Ma Jen-Wen, Hu Sung-Yuan, Hsieh Ming-Shun, Lee Yi-Chen, Huang Shih-Che, Chen Kuan-Ju, Chang Yan-Zin, Tsai Yi-Chun
Department of Emergency Medicine, Taichung Veterans General Hospital, Taichung 407219, Taiwan.
Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung 402, Taiwan.
J Pers Med. 2023 Nov 16;13(11):1614. doi: 10.3390/jpm13111614.
The in-hospital mortality of cardiogenic shock (CS) remains high (28% to 45%). As a result, several studies developed prediction models to assess the mortality risk and provide guidance on treatment, including CardShock and IABP-SHOCK II scores, which performed modestly in external validation studies, reflecting the heterogeneity of the CS populations. Few articles established predictive scores of CS based on Asian people with a higher burden of comorbidities than Caucasians. We aimed to describe the clinical characteristics of a contemporary Asian population with CS, identify risk factors, and develop a predictive scoring model.
A retrospective observational study was conducted between 2014 and 2019 to collect the patients who presented with all-cause CS in the emergency department of a single medical center in Taiwan. We divided patients into subgroups of CS related to acute myocardial infarction (AMI-CS) or heart failure (HF-CS). The outcome was all-cause 30-day mortality. We built the prediction model based on the hazard ratio of significant variables, and the cutoff point of each predictor was determined using the Youden index. We also assessed the discrimination ability of the risk score using the area under a receiver operating characteristic curve.
We enrolled 225 patients with CS. One hundred and seven patients (47.6%) were due to AMI-CS, and ninety-eight patients among them received reperfusion therapy. Forty-nine patients (21.8%) eventually died within 30 days. Fifty-three patients (23.55%) presented with platelet counts < 155 × 10/μL, which were negatively associated with a 30-day mortality of CS in the restrictive cubic spline plot, even within the normal range of platelet counts. We identified four predictors: platelet counts < 200 × 10/μL (HR 2.574, 95% CI 1.379-4.805, = 0.003), left ventricular ejection fraction (LVEF) < 40% (HR 2.613, 95% CI 1.020-6.692, = 0.045), age > 71 years (HR 2.452, 95% CI 1.327-4.531, = 0.004), and lactate > 2.7 mmol/L (HR 1.967, 95% CI 1.069-3.620, = 0.030). The risk score ended with a maximum of 5 points and showed an AUC (95% CI) of 0.774 (0.705-0.843) for all patients, 0.781 (0.678-0.883), and 0.759 (0.662-0.855) for AMI-CS and HF-CS sub-groups, respectively, all < 0.001.
Based on four parameters, platelet counts, LVEF, age, and lactate (PEAL), this model showed a good predictive performance for all-cause mortality at 30 days in the all patients, AMI-CS, and HF-CS subgroups. The restrictive cubic spline plot showed a significantly negative correlation between initial platelet counts and 30-day mortality risk in the AMI-CS and HF-CS subgroups.
心源性休克(CS)的院内死亡率仍然很高(28%至45%)。因此,多项研究开发了预测模型来评估死亡风险并为治疗提供指导,包括CardShock和IABP-SHOCK II评分,这些模型在外部验证研究中的表现一般,反映了CS人群的异质性。很少有文章基于合并症负担高于白种人的亚洲人群建立CS的预测评分。我们旨在描述当代亚洲CS人群的临床特征,识别危险因素,并开发一种预测评分模型。
2014年至2019年间进行了一项回顾性观察研究,收集台湾一家单一医疗中心急诊科所有病因的CS患者。我们将患者分为与急性心肌梗死相关的CS(AMI-CS)或心力衰竭相关的CS(HF-CS)亚组。结局为全因30天死亡率。我们基于显著变量的风险比构建预测模型,并使用约登指数确定每个预测因子的截断点。我们还使用受试者工作特征曲线下面积评估风险评分的辨别能力。
我们纳入了225例CS患者。107例患者(47.6%)为AMI-CS,其中98例接受了再灌注治疗。49例患者(21.8%)最终在30天内死亡。53例患者(23.55%)血小板计数<155×10⁹/μL,在限制性立方样条图中,即使在血小板计数正常范围内,其与CS的30天死亡率呈负相关。我们确定了四个预测因子:血小板计数<200×10⁹/μL(HR 2.574,95%CI 1.379 - 4.805,P = 0.003)、左心室射血分数(LVEF)<40%(HR 2.613,95%CI 1.020 - 6.692,P = 0.045)、年龄>71岁(HR 2.452,95%CI 1.327 - 4.531,P = 0.004)和乳酸>2.7 mmol/L(HR 1.967,95%CI 1.069 - 3.620,P = 0.030)。风险评分最高为5分,所有患者的曲线下面积(95%CI)为0.774(0.705 - 0.843),AMI-CS和HF-CS亚组分别为0.781(0.678 - 0.883)和0.759(0.662 - 0.855),均<0.001。
基于血小板计数、LVEF、年龄和乳酸这四个参数(PEAL),该模型在所有患者、AMI-CS和HF-CS亚组中对30天全因死亡率显示出良好的预测性能。限制性立方样条图显示,AMI-CS和HF-CS亚组中初始血小板计数与30天死亡风险之间存在显著负相关。