Publication | Open Access
Development and Validation of Risk Nomogram Model Predicting Coronary Microvascular Obstruction in Patients with ST-Segment Elevation Myocardial Infarction (STEMI) Undergoing Primary Percutaneous Catheterization
21
Citations
26
References
2019
Year
Cmvo RiskCoronary Artery DiseaseAcute Myocardial InfarctionPublic HealthAtherosclerosisCardiologyCardiac ImagingCardiothoracic SurgeryMyocardial InfarctionCardiovascular ImagingPercutaneous Coronary InterventionCardiac CareCmvo Risk PredictionEpidemiologyStructural ObstructionCardiovascular DiseasePatient SafetyMedicineEmergency Medicine
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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