A novel prediction model for myocardial fibrosis in patients suspected of myocarditis

Year 2024, Volume: 49 Issue: 1, 192 - 203, 29.03.2024

Aslan Erdoğan , Omer Genç , İhsan Demirtaş , Muhammed Mert Göksu , Berk Erdinç , Duygu Genç , Abdullah Yıldırım , Yiğit Can Kartal

https://doi.org/10.17826/cumj.1439074

Abstract

Purpose: This study aimed at establishing a predictive method that consists of clinical, electrocardiographic (ECG), and laboratory parameters for myocardial fibrosis, especially as detected on cardiac magnetic resonance imaging (CMRI), in patients examined with suspicion of myocarditis.
Materials and Methods: This study is a retrospective, single-centre study that includes patients admitted to our centre with suspected myocarditis between March 2020 and November 2023. Participants were categorised into two groups (myocardial fibrosis positive and myocardial fibrosis negative), and a detailed comparison of comorbidities, ECG changes, and laboratory parameters was performed. Multivariate analysis was conducted to identify independent predictors of myocardial fibrosis. A nomogram was constructed using the coefficients from the multivariate analysis to estimate the probability of myocardial fibrosis presence based on key predictors.
Results: This study included 98 participants with a median age of 30 years, predominantly male (80.6%), with 14.3% having hypertension, 8.2% having diabetes mellitus, and 10.2% being smokers. The myocardial fibrosis-negative group exhibited higher levels of left ventricular ejection fraction and lymphocyte count. Conversely, the myocardial fibrosis-positive group showed higher levels of ECG changes at admission, peak C-reactive protein (CRP), CRP velocity, peak troponin, N-terminal pro-brain natriuretic peptide (NT-proBNP), monocytes, and platelets (PLT). In multivariate analysis, PLT, lymphocyte, monocyte, peak troponin, and ECG changes were identified as independent predictors of myocardial fibrosis. Receiving operating characteristic (ROC) curve analysis showed the model's diagnostic accuracy for predicting myocardial fibrosis (area under the ROC (AUC): 0.959, 95% confidence interval (CI), and p<0.001).
Conclusion: This comprehensive analysis highlights the relationships between clinical and laboratory parameters and myocardial fibrosis and presents a predictive model with high diagnostic accuracy.

Keywords

Endomyocardial fibrosis, magnetic resonance ımaging, myocarditis

Miyokardit şüphesi olan hastalarda miyokardiyal fibrozis için yeni bir tahmin modeli

Abstract

Amaç: Bu çalışmanın amacı, miyokardit şüphesi ile tetkik edilen hastalarda özellikle kardiyak manyetik rezonans görüntülemede saptanan miyokardiyal fibrozisi klinik, elektrokardiyografik (EKG) ve laboratuvar parametrelerinden oluşan bir öngörücü metod ile saptamaya çalışmaktır.
Gereç ve Yöntem: Bu çalışma, Mart 2020 ile Kasım 2023 tarihleri arasında merkezimize şüpheli miyokardit ile başvuran hastaları içeren retrospektif, tek merkezli bir çalışmadır. Katılımcılar, miyokardiyal fibrosiz pozitif ve negatif olmak üzere iki gruba ayrıldı. Komorbid durumlar, EKG değişiklikleri ve laboratuvar parametrelerinin detaylı bir karşılaştırması yapıldı. Miyokard fibrozunun bağımsız belirleyicilerini tanımlamak için çok değişkenli analiz yapıldı. Çok değişkenli analizden elde edilen katsayılar kullanılarak miyokardiyal fibrosizin varlığını tahmin etmek amacıyla bir nomogram oluşturuldu.
Bulgular: Bu çalışma, yaş ortalaması 30 olan, %80.6’sı erkek, 98 katılımcıyı içermektedir. Hastaların %14.3'ünde hipertansiyon, %8.2'sinde diyabet varken %10.2'si sigara içicisiydi. Miyokardiyal fibrozis negatif grupta, sol ventrikül ejeksiyon fraksiyonu ve lenfosit sayısı daha yüksek oranlarda izlendi. Aksine miyokardiyal fibrozis pozitif grupta başvuruda EKG değişiklikleri, pik CRP, CRP velositesi, pik troponin, NT-proBNP, monosit ve trombosit (PLT) düzeyleri daha yüksek seviyelere sahipti. Çok değişkenli analizde PLT sayısı, lenfosit sayısı, monosit sayısı, pik troponin ve başvuru esnasındaki EKG değişiklikleri miyokard fibrozunun bağımsız belirleyicileri olarak saptandı. ROC eğrisi analizi, miyokardial fibrozisi tahmin etme modelinin doğru tanı koyma gücüne sahip olduğunu gösterdi. (AUC: 0.959, p<0.001).
Sonuç: Bu kapsamlı analiz, klinik ve laboratuvar parametreleri ile miyokard fibrozu arasındaki ilişkilere öngörüler sunarak, doğru tanı koyma oranına sahip bir tahmin modeli sunmaktadır.

Keywords

Endomiyokardiyal fibrozis, manyetik rezonans görüntüleme, miyokardit

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