Department of Cardiology, First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Xinjiang Key Laboratory of Cardiovascular Disease, Clinical Medical Research Institute, First Affiliated Hospital of Xinjiang Medical University, Urumqi, 830011, China.
BMC Cardiovasc Disord. 2023 May 17;23(1):257. doi: 10.1186/s12872-023-03260-5.
Acute type B aortic dissection (ABAD) is a life-threatening cardiovascular disease. A practicable and effective prediction model to predict and evaluate the risk of in-hospital death for ABAD is required. The present study aimed to construct a prediction model to predict the risk of in-hospital death in ABAD patients.
A total of 715 patients with ABAD were recruited in the first affiliated hospital of Xinjiang medical university from April 2012 to May 2021. The information on the demographic and clinical characteristics of all subjects was collected. The logistic regression analysis, receiver operating characteristic (ROC) curve analysis, and nomogram were applied to screen the appropriate predictors and to establish a prediction model for the risk of in-hospital mortality in ABAD. The receiver operator characteristic curve and calibration plot were applied to validate the performance of the prediction model.
Of 53 (7.41%) subjects occurred in-hospital death in 715 ABAD patients. The variables including diastolic blood pressure (DBP), platelets, heart rate, neutrophil-lymphocyte ratio, D-dimer, C-reactive protein (CRP), white blood cell (WBC), hemoglobin, lactate dehydrogenase (LDH), procalcitonin, and left ventricular ejection fraction (LVEF) were shown a significant difference between the in-hospital death group and the in-hospital survival group (all P < 0.05). Furthermore, all these factors which existed differences, except CRP, were associated with in-hospital deaths in ABAD patients (all P < 0.05). Then, parameters containing LVEF, WBC, hemoglobin, LDH, and procalcitonin were identified as independent risk factors for in-hospital deaths in ABAD patients by adjusting compound variables (all P < 0.05). In addition, these independent factors were qualified as predictors to build a prediction model (AUC > 0.5, P < 0.05). The prediction model was shown a favorable discriminative ability (C index = 0.745) and demonstrated good consistency.
The novel prediction model combined with WBC, hemoglobin, LDH, procalcitonin, and LVEF, was a practicable and valuable tool to predict in-hospital deaths in ABAD patients.
急性 B 型主动脉夹层（ABAD）是一种危及生命的心血管疾病。需要建立一种实用且有效的预测模型，以预测和评估 ABAD 患者住院期间死亡的风险。本研究旨在建立一种预测 ABAD 患者住院期间死亡风险的预测模型。
共纳入新疆医科大学第一附属医院 2012 年 4 月至 2021 年 5 月期间收治的 715 例 ABAD 患者。收集所有患者的人口统计学和临床特征信息。应用逻辑回归分析、受试者工作特征（ROC）曲线分析和列线图筛选合适的预测因子，并建立 ABAD 患者住院期间死亡风险的预测模型。应用 ROC 曲线和校准图验证预测模型的性能。
715 例 ABAD 患者中，53 例（7.41%）发生院内死亡。在住院死亡组和住院存活组之间，舒张压（DBP）、血小板、心率、中性粒细胞与淋巴细胞比值、D-二聚体、C 反应蛋白（CRP）、白细胞（WBC）、血红蛋白、乳酸脱氢酶（LDH）、降钙素原和左心室射血分数（LVEF）等变量均存在显著差异（均 P<0.05）。此外，除 CRP 外，上述差异变量均与 ABAD 患者的院内死亡相关（均 P<0.05）。然后，通过调整复合变量，确定 LVEF、WBC、血红蛋白、LDH 和降钙素原等参数为 ABAD 患者住院期间死亡的独立危险因素（均 P<0.05）。此外，这些独立因素可作为预测因子纳入预测模型（AUC>0.5，P<0.05）。该预测模型具有良好的判别能力（C 指数=0.745），且一致性较好。
该新型预测模型结合 WBC、血红蛋白、LDH、降钙素原和 LVEF，可用于预测 ABAD 患者住院期间的死亡风险，是一种实用且有价值的工具。
