Establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: A STROBE compliant cross-sectional study

Establishment and validation of a prediction model for myocarditis in Chinese children below 14 years old: a protocol for a retrospective cohort study

INTRODUCTION

Paediatric myocarditis, a rare inflammatory disease, often presents without clear early symptoms. Although cardiac troponin I levels can aid in diagnosing myocarditis, they are not definitive indicators. Troponin I levels frequently fluctuate within and outside the reference range, potentially causing misinterpretations by clinicians. Although a negative troponin I result is valuable for excluding myocarditis, its specificity is low. Moreover, the clinical diagnosis of paediatric myocarditis is exceptionally challenging, and accurate early-stage diagnosis and treatment pose difficulties. Currently, the Dallas criteria, involving cardiac biopsy, serves as the gold standard for myocarditis diagnosis. However, this method has several drawbacks and is unsuitable for children, resulting in its limited use.

METHODS AND ANALYSIS

In this study, we will employ multiple logistic regression analysis to develop a predictive model for early childhood myocarditis. This model will assess the patient's condition at onset and provide the probability of a myocarditis diagnosis. Model performance will be evaluated for accuracy and calibration, and the results will be presented through receiver operating characteristic (ROC) curves and calibration plots. Clinical decision curve analysis, in conjunction with ROC curve analysis, will be employed to determine the optimal cut-off value and calculate the net clinical benefit value for assessing clinical effectiveness. Finally, internal model validation will be conducted using bootstrapping.

ETHICS AND DISSEMINATION

Approval from the Clinical Research Ethics Committee of The Third Affiliated Hospital of Wenzhou Medical University has been obtained. The research findings will be disseminated through presentations at scientific conferences and publication in peer-reviewed journals.

Development and Validation of a Prediction Model on Adult Emergency Department Patients for Early Identification of Fulminant Myocarditis

OBJECTIVE

It is difficult to predict fulminant myocarditis at an early stage in the emergency department. The objective of this study was to construct and validate a simple prediction model for the early identification of fulminant myocarditis.

METHODS

A total of 61 patients with fulminant myocarditis and 160 patients with acute myocarditis were enrolled in the training and internal validation cohorts. LASSO regression and multivariate logistic regression were selected to develop the prediction model. The selection of the model was based on overall performance and simplicity. A nomogram based on the optimal model was built, and its clinical usefulness was evaluated by decision curve analysis. The predictive model was further validated in an external validation group.

RESULTS

The resulting prediction model was based on 4 factors: systolic blood pressure, troponin I, left ventricular ejection fraction, and ventricular wall motion abnormality. The Brier scores of the final model were 0.078 in the training data set and 0.061 in the internal testing data set, respectively. The C-indexes of the training data set and the testing data set were 0.952 and 0.968, respectively. Decision curve analysis showed that the nomogram model developed based on the 4 predictors above had a positive net benefit for predicting probability thresholds. In the external validation cohort, the model also showed good performance (Brier score=0.007, and C-index=0.989).

CONCLUSION

We developed and validated an early prediction model consisting of 4 clinical factors (systolic blood pressure, troponin I, left ventricular ejection fraction, and ventricular wall motion abnormality) to identify potential fulminant myocarditis patients in the emergency department.

PD-1 inhibitors-associated myocarditis in non-small cell lung cancer patients

Background

Immune checkpoint inhibitors (ICIs)-associated myocarditis remains a rare but fatal adverse event. The authors sought to provide a comprehensive clinical description of ICI-associated myocarditis by analyzing symptoms, laboratory indicators, imaging features, and management of ICI-associated myocarditis in patients with non-small cell lung cancer (NSCLC).

Methods

A retrospective study was conducted to analyze 14 ICI-associated myocarditis cases and 45 control patients to clarify clinical features of ICI-associated myocarditis. Detailed laboratory tests and imaging examinations were performed in 14 cases, and the rescue process and follow-up after the onset of myocarditis were recorded.

Results

A total of 14 (2.08%) NSCLC patients developed ICI-related myocarditis, with a median time of onset of 34 days (interquartile range, 12 to 146 days) after ICI initiation. The most common concurrent adverse events in cases were myositis (P<0.001) and peripheral neuritis (P<0.001). Among cases, cardiac troponin I (cTnI) levels were abnormally elevated in 92% of patients, and electrocardiogram (ECG) showed abnormal in all cases. Steroid therapy was used in 92.9% of patients with ICI-associated myocarditis, of which the response rate to steroids was 76.9% and the mortality rate was 7.1%. A dose of 1 g/d of glucocorticoid supplemented by immunoglobulin was observed to be effective for severe myocarditis.

Conclusions

Early identification and treatment are essential for managing myocarditis caused by ICI. Routine monitoring of cTnI level and ECG is most sensitive for the early diagnosis of ICI-related myocarditis. High-dose of glucocorticoids can effectively relieve the symptoms of ICI-associated myocarditis and stabilize the condition, especially for fulminant myocarditis.