A Risk Prediction Model for In-hospital Mortality in Patients with Suspected Myocarditis

Abstract

Background: Myocarditis is an inflammatory disease of the myocardium that may lead to cardiac death in some patients. However, little is known about the predictors of in-hospital mortality in patients with suspected myocarditis. Thus, the aim of this study was to identify the independent risk factors for in-hospital mortality in patients with suspected myocarditis by establishing a risk prediction model. Methods: A retrospective study was performed to analyze the clinical medical records of 403 consecutive patients with suspected myocarditis who were admitted to Ningbo First Hospital between January 2003 and December 2013. A total of 238 males (59%) and 165 females (41%) were enrolled in this study. We divided the above patients into two subgroups (survival and nonsurvival), according to their clinical in-hospital outcomes. To maximize the effectiveness of the prediction model, we first identified the potential risk factors for in-hospital mortality among patients with suspected myocarditis, based on data pertaining to previously established risk factors and basic patient characteristics. We subsequently established a regression model for predicting in-hospital mortality using univariate and multivariate logistic regression analyses. Finally, we identified the independent risk factors for in-hospital mortality using our risk prediction model. Results: The following prediction model for in-hospital mortality in patients with suspected myocarditis, including creatinine clearance rate (Ccr), age, ventricular tachycardia (VT), New York Heart Association (NYHA) classification, gender and cardiac troponin T (cTnT), was established in the study: P = ea/(1 + ea) (where e is the exponential function, P is the probability of in-hospital death, and a = −7.34 + 2.99 × [Ccr <60 ml/min = 1, Ccr ≥60 ml/min = 0] + 2.01 × [age ≥50 years = 1, age <50 years = 0] + 1.93 × [VT = 1, no VT = 0] + 1.39 × [NYHA ≥3 = 1, NYHA <3 = 0] + 1.25 × [male = 1, female = 0] + 1.13 × [cTnT ≥50 μg/L = 1, cTnT <50 μg/L = 0]). The area under the receiver operating characteristic curve was 0.96 (standard error = 0.015, 95% confidence interval [CI]: 0.93-0.99). The model demonstrated that a Ccr <60 ml/min (odds ratio [OR] = 19.94, 95% CI: 5.66–70.26), an age ≥50 years (OR = 7.43, 95% CI: 2.18–25.34), VT (OR = 6.89, 95% CI: 1.86–25.44), a NYHA classification ≥3 (OR = 4.03, 95% CI: 1.13–14.32), male gender (OR = 3.48, 95% CI: 0.99–12.20), and a cTnT level ≥50 μg/L (OR = 3.10, 95% CI: 0.91–10.62) were the independent risk factors for in-hospital mortality. Conclusions: A Ccr <60 ml/min, an age ≥50 years, VT, an NYHA classification ≥3, male gender, and a cTnT level ≥50 μg/L were the independent risk factors resulting from the prediction model for in-hospital mortality in patients with suspected myocarditis. In addition, sufficient life support during the early stage of the disease might improve the prognoses of patients with suspected myocarditis with multiple risk factors for in-hospital mortality.

Keywords

• In-hospital Mortality; Logistic Model; Myocarditis; Risk Factors