入住重症监护病房 (ICU) 的 Takotsubo 综合征 (TTS) 患者总是比心脏病科住院的患者面临更高的院内死亡风险。后者的预后经过大量研究分析。然而,尚无实用模型来预测 ICU 中 TTS 患者的院内死亡风险。本研究旨在建立一个预测入住 ICU 的 TTS 患者院内死亡的模型。我们回顾性地纳入 MIMIC-IV 数据库中患有 TTS 的 ICU 患者。列线图的结果是院内死亡。最小绝对收缩选择算子(LASSO)分析初步选择了预测变量。该模型是通过多变量逻辑回归分析开发的。校准、决策曲线分析 (DCA) 和受试者工作特征 (ROC) 分别测量列线图在准确性、临床实用性和辨别力方面的性能。最终,368 名 ICU 患有 TTS 的患者参与了这项研究。院内死亡率为13.04%。 LASSO 回归和多变量逻辑回归分析验证了与院内死亡率显着相关的危险因素。它们是钾、凝血酶原时间(PT)、年龄、心肌梗塞、白细胞计数(WBC)、血细胞比容、阴离子间隙和序贯器官衰竭评估(SOFA)评分。该列线图很好地区分了有院内死亡风险的患者。训练集中的曲线下面积 (AUC) 为 0.779 (95%CI: 0.732–0.826),测试集中的曲线下面积 (AUC) 为 0.775 (95%CI: 0.711–0.839)。校准图和 DCA 显示该列线图具有良好的临床效益。我们开发了列线图来预测 ICU 患有 TTS 患者的院内死亡概率。 该列线图能够区分院内死亡风险高的患者并具有临床实用性。
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Development and validation of a prognostic nomogram for Takotsubo syndrome patients in the intensive care units: a retrospective cohort study
Patients with Takotsubo syndrome (TTS) admitted to the intensive care unit (ICU) always confront a higher risk of in-hospital death than those hospitalized in the cardiology unit. The prognosis of the latter was analyzed by a large number of studies. However, there was no utility model to predict the risk of in-hospital death for patients with TTS in the ICU. This study aimed to establish a model predicting in-hospital death in patients with TTS admitted to ICU. We retrospectively included ICU patients with TTS from the MIMIC-IV database. The outcome of the nomogram was in-hospital death. Least Absolute Shrinkage Selection Operator (LASSO) analysis selected predictors preliminarily. The model was developed by multivariable logistic regression analysis. Calibration, decision curve analysis (DCA), and receiver operating characteristic (ROC) measured the performance of the nomogram on the accuracy, clinical utility, and discrimination, respectively. Eventually, 368 ICU patients with TTS were enrolled in this research. The in-hospital mortality was 13.04%. LASSO regression and multivariate logistic regression analysis verified risk factors significantly associated with in-hospital mortality. They were potassium, prothrombin time (PT), age, myocardial infarction, white cell count (WBC), hematocrit, anion gap, and sequential organ failure assessment (SOFA) score. This nomogram excellently discriminated against patients with a risk of in-hospital death. The area under curve (AUC) was 0.779 (95%CI: 0.732–0.826) in training set and 0.775 (95%CI: 0.711–0.839) in test set. The calibration plot and DCA showed good clinical benefits for this nomogram. We developed a nomogram that predicts the probability of in-hospital death for ICU patients with TTS. This nomogram was able to discriminate patients with a high risk of in-hospital death and performed clinical utility.