AIM To explore the influencing factors for poor prognosis of acute myocarditis patients during hospitalization and to construct a predictive model.
METHODS The clinical data of 178 patients with acute myocarditis diagnosed and treated in our hospital from December 2009 to December 2019 were retrospectively analyzed and based on the outcome during hospitalization, they were divided into major adverse cardiac events (MACE) group (n=23) non-MACE group (n=155). General data, laboratory test indexes, echocardiogram, electrocardiogram indexes and treatment status were compared between the two groups. Multivariate logistic regression analysis was used to evaluate the risk factors of MACE during the hospitalization and a prediction model was constructed based on multivariate logistic regression analysis. ROC curve was used to verify the value of the model.
RESULTS Univariate analysis showed that age, female ratio, severe myocarditis ratio, respiratory rate, white blood cells, neutrophils, serum creatinine (SCr), fasting blood glucose, N-terminal B-type natriuretic peptide, Troponin I, creatine kinase MB (CK-MB), creatine kinase, lactate dehydrogenase, alanine aminotransferase, C-reactive protein, LVEF <40%, QRS interval> 120 ms, and the ratios of IABP, ECMO, CRRT, ventilator assist, β-blocker and positive inotropic/boosting drugs in MACE group were higher than those in non-MACE group, and systolic blood pressure in MACE group at admission was lower than that in non-MACE group (P<0.05). Multivariate logistic regression analysis showed that severe myocarditis (OR=2.89, 95%CI:1.55-6.36, P<0.05), female (OR=2.55, 95%CI:1.73-5.28, P=0.010), LVEF <40% (OR=2.38, 95%CI:1.17-3.53, P<0.05), QRS interval> 120 ms (OR=3.23, 95%CI:1.86-9.21, P<0.05), CK-MB>23.56 u/L (OR=2.78, 95% CI: 1.35-5.76, P< 0.05) and SCr>135.85 μmol/L (OR=1.49, 95% CI: 1.16-2.83, P<0.05) were the risk factors of MACE in acute myocarditis patients during hospitalization. Based on multivariate logistic regression analysis results, a regression equation was conducted fit it as a new variable Predict. ROC curve analysis showed that Predict predicted the occurrence of MACE in acute myocarditis patients during hospitalization was 0.830 (95%CI:0.771-0.888, P<0.01), sensitivity 78 %, the specificity 76% and the critical value 0.562.
CONCLUSION There are many risk factors for MACE in acute myocarditis patients, which are related to the patient’s gender, disease types, degrees of myocardial injury, reduced cardiac functions, electrocardiogram changes and renal injury. The prediction model constructed according to risk factors has a high predictive value for the short-term prognosis of acute myocarditis.
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