Chen Tien-Yu, Tseng Chien-Hao, Wu Po-Jui, Chung Wen-Jung, Lee Chien-Ho, Wu Chia-Chen, Cheng Cheng-I
Division of Cardiology, Department of Internal Medicine, Kaohsiung Chang Gung Memorial Hospital, Kaohsiung, Taiwan.
Division of Cardiothoracic and Vascular Surgery, Department of Surgery, Chang Gung Memorial Hospital Kaohsiung Branch, Kaohsiung, Taiwan.
Front Cardiovasc Med. 2022 Feb 24;9:825181. doi: 10.3389/fcvm.2022.825181. eCollection 2022.
Use of statistical models for assessing the clinical risk of readmission to medical and surgical intensive care units is well established. However, models for predicting risk of coronary care unit (CCU) readmission are rarely reported. Therefore, this study investigated the characteristics and outcomes of patients readmitted to CCU to identify risk factors for CCU readmission and to establish a scoring system for identifying patients at high risk for CCU readmission.
Medical data were collected for 27,841 patients with a history of readmission to the CCU of a single multi-center healthcare provider in Taiwan during 2001-2019. Characteristics and outcomes were compared between a readmission group and a non-readmission group. Data were segmented at a 9:1 ratio for model building and validation.
The number of patients with a CCU readmission history after transfer to a standard care ward was 1,790 (6.4%). The eleven factors that had the strongest associations with CCU readmission were used to develop and validate a CCU readmission risk scoring and prediction model. When the model was used to predict CCU readmission, the receiver-operating curve characteristic was 0.7038 for risk score model group and 0.7181 for the validation group. A CCU readmission risk score was assigned to each patient. The patients were then stratified by risk score into low risk (0-12), moderate risk (13-31) and high risk (32-40) cohorts check scores, which showed that CCU readmission risk significantly differed among the three groups.
This study developed a model for estimating CCU readmission risk. By using the proposed model, clinicians can improve CCU patient outcomes and medical care quality.
使用统计模型评估内科和外科重症监护病房再入院的临床风险已得到广泛认可。然而,预测冠心病监护病房(CCU)再入院风险的模型却鲜有报道。因此,本研究调查了CCU再入院患者的特征和结局,以确定CCU再入院的危险因素,并建立一个评分系统来识别CCU再入院高危患者。
收集了2001年至2019年期间台湾一家多中心医疗服务机构中27841例有CCU再入院史患者的医疗数据。比较了再入院组和非再入院组的特征和结局。数据按9:1的比例进行分割,用于模型构建和验证。
转至标准护理病房后有CCU再入院史的患者有1790例(6.4%)。与CCU再入院关联最强的11个因素被用于开发和验证CCU再入院风险评分及预测模型。当该模型用于预测CCU再入院时,风险评分模型组的受试者工作特征曲线下面积为0.7038,验证组为0.7181。为每位患者分配了一个CCU再入院风险评分。然后根据风险评分将患者分为低风险(0 - 12)、中度风险(13 - 31)和高风险(32 - 40)队列,检查评分结果显示三组之间CCU再入院风险存在显著差异。
本研究开发了一种估计CCU再入院风险的模型。通过使用所提出的模型,临床医生可以改善CCU患者的结局和医疗质量。