August 7, 2019Medical Science MonitorOpen 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

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Why the study?

Coronary microvascular obstruction remains a major complication in STEMI patients, creating a need for a model to predict risk during primary percutaneous catheterization.

Can a risk nomogram model accurately predict coronary microvascular obstruction in STEMI patients undergoing primary percutaneous catheterization?

Structured PICO

Can a risk nomogram model accurately predict coronary microvascular obstruction in STEMI patients undergoing primary percutaneous catheterization?

Population

545 patients with ST-segment elevation myocardial infarction (STEMI) undergoing primary percutaneous catheterization (training database n=446, validation database n=99).

Intervention

Development and validation of a 6-factor risk nomogram model (age, symptom onset to balloon time, Killip classification, admission activated clotting time, neutrophil/lymphocyte ratio, and glucose value)

Outcome

Coronary microvascular obstruction (CMVO) based on TIMI myocardial perfusion grade results after recanalizationsurrogate

A novel 6-factor nomogram model demonstrates high accuracy in predicting the risk of coronary microvascular obstruction in STEMI patients undergoing primary PCI, which may aid in early risk stratification.

Implication

May support CMVO risk stratification by nomogram in STEMI; leaves open prospective validation before clinical adoption.

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 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.