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

Abstract

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/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.

A nomogramic model based on clinical and laboratory parameters at admission for predicting the survival of COVID-19 patients

“…The nomogram, as a visual form of predictive models, has been used in the diagnosis, treatment and prognosis of various diseases [7][8][9]39]. It is visual and intuitive, and does not need to substitute the numbers into the equation calculation.…”

“…A nomogram is known to be a commonly used visual tool that integrates clinical data and laboratory variables for predicting the outcome of a disease. It was invented in the 19th century and has been widely used as a visualized, intuitive and appreciable tool in clinical practice [7][8][9]. The present study aimed to develop a nomogram model to predict the survival of COVID-19 patients based on their baseline clinical and laboratory data at admission.…”

A nomogramic model based on clinical and laboratory parameters at admission for predicting the survival of COVID-19 patients

“…The nomogram, as a visual form of predictive models, has been used in the diagnosis, treatment and prognosis of various diseases [29][30][31][32]. It is visual and intuitive, and does not need to substitute the numbers into the equation calculation.…”

A Retrospective Analysis of the Merit of Iris-pupil Area Ratio as a Predictor of Risk of Myocardial Infarction

“…[3][4][5] Although several biochemical, physiological and lifestyle risk factors are know, the utility of these risk factors in predicting immediate episodes of myocardial infarction is limited. 2,[4][5][6][7][8][9][10][11][12] This is perhaps due to the limitations in our understanding of the causative factors, which trigger myocardial infarction. While microvascular constriction is reported to be a major culprit, the feasibility to measure this parameter in a dynamic scale is technically limited.…”