Development and validation of nomogram for unplanned ICU admission in patients with dilated cardiomyopathy.
Development and validation of nomogram for unplanned ICU admission in patients with dilated cardiomyopathy.
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DOI：
10.3389/fcvm.2023.1043274
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发表时间：
2023
影响因子：
3.6
通讯作者：
Ma, Yi-Tong
中科院分区：
文献类型：
--
作者：
Li, Xiao-Lei;Adi, Dilare;Zhao, Qian;Aizezi, Aibibanmu;Keremu, Munawaer;Li, Yan-Peng;Liu, Fen;Ma, Xiang;Li, Xiao-Mei;Azhati, Adila;Ma, Yi-Tong
扩张型心肌病（DCM）患者的主要院内不良事件是计划外入住重症监护室（ICU）。我们的目的是建立一个诺模图的DCM患者计划外ICU入院的个体化风险预测。对新疆医科大学第一附属医院2010年1月1日至2020年12月31日收治的2,214例DCM患者进行回顾性分析。患者以7：3的比例随机分为训练组和验证组。最小绝对收缩和选择算子和多变量逻辑回归分析用于诺模图模型开发。使用受试者工作特征曲线下面积、校准曲线和决策曲线分析（DCA）对模型进行评价。主要结局定义为计划外ICU入院。共有209例（9.44%）患者发生计划外ICU入院。我们最终列线图中的变量包括急诊入院、既往卒中史、纽约心脏协会分级、心率、中性粒细胞计数和N末端前B型利钠肽水平。在训练组中，列线图显示出良好的校准（Hosmer-Lemeshow χ2 = 14.40，P = 0.07）和良好的区分度，最佳校正C指数为0.76（95%置信区间：0.72-0.80）。DCA证实了诺模图模型的临床净受益，诺模图在验证组中保持了优异的性能。这是第一个通过简单收集临床信息预测DCM患者计划外ICU入院的风险预测模型。该模型可以帮助医生识别DCM住院患者计划外ICU入院的高风险个体。
Unplanned admission to the intensive care unit (ICU) is the major in-hospital adverse event for patients with dilated cardiomyopathy (DCM). We aimed to establish a nomogram of individualized risk prediction for unplanned ICU admission in DCM patients. A total of 2,214 patients diagnosed with DCM from the First Affiliated Hospital of Xinjiang Medical University from January 01, 2010, to December 31, 2020, were retrospectively analyzed. Patients were randomly divided into training and validation groups at a 7:3 ratio. The least absolute shrinkage and selection operator and multivariable logistic regression analysis were used for nomogram model development. The area under the receiver operating characteristic curve, calibration curves, and decision curve analysis (DCA) were used to evaluate the model. The primary outcome was defined as unplanned ICU admission. A total of 209 (9.44%) patients experienced unplanned ICU admission. The variables in our final nomogram included emergency admission, previous stroke, New York Heart Association Class, heart rate, neutrophil count, and levels of N-terminal pro b-type natriuretic peptide. In the training group, the nomogram showed good calibration (Hosmer–Lemeshow χ2 = 14.40, P = 0.07) and good discrimination, with an optimal-corrected C-index of 0.76 (95% confidence interval: 0.72–0.80). DCA confirmed the clinical net benefit of the nomogram model, and the nomogram maintained excellent performances in the validation group. This is the first risk prediction model for predicting unplanned ICU admission in patients with DCM by simply collecting clinical information. This model may assist physicians in identifying individuals at a high risk of unplanned ICU admission for DCM inpatients.
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