Construction of visual prediction model for no reflow phenomenon in patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention / 中华急诊医学杂志

ABSTRACT

Objective:To build a simple, rapid and accurate visual prediction model for identifying the ST-segment elevation myocardial infarction (STEMI) patients with high risk of no reflow during the primary percutaneous coronary intervention (PPCI).Methods:A retrospective study of STEMI patients treated by PPCI in China-Japan Friendship Hospital from January 2018 to June 2019 was performed. The clinical data including sex, age, comorbidities, personal history, Killip classification and laboratory examinations were collected. Whether the patients had no reflow during the PPCI were retrospective observed. Multivariable logistic regression analysis was used to identify risk factors. A nomogram was developed to predict no reflow risk among STEMI patients. C-index and Hosmer-Lemeshow goodness-of-fit test were used to verify the differentiation, consistency and clinical applicability of the model. Internal verification of the model was used by Bootstrap validation.Results:Of the included 280 patients, the prevalence of no flow rate was 30.7%. Killip class Ⅲ or Ⅳ ( OR=3.537, 95% CI 1.665-7.514, P=0.002), mean platelet volume≥9 fL ( OR=4.003, 95% CI 1.091-14.689, P=0.037), Glucose ≥7.8 mmol/L ( OR=2.315, 95% CI 1.318-4.066, P=0.003) and time from symptoms to hospital ( OR=5.594, 95% CI 2.041-15.328, P=0.002) were the independent risk factors of no flow (all P<0.05). The AUC of ROC curve in the prediction model was 0.731 (95% CI 0.668-0.795). The calibration curves were close to the standard curve. Conclusions:The visual prediction model constructed in this study can early identify STEMI patients with high risk of no reflow, and may be helpful for physicians to provide prospective pre-treatment before the occurrence of no reflow during PPCI.