Umeh Chukwuemeka, Maguwudze Stella, Torbela Adrian, Saigal Shipra, Kaur Harpreet, Kazourra Shadi, Aseri Mahendra, Gupta Rakesh, Chaudhuri Sumanta, Gupta Rahul
Internal Medicine, Hemet Global Medical Center, Hemet, USA.
Data Engineering & Business Intelligence, Hemet Global Medical Center, Hemet, USA.
Cureus. 2021 Sep 20;13(9):e18137. doi: 10.7759/cureus.18137. eCollection 2021 Sep.
Introduction The majority of patients infected with coronavirus disease 2019 (COVID-19) recover from the illness after suffering mild to moderate symptoms, while approximately 20% progress to severe or critical disease, which may result in death. Understanding the predictors of severe disease and mortality in COVID-19 patients will help to risk stratify patients and improve clinical decision making. US data to inform this understanding are, however, scarce. We studied predictors of COVID-19 mortality in a cohort of 1,116 hospitalized patients in Southern California in the United States. Methods We conducted a retrospective cohort study of COVID-19 patients admitted at two hospitals in Southern California United States between March 2020 and March 2021. Bivariate and multivariate analyses of the relationship between mortality and other variables such as demographics, comorbidities, and laboratory values were performed, with a p-value of 0.05 considered as significant. Results The analysis involved 1,116 COVID-19 patients, of which 51.5% were males and 48.5% were females. Of the 1,116 patients, 81.6% were whites, 7.2% were blacks, and 11.2% were other races. After adjusting for co-variables, age (p<0.001), admission to intensive care unit (p< 0.001), use of remdesivir (p=0.018), C-reactive protein (CRP) levels (p<0.001), and lactate dehydrogenase (LDH) levels (p=0.039) were independently associated with mortality in our study. Gender, race, body mass index, presence of co-morbidities such as diabetes and hypertension, and use of steroid, statin, calcium channel blockers, angiotensin-converting enzyme inhibitors or angiotensin receptor blockers were not associated with mortality in the multivariate analysis. Conclusion In the cohort we studied, admission to intensive care unit was associated with decreased mortality while older age, use of remdesivir, and high levels of CRP and LDH were associated with increased mortality in COVID-19 patients.
大多数感染2019冠状病毒病（COVID-19）的患者在经历轻度至中度症状后康复，而约20%的患者会发展为重症或危重症疾病，这可能导致死亡。了解COVID-19患者重症疾病和死亡的预测因素将有助于对患者进行风险分层并改善临床决策。然而，美国用于增进这一认识的数据很少。我们在美国南加州的一组1116名住院患者中研究了COVID-19死亡率的预测因素。
我们对2020年3月至2021年3月期间在美国南加州两家医院收治的COVID-19患者进行了一项回顾性队列研究。对死亡率与其他变量（如人口统计学、合并症和实验室值）之间的关系进行了双变量和多变量分析，p值为0.05被视为具有统计学意义。
该分析涉及1116名COVID-19患者，其中51.5%为男性，48.5%为女性。在这1116名患者中，81.6%为白人，7.2%为黑人，11.2%为其他种族。在对协变量进行调整后，年龄（p<0.001）、入住重症监护病房（p<0.001）、使用瑞德西韦（p=0.018）、C反应蛋白（CRP）水平（p<0.001）和乳酸脱氢酶（LDH）水平（p=0.039）在我们的研究中与死亡率独立相关。在多变量分析中，性别、种族、体重指数、是否存在糖尿病和高血压等合并症以及使用类固醇、他汀类药物、钙通道阻滞剂、血管紧张素转换酶抑制剂或血管紧张素受体阻滞剂与死亡率无关。
在我们研究的队列中，入住重症监护病房与COVID-19患者死亡率降低相关，而年龄较大、使用瑞德西韦以及CRP和LDH水平较高与死亡率增加相关。
