BACKGROUND: Many factors are associated with no-reflow (NRF) phenomenon in ST-segment elevation myocardial infarction (STEMI), including plasma glucose, age, and pre-percutaneous coronary intervention (PCI) thrombus score. Initial clinical assessment would benefit from accurate NRF prediction. This study aimed to develop a simple scoring system to predict the risk of NRF in patients undergoing primary PCI with STEMI. METHODS: Baseline clinical and procedural variables were used for risk score development (the training dataset, n = 912) and validation (the test dataset, n = 864). Independent predictors of NRF from the multivariable model were assigned integer weights based on their coefficients and incorporated into a risk score. The discriminant ability of the score was tested by receiver operating characteristic analysis using the test dataset. RESULTS: The final model included 7 significant variables, which were age, pain-to-PCI time, neutrophil count, admission plasma glucose level, pre-PCI thrombus score, collateral circulation, and Killip class. All these variables were then used to build a risk score in terms of the prediction of NRF. Receiver operating characteristic analysis demonstrated good risk prediction with a c statistic of 0.800 (95% confidence interval: 0.772-0.826) in the test dataset. CONCLUSIONS: In patients with STEMI treated by primary PCI, incidence of NRF phenomenon may be predicted with an acceptable accuracy based on a 7-item simplified risk score.
BACKGROUND: Many factors are associated with no-reflow (NRF) phenomenon in ST-segment elevation myocardial infarction (STEMI), including plasma glucose, age, and pre-percutaneous coronary intervention (PCI) thrombus score. Initial clinical assessment would benefit from accurate NRF prediction. This study aimed to develop a simple scoring system to predict the risk of NRF in patients undergoing primary PCI with STEMI. METHODS: Baseline clinical and procedural variables were used for risk score development (the training dataset, n = 912) and validation (the test dataset, n = 864). Independent predictors of NRF from the multivariable model were assigned integer weights based on their coefficients and incorporated into a risk score. The discriminant ability of the score was tested by receiver operating characteristic analysis using the test dataset. RESULTS: The final model included 7 significant variables, which were age, pain-to-PCI time, neutrophil count, admission plasma glucose level, pre-PCI thrombus score, collateral circulation, and Killip class. All these variables were then used to build a risk score in terms of the prediction of NRF. Receiver operating characteristic analysis demonstrated good risk prediction with a c statistic of 0.800 (95% confidence interval: 0.772-0.826) in the test dataset. CONCLUSIONS: In patients with STEMI treated by primary PCI, incidence of NRF phenomenon may be predicted with an acceptable accuracy based on a 7-item simplified risk score.
Authors: Jennifer Ann Rossington; Eirini Sol; Konstantina Masoura; Konstantinos Aznaouridis; Raj Chelliah; Michael Cunnington; Benjamin Davison; Joseph John; Richard Oliver; Angela Hoye Journal: Open Heart Date: 2020-07