Machine Learning-based Mortality Prediction for Pediatric Fulminant Myocarditis Using Cytokine Profiles

Abstract

Background Fulminant myocarditis (FM) is a rare but life-threatening pediatric condition that rapidly progresses to cardiogenic shock and fatal arrhythmias. Early identification of prognostic biomarkers is vital for timely intervention and better outcomes. Although inflammatory cytokines contribute to FM pathogenesis, their prognostic value remains unclear. This study aimed to identify mortality-associated markers by integrating cytokine profiles and clinical variables through a machine learning approach.

Methods We retrospectively analyzed 21 pediatric FM cases from two tertiary centers (2012–2022). At admission, 37 cytokines and 14 clinical parameters were assessed. Partial least squares discriminant analysis was employed to identify prognostic features, with variable importance in projection scores quantifying their contribution. Model performance was evaluated using leave-one-out cross-validation. Statistical significance was determined via the Benjamini-Hochberg method at a false discovery rate of 0.05.

Results Of the 51 features analyzed, 23 emerged as key predictors with variable importance in projection scores above 1.0, including 20 cytokines and three clinical parameters. Six cytokines (TNF-α, M-CSF, MIP-1α, IL-8, IL-6, and IL-15) were both statistically significant and highly important. Elevated CK-MB and lactate levels and lower pH were also linked to poor outcomes. The model performed robustly, with an AUC of 0.92, 85.7% accuracy, 92.9% sensitivity, and 71.4% specificity.

Conclusions TNF-α emerged as a key cytokine linked to mortality in pediatric FM, supporting its role as a prognostic biomarker and potential therapeutic target.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This research was supported by grants from the Suzuken Memorial Foundation 2021, Japan; AMED under Grant Number JP23tm0524001; and JSPS KAKENHI Grant Number JP24K15184.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The Ethics Committee of Aichi Children's Health and Medical Center and the Ethics Committee of Fujita Health University gave ethical approval for this work (approval numbers 2019027 and HM21-575, respectively). All procedures were conducted in accordance with institutional ethical guidelines and the Declaration of Helsinki. Informed consent was obtained from all participants prior to their involvement in the study.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

DATA AVAILABILITY

De-identified data analyzed in this study are presented in the main text and tables. Additional data are available from the corresponding author upon reasonable request.

Non-standard Abbreviations and AcronymsAMAcute MyocarditisAUC-ROCArea Under the Receiver Operating Characteristic CurveBNPB-type Natriuretic PeptideCAVBComplete Atrioventricular BlockCK-MBCreatine Kinase MBECMOExtracorporeal Membrane OxygenationFDRFalse Discovery RateFMFulminant MyocarditisFNFalse NegativesFPFalse PositivesLOOCVLeave-One-Out Cross-ValidationLVEFLeft Ventricular Ejection FractionMCSMechanical Circulatory SupportPLS-DAPartial Least Square Discriminant AnalysisROCReceiver Operating Characteristic CurveTNF-αTumor necrosis factor-alphaTNTrue NegativesTPTrue PositivesVIPVariable Importance in ProjectionVTVentricular Tachycardia

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