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Development and Validation of Risk Nomogram Model Predicting Coronary Microvascular Obstruction in Patients with ST-Segment Elevation Myocardial Infarction (STEMI) Undergoing Primary Percutaneous Catheterization

Yuyang Xiao, Xianghua Fu, Yanbo Wang, Yanqiang Wu, Wenlu Wang, Qian Zhang

(Department of Cardiology, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China (mainland))

Med Sci Monit 2019; 25:5864-5877

DOI: 10.12659/MSM.915960

BACKGROUND: Coronary microvascular functional and structural obstruction (CMVO) remains a major complication in patients with ST-segment elevation myocardial infarction (STEMI). This study was designed to develop and validate a nomogram model to predict CMVO risk during primary percutaneous catheterization procedure.
MATERIAL AND METHODS: Starting January 2014 to December 2016, a cohort of eligible candidates were enrolled and divided into a training or a validation database. Each database was divided into MO or NMO subgroups based on TIMI myocardial perfusion grade results after recanalization. Independent factors were identified by multivariate logistic regression, from which the nomogram was plotted. The echocardiography measurement of the left ventricular ejection fraction (LVEF) was arranged within 7 days after the procedure.
RESULTS: A nomogram was built for CMVO risk prediction for the first time. There were 446 participants in the training database with 319 cases in the NMO subgroup and 127 participants in the MO subgroup. The validation database included 99 participants with 25 cases in the NMO subgroup and 74 in the MO subgroup. The risk model was developed by 6 independently significant factors: age, symptom onset to balloon time, Killip classification, admission activated clotting time, neutrophil/lymphocyte ratio, and glucose value. Internal receiver operating characteristic displayed favorable performance with concordance index of 0.925, while external validation area under curve was 0.939. There were significant differences in LVEF values during hospitalization between the subgroups of each database (both P<0.001).
CONCLUSIONS: The nomogram model consisting of 6 factors could predict CMVO risk accurately for STEMI patients undergoing primary percutaneous catheterization.

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