Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study.
Rong Hui Du,Li Rong Liang,Cheng Qing Yang,Wen Wang,Tan Ze Cao,Ming Li,Guang Yun Guo,Juan Du,Chun Lan Zheng,Qi Zhu,Ming Hu,Xu Yan Li,Peng Peng,Huan-Zhong Shi +13 more
TLDR
Age ≥65 years, pre-existing concurrent cardiovascular or cerebrovascular diseases, CD3+CD8+ T-cells ≤75 cells·μL−1 and cardiac troponin I ≥0.05 ng·mL−1 were four risk factors predicting high mortality of COVID-19 pneumonia patients.Abstract:
The aim of this study was to identify factors associated with the death of patients with COVID-19 pneumonia caused by the novel coronavirus SARS-CoV-2. All clinical and laboratory parameters were collected prospectively from a cohort of patients with COVID-19 pneumonia who were hospitalised to Wuhan Pulmonary Hospital (Wuhan City, Hubei Province, China) between 25 December 2019 and 7 February 2020. Univariate and multivariate logistic regression was performed to investigate the relationship between each variable and the risk of death of COVID-19 pneumonia patients. In total, 179 patients with COVID-19 pneumonia (97 male and 82 female) were included in the present prospective study, of whom 21 died. Univariate and multivariate logistic regression analysis revealed that age ≥65 years (OR 3.765, 95% CI 1.146‒17.394; p=0.023), pre-existing concurrent cardiovascular or cerebrovascular diseases (OR 2.464, 95% CI 0.755‒8.044; p=0.007), CD3+CD8+ T-cells ≤75 cells·μL−1 (OR 3.982, 95% CI 1.132‒14.006; p We identified four risk factors: age ≥65 years, pre-existing concurrent cardiovascular or cerebrovascular diseases, CD3+CD8+ T-cells ≤75 cells·μL−1 and cardiac troponin I ≥0.05 ng·mL−1. The latter two factors, especially, were predictors for mortality of COVID-19 pneumonia patients.read more
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COVID-19 vaccination for people with severe mental illness: why, what, and how?
TL;DR: In this article, the authors discuss the risk for worse COVID-19 outcomes in this vulnerable group, the effect of severe mental illnesses and psychotropic medications on vaccination response, the attitudes of people with severe mental illness towards vaccination, and, the potential barriers to, and possible solutions for, an efficient vaccination programme in this population.
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Anemia is associated with severe illness in COVID-19: A retrospective cohort study.
Zheying Tao,Jing Xu,Wei Chen,Zhitao Yang,Xiaoman Xu,Ling Liu,Ruwu Chen,Jingyuan Xie,Mingyu Liu,Jingyi Wu,Huiming Wang,Jialin Liu +11 more
TL;DR: Patients with anemia were more likely to have one or more comorbidities and severe COVID‐19 illness, and healthcare professionals should be more sensitive to the hemoglobin levels of CO VID‐19 patients on admission.
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Factors associated with the presence of headache in hospitalized COVID-19 patients and impact on prognosis: a retrospective cohort study.
Javier Trigo,David García-Azorín,Álvaro Planchuelo-Gómez,Enrique Martínez-Pías,Blanca Talavera,Isabel Hernández-Pérez,Gonzalo Valle-Peñacoba,Paula Simón-Campo,Mercedes de Lera,Alba Chavarría-Miranda,Cristina López-Sanz,María Gutiérrez-Sánchez,Elena Martínez-Velasco,María Pedraza,Álvaro Sierra,Beatriz Gómez-Vicente,Juan F. Arenillas,Juan F. Arenillas,Ángel L Guerrero +18 more
TL;DR: Headache is a frequent symptom in CO VID-19 patients and its presence is an independent predictor of lower risk of mortality in COVID-19 hospitalized patients.
Journal ArticleDOI
Elevated D-Dimer Levels Are Associated With Increased Risk of Mortality in Coronavirus Disease 2019: A Systematic Review and Meta-Analysis
Siddharth Shah,Kuldeep Shah,Siddharth B Patel,Foram S Patel,Mohammed Osman,Poonam Velagapudi,Mohit K. Turagam,Dhanunjaya Lakkireddy,Jalaj Garg +8 more
TL;DR: It is demonstrated that patients with COVID-19 infection presenting with elevated D-dimer levels have an increased risk of severe disease and mortality.
Journal ArticleDOI
Predicting mortality risk in patients with COVID-19 using machine learning to help medical decision-making
TL;DR: In the wake of COVID-19 disease, caused by the SARS-CoV-2 virus, a predictive model based on Artificial Intelligence (AI) and Machine Learning (ML) algorithms to determine the health risk and predict the mortality risk of patients with CoV-19 was developed in this paper.
References
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Nanshan Chen,Min Zhou,Xuan Dong,Jie-Ming Qu,Fengyun Gong,Yang Han,Yang Qiu,Jingli Wang,Ying Liu,Yuan Wei,Jia'an Xia,Ting Yu,Xinxin Zhang,Li Zhang +13 more
TL;DR: Characteristics of patients who died were in line with the MuLBSTA score, an early warning model for predicting mortality in viral pneumonia, and further investigation is needed to explore the applicability of the Mu LBSTA scores in predicting the risk of mortality in 2019-nCoV infection.
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