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LACE Index to Predict the High Risk of 30-Day Readmission in Patients With Acute Myocardial Infarction at a University Affiliated Hospital

Authors
 Vasuki Rajaguru  ;  Tae Hyun Kim  ;  Whiejong Han  ;  Jaeyong Shin  ;  Sang Gyu Lee 
Citation
 FRONTIERS IN CARDIOVASCULAR MEDICINE, Vol.9 : 925965, 2022-07 
Journal Title
FRONTIERS IN CARDIOVASCULAR MEDICINE
Issue Date
2022-07
Keywords
acute myocardial infarction ; hospital ; prediction ; quality improvement ; readmission ; risk assessment
Abstract
Background: 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).

Methods: 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.

Results: 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 p = 0.920, indicating that the model was well-calibrated to predict risk of the 30-day readmission.

Conclusion: 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.
Files in This Item:
T202203501.pdf Download
DOI
10.3389/fcvm.2022.925965
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Preventive Medicine (예방의학교실) > 1. Journal Papers
4. Graduate School of Public Health (보건대학원) > Graduate School of Public Health (보건대학원) > 1. Journal Papers
Yonsei Authors
Kim, Tae Hyun(김태현) ORCID logo https://orcid.org/0000-0003-1053-8958
Rajaguru, Vasuki(바수키) ORCID logo https://orcid.org/0000-0003-2519-2814
Shin, Jae Yong(신재용) ORCID logo https://orcid.org/0000-0002-2955-6382
Lee, Sang Gyu(이상규) ORCID logo https://orcid.org/0000-0003-4847-2421
Han, Whiejong(한휘종)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/189490
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