Risk Estimation for Infection in Patients With ST-Segment Elevation Myocardial Infarction Undergoing Percutaneous Coronary Intervention: Development and Validation of a Predictive Score

Frontiers in Cardiovascular Medicine

Chongyang Duan¹  Simin Liu²  Wei Chen³  Zhengrong Xu⁵  Yaowang Lin⁶  Litao Wang⁷  Pengyuan Chen⁸  Yuanhui Liu⁹  Hualin Fan⁹  Ling Xue⁹  Jiyan Chen⁹  Lihuan Zeng⁹  Yining Dai⁹  Ning Tan^1,10  Pengcheng He^1,10 

[1] 0Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China;Center for Global Cardiometabolic Health, Department of Epidemiology, Medicine, and Surgery, Brown University, Providence, RI, United States;Clinical College of Fujian Provincial Hospital, Fujian Provincial Hospital, Fujian Provincial Key Laboratory of Cardiovascular Disease, Fujian Provincial Center for Geriatrics, Fujian Medical University, Fujian Cardiovascular Institute, Fuzhou, China;Department of Cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China;Department of Cardiology, People’s Hospital of Baoan Shenzhen, Shenzhen, China;Department of Cardiology, Second Clinical Medical College of Jinan University, Shenzhen People’s Hospital, First Affiliated Hospital of South University of Science and Technology, Shenzhen, China;Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai, China;Department of Cardiology, The Second People’s Hospital of Nanhai District, Guangdong General Hospital’s Nanhai Hospital, Foshan, China;Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China;The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China;

关键词: risk score;    infection;    ST-elevation myocardial infarction;    percutaneous coronary intervention;    observational study;   

DOI  :  10.3389/fcvm.2022.845307

来源: DOAJ

【 摘 要 】

BackgroundInfection during hospitalization is a serious complication among patients who suffered from acute myocardial infarction (AMI) undergoing percutaneous coronary intervention (PCI); however, there are no suitable and accurate means to assess risk. This study aimed to develop and validate a simple scoring system to predict post-AMI infection in such patients.MethodsAll patients with ST-segment elevation myocardial infarction (STEMI) undergoing PCI consecutively enrolled from January 2010 to May 2016 were served as derivation cohort, and those from June 2016 to May 2018 as validation cohort, respectively. The primary endpoint was post-AMI infection during hospitalization, and all-cause death and major adverse cardiovascular events (MACE) were considered as secondary endpoints. The simplified risk model was established using logistic regression. The area under the receiver operating curve and calibration of predicted and observed infection risk were calculated.ResultsA 24-point risk score was developed, with infection risk ranging from 0.7 to 99.6% for patients with the lowest and highest score. Seven variables including age, Killip classification, insulin use, white blood cell count, serum albumin, diuretic use, and transfemoral approach were included. This model achieved the same high discrimination in the development and validation cohort (C-statistic:0.851) and revealed adequate calibration in both datasets. The incidences of post-AMI infection increased steadily across risk score groups in both development (1.3, 5.1, 26.3, and 69.1%; P < 0.001) and validation (1.8, 5.9, 27.2, and 79.2%; P < 0.001) cohort. Moreover, the risk score demonstrated good performance for infection, in-hospital all-cause death, and MACE among these patients, as well as in patients with the non-ST-elevation acute coronary syndrome.ConclusionThis present risk score established a simple bedside tool to estimate the risk of developing infection and other in-hospital outcomes in patients with STEMI undergoing PCI. Clinicians can use this risk score to evaluate the infection risk and subsequently make evidence-based decisions.

【 授权许可】

Unknown