 4C Mortality Score was 0.84 (95% CI 0.80 to 0.88) for in-hospital mortality and 0.78 (95% CI 0.74 to 0.81) for the composite endpoint. It showed greater discriminatory ability compared with other scores, except for the RISE UP score, for predicting in-hospital mortality (AUC: 0.82, 95% CI 0.78 to 0.86). Similarly, the 4C Mortality Score showed a positive net reclassification improvement index over the A-DROP and REMS for mortality and over all three scores for the composite endpoint. The 4C Mortality Score model showed good calibration, regardless of outcome.ConclusionsThe 4C Mortality Score performed well in an independent external COVID-19 cohort and may enable appropriate disposition of patients and allocation of medical resources.Trial registration number UMIN000040598.
as a remarkable and independent predictor of outcomes, which can add clinical value to existing prediction models of COVID-19. Given that the prediction of the clinical course in patients with COVID-19 is difficult due to their heterogeneity, the 4C mortality score, 6,7 which is another useful predictor independent from the pre-existing prediction model developed and validated specifically in patients with COVID-19, is warranted.AF is a common arrhythmia that increases the risk of morbidity and mortality in patients with CVD. 8,9 The incidence of new-onset atrial fibrillation (NOAF) in patients with COVID-19 is common, and is related to worse out-P re-existing cardiovascular diseases and risk factors (CVDRF), including atrial fibrillation (AF), are commonly observed and associated with higher mortality rates after infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative virus of coronavirus disease 2019 (COVID-19). 1,2 SARS-CoV-2 specifically impairs the cardiovascular system and causes myocardial injury, which is related to worse clinical outcomes during hospitalization, particularly in those with underlying cardiovascular disease (CVD). 3-5 These facts highlight the need to focus on underlying and new-onset CVDs during the clinical course of SARS-CoV-2 infection
the comorbidities of COVID-19 that lead to worse outcomes. 2,4,7 However, controversy remains regarding the associations between age, cardiovascular comorbidities, and outcomes in patients with COVID-19. 8-10 Furthermore, there have been few reports regarding the prognosis of COVID-19 infection from East Asian countries other than China, where the contribution of cardiovascular diseases and risk factors (CVDRF) is known to differ significantly from those in Western countries. 11 Thus, a better under-A s of October 31, 2020, the World Health Organization reported that the case fatality ratio of coronavirus disease 2019 (COVID-19) was approximately 2.6% in the overall infected population, 1 but COVID-19 highlighted the particular vulnerabilities of the aging population. 2-4 In addition, elderly patients are generally characterized by a higher incidence of cardiovascular risk factors, such as hypertension, diabetes, dyslipidemia, and a history of cardiovascular diseases, 5,6 which are some of
Background: Cardiovascular diseases and/or risk factors (CVDRF) have been reported as risk factors for severe coronavirus disease 2019 (COVID-19). Methods and Results:In total, we selected 693 patients with CVDRF from the CLAVIS-COVID database of 1,518 cases in Japan. The mean age was 68 years (35% females). Statin use was reported by 31% patients at admission. Statin users exhibited lower incidence of extracorporeal membrane oxygenation (ECMO) insertion (1.4% vs. 4.6%, odds ratio [OR]: 0.295, P=0.037) and septic shock (1.4% vs. 6.5%, OR: 0.205, P=0.004) despite having more comorbidities such as diabetes mellitus. Conclusions:This study suggests the potential benefits of statins use against COVID-19.
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