Rajaguru Vasuki, Kim Tae Hyun, Han Whiejong, Shin Jaeyong, Lee Sang Gyu
Department of Healthcare Management, Graduate School of Public Health, Yonsei University, Seoul, South Korea.
Department of Global Health Security, Graduate School of Public Health, Yonsei University, Seoul, South Korea.
Front Cardiovasc Med. 2022 Jul 11;9:925965. doi: 10.3389/fcvm.2022.925965. eCollection 2022.
The LACE index (length of stay, acuity of admission, comorbidity index, and emergency room visit in the past 6 months) has been used to predict the risk of 30-day readmission after hospital discharge in both medical and surgical patients. This study aimed to utilize the LACE index to predict the risk of 30-day readmission in hospitalized patients with acute myocardial infraction (AMI).
This was a retrospective study. Data were extracted from the hospital's electronic medical records of patients admitted with AMI between 2015 and 2019. LACE index was built on admission patient demographic data, and clinical and laboratory findings during the index of admission. The multivariate logistic regression was performed to determine the association and the risk prediction ability of the LACE index, and 30-day readmission were analyzed by receiver operator characteristic curves with C-statistic.
Of the 3,607 patients included in the study, 5.7% (205) were readmitted within 30 days of discharge from the hospital. The adjusted odds ratio based on logistic regression of all baseline variables showed a statistically significant association with the LACE score and revealed an increased risk of readmission within 30 days of hospital discharge. However, patients with high LACE scores (≥10) had a significantly higher rate of emergency revisits within 30 days from the index discharge than those with low LACE scores. Despite this, analysis of the receiver operating characteristic curve indicated that the LACE index had favorable discrimination ability C-statistic 0.78 (95%CI; 0.75-0.81). The Hosmer-Lemeshow goodness- of-fit test P value was , indicating that the model was well-calibrated to predict risk of the 30-day readmission.
The LACE index demonstrated the good discrimination power to predict the risk of 30-day readmissions for hospitalized patients with AMI. These results can help clinicians to predict the risk of 30-day readmission at the early stage of hospitalization and pay attention during the care of high-risk patients. Future work is to be focused on additional factors to predict the risk of 30-day readmissions; they should be considered to improve the model performance of the LACE index with other acute conditions by using administrative data.
LACE指数（住院时间、入院急症程度、合并症指数以及过去6个月内的急诊室就诊情况）已被用于预测内科和外科患者出院后30天再入院的风险。本研究旨在利用LACE指数预测急性心肌梗死（AMI）住院患者30天再入院的风险。
这是一项回顾性研究。数据从2015年至2019年因AMI入院患者的医院电子病历中提取。LACE指数基于入院时患者的人口统计学数据以及入院期间的临床和实验室检查结果构建。进行多因素逻辑回归以确定LACE指数的相关性和风险预测能力，并通过C统计量的受试者工作特征曲线分析30天再入院情况。
在纳入研究的3607例患者中，5.7%（205例）在出院后30天内再次入院。基于所有基线变量的逻辑回归调整后的比值比显示与LACE评分存在统计学显著相关性，并揭示出院后30天内再入院风险增加。然而，LACE评分高（≥10）的患者在出院后30天内的急诊复诊率显著高于LACE评分低的患者。尽管如此，受试者工作特征曲线分析表明LACE指数具有良好的区分能力，C统计量为0.78（95%CI；0.75 - 0.81）。Hosmer-Lemeshow拟合优度检验P值为 ，表明该模型在预测30天再入院风险方面校准良好。
LACE指数在预测AMI住院患者30天再入院风险方面显示出良好的区分能力。这些结果有助于临床医生在住院早期预测30天再入院风险，并在高危患者护理期间予以关注。未来的工作将集中于预测30天再入院风险的其他因素；应考虑通过使用行政数据来改善LACE指数在其他急性疾病中的模型性能。
