Department of Dermatology, Seoul National University Hospital, Seoul, Republic of Korea.
Department of Anesthesiology and Pain Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Sci Rep. 2021 Mar 18;11(1):6375. doi: 10.1038/s41598-021-85813-2.
We aimed to investigate the impact of comorbidity burden on mortality in patients with coronavirus disease (COVID-19). We analyzed the COVID-19 data from the nationwide health insurance claims of South Korea. Data on demographic characteristics, comorbidities, and mortality records of patients with COVID-19 were extracted from the database. The odds ratios of mortality according to comorbidities in these patients with and without adjustment for age and sex were calculated. The predictive value of the original Charlson comorbidity index (CCI) and the age-adjusted CCI (ACCI) for mortality in these patients were investigated using the receiver operating characteristic (ROC) curve analysis. Among 7590 patients, 227 (3.0%) had died. After age and sex adjustment, hypertension, diabetes mellitus, congestive heart failure, dementia, chronic pulmonary disease, liver disease, renal disease, and cancer were significant risk factors for mortality. The ROC curve analysis showed that an ACCI threshold > 3.5 yielded the best cut-off point for predicting mortality (area under the ROC 0.92; 95% confidence interval 0.91-0.94). Our study revealed multiple risk factors for mortality in patients with COVID-19. The high predictive power of the ACCI for mortality in our results can support the importance of old age and comorbidities in the severity of COVID-19.
我们旨在探讨合并症负担对冠状病毒病 (COVID-19) 患者死亡率的影响。我们分析了来自韩国全国健康保险索赔的 COVID-19 数据。从数据库中提取了 COVID-19 患者的人口统计学特征、合并症和死亡率记录。计算了这些患者有无年龄和性别调整的合并症与死亡率之间的比值比。使用接收者操作特征 (ROC) 曲线分析，研究了原始 Charlson 合并症指数 (CCI) 和年龄调整的 CCI (ACCI) 对这些患者死亡率的预测价值。在 7590 名患者中，有 227 人 (3.0%) 死亡。在年龄和性别调整后，高血压、糖尿病、充血性心力衰竭、痴呆、慢性肺病、肝病、肾病和癌症是死亡的显著危险因素。ROC 曲线分析表明，ACCI 阈值 > 3.5 可预测死亡率的最佳截断点 (ROC 曲线下面积为 0.92；95%置信区间为 0.91-0.94)。我们的研究揭示了 COVID-19 患者死亡的多个危险因素。在我们的结果中，ACCI 对死亡率的高预测能力可以支持年龄和合并症在 COVID-19 严重程度中的重要性。
