| Background:Acute myocarditis is an inflammatory disease of the myocardium due to various causes,with widely varying clinical manifestations.Common acute myocarditis has widely varying clinical manifestations,mostly with mild symptoms,and fulminant myocarditis(FM)is the most severe type of myocarditis,which is defined as myocarditis with a symptom duration of <2 weeks,accompanied by severe heart failure requiring positive inotropic or mechanical circulatory support,and characterized by sudden,severe diffuse Cardiac inflammation is characterized by sudden,severe diffuse inflammation,often leading to fatal outcomes such as ventricular arrhythmias,cardiogenic shock,and multi-organ failure.These fatal outcomes often occur in the acute phase,and if treated promptly,patients with fulminant myocarditis can have a survival rate of more than 50%.Early identification of individuals at risk for fulminant myocarditis and measures to prevent its development into overt fulminant myocarditis and reduce its fatal outcome are crucial.Therefore,it is necessary to conduct studies related to early identification of predictive models for fulminant myocarditis to provide a scientific basis for early and timely detection of patients at high risk of fulminant myocarditis.Objective:The aim of this study was to analyze the clinical characteristics and risk factors associated with fulminant myocarditis,further construct a columnar graph model to predict the likelihood of fulminant progression in patients with acute myocarditis,and validate and evaluate the model to facilitate clinical decision makers to quantitatively assess the risk of fulminant progression in patients with acute myocarditis conveniently and quickly.Methods:The study was a single-center retrospective study.Two hundred and forty patients diagnosed with acute myocarditis/ fulminant myocarditis from January 2016 to January 2023 at the First Affiliated Hospital of Nanchang University were included and divided into FM group(n=70)and NFM group(n=170)according to diagnostic criteria.Demographic characteristics,admission vital signs,major symptoms,laboratory indices,electrocardiographic and echocardiographic findings were compared between the two groups.After cleaning and processing the data,all samples were randomly divided into modeling and validation groups in the ratio of7:3.Single-factor and multi-factor logistic regression and Lasso regression were used to jointly confirm the independent risk factors for fulminant progression of acute myocarditis,and further construct the column line graph prediction model.The distinguishing ability,calibration ability and clinical utility of the models were also evaluated and validated in the two groups,respectively.Results:1.The FM group and the NFM group were compared in terms of age,heart rate,systolic blood pressure,diastolic blood pressure,glutathione transaminase,glutamic oxalacetic transaminase,total bilirubin,blood creatinine,blood urea nitrogen,creatine kinase,creatine kinase isoenzyme,albumin,white blood cell count,platelet count,neutrophil count,lymphocyte count,C-reactive protein,NT-pro BNP level,troponin positive rate,corrected QT interval(QTc)time and QRS wave group time frame and left ventricular ejection fraction were compared with statistically significant differences(P<0.05).There was a statistically significant difference between the two groups in the proportion of syncope,palpitations,chest tightness symptoms and ECG examination with severe AV block,low voltage in the thoracic leads,abnormal Q waves,bundle branch block,accelerated arrhythmias,ST segment and T wave changes(P<0.05).There were no statistically significant differences between the two groups when comparing sex,weight,respiratory rate,anterior-posterior left atrial diameter,septal thickness,posterior left ventricular wall thickness,left ventricular end-diastolic diameter,frequency of symptoms presenting with nausea and vomiting,fever,chest pain,and frequency of poor R-wave progression in the thoracic leads and premature ventricular or atrial beats on electrocardiography(P > 0.05).2.In the modeling group,Lasso regression analysis and univariate and multivariate logistic regression revealed that higher heart rate and lower diastolic blood pressure level at admission,elevated cardiac function marker BNP,and wide QRS wave and ST-segment or T-wave abnormalities on ECG could be used as independent risk factors for fulminant myocarditis,and the risk prediction model was constructed accordingly,and the model was visualized by drawing a column line diagram.3.The established prediction models were evaluated and validated in the modeling and validation groups,respectively,and the results showed that the AUC of the modeling group was 0.940(95% CI: 0.935-0.946)and the AUC of the validation group was 0.935(95% CI: 0.922-0.947),the calibration curve showed that the model was well calibrated,and the decision curve analysis showed that the model could obtain a net clinical benefit.Conclusions:1.high heart rate on admission,low diastolic blood pressure,elevated BNP,wide QRS waves on ECG and ST-segment or T-wave abnormalities are independent risk factors for fulminant progression in patients with acute myocarditis.2.A risk prediction model for early identification of fulminant myocarditis was constructed based on five independent risk factors:Probability=1/(1+exp(-(-10.389+0.033 x HR-0.040 x DBP+1.852xlog10(BNP)+0.036 x QRS wave group time limit-1.153 x ST-T changes)))3.The model was evaluated and validated,and the results showed that the early identification of fulminant myocarditis risk prediction model established in this study has good differentiation ability,calibration and certain clinical utility,proving that the model has good prediction ability and can provide reference for clinical workers to identify patients at high risk of fulminant myocarditis at an early stage for early intervention. |
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