Sun Xuejun, Xie Naxin, Guo Mengling, Qiu Xuelian, Chen Hongwei, Liu Haibo, Li Hongmu
Department of Cardiovascular Surgery, Fujian Medical University Affiliated First Quanzhou Hospital, Quanzhou, China.
Department of Medical Record, Fujian Medical University Affiliated First Quanzhou Hospital, Quanzhou, China.
Cardiol Res Pract. 2021 May 12;2021:9947034. doi: 10.1155/2021/9947034. eCollection 2021.
This research aimed to establish a nomogram for predicting early death in viral myocarditis (VMC) patients.
A total of 362 consecutive VMC patients in Fujian Medical University Affiliated First Quanzhou Hospital between January 1, 2009, and December 31, 2019, were included. A least absolute shrinkage and selection operator (LASSO) regression model was used to detect the risk factors that most consistently and correctly predicted early death in VMC. The performance of the nomogram was assessed by calibration, discrimination, and clinical utility.
9 factors were screened by LASSO regression analysis for predicting the early death of VMC. Combined with the actual clinical situation, the heart failure (HF) (OR: 2.13, 95% CI: 2.76-5.95), electrocardiogram (ECG) (OR: 6.11, 95% CI: 1.05-8.66), pneumonia (OR: 3.62, 95% CI: 1.43-9.85), brain natriuretic peptide (BNP) (OR: 4.66, 95% CI: 3.07-24.06), and lactate dehydrogenase (LDH) (OR: 1.90, 95% CI: 0.19-9.39) were finally used to construct the nomogram. The nomogram's C-index was 0.908 in the training cohort and 0.924 in the validation cohort. And the area under the receiver operating characteristic curve of the nomogram was 0.91 in the training cohort and 0.924 in the validating cohort. Decision curve analysis (DCA) also showed that the nomogram was clinically useful.
This nomogram achieved an good prediction of the risk of early death in VMC patients.
本研究旨在建立一种预测病毒性心肌炎（VMC）患者早期死亡的列线图。
纳入2009年1月1日至2019年12月31日在福建医科大学附属泉州第一医院连续收治的362例VMC患者。采用最小绝对收缩和选择算子（LASSO）回归模型检测最能持续且正确预测VMC患者早期死亡的危险因素。通过校准、鉴别和临床实用性评估列线图的性能。
通过LASSO回归分析筛选出9个预测VMC早期死亡的因素。结合实际临床情况，最终采用心力衰竭（HF）（OR：2.13，95%CI：2.76 - 5.95）、心电图（ECG）（OR：6.11，95%CI：1.05 - 8.66）、肺炎（OR：3.62，95%CI：1.43 - 9.85）、脑钠肽（BNP）（OR：4.66，95%CI：3.07 - 24.06）和乳酸脱氢酶（LDH）（OR：1.90，95%CI：0.19 - 9.39）构建列线图。该列线图在训练队列中的C指数为0.908，在验证队列中的C指数为0.924。列线图在训练队列中的受试者工作特征曲线下面积为0.91，在验证队列中的受试者工作特征曲线下面积为0.924。决策曲线分析（DCA）也表明该列线图具有临床实用性。
该列线图对VMC患者早期死亡风险具有良好的预测能力。
