The Early Dynamic Change in Cardiac Enzymes and Renal Function Is Associated with Mortality in Patients with Fulminant Myocarditis on Extracorporeal Membrane Oxygenation: Analysis of a Single Center's Experience.
Ching-Lin HoTeressa Reanne JuChi Chan LeeHsin-Ti LinAlexander-Lee WangRobert Jeen-Chen ChenYou-Cian LinPublished in: Healthcare (Basel, Switzerland) (2022)
(1) Background: Fulminant myocarditis (FM) could result in hemodynamic derangement and fatal arrhythmia. Veno-arterial extracorporeal membrane oxygenation (V-A ECMO) is used to maintain organ perfusion in FM patients complicating cardiogenic shock. The present study aims to assess the static and dynamic factors in association with mortality in FM patients on V-A ECMO (2) Methods: Twenty-eight patients were enrolled between 2013 to 2019 for analysis (3) Results: In-hospital survival rate was 78.5%. There was no statistical difference in demographics and baseline laboratory data between survivors and non-survivors. However, within 24 h after ECMO support, CK-MB increased by 96.8% among non-survivors, but decreased by 23.7% among survivors ( p = 0.022). Troponin I increased by 378% among non-survivors and 1.7% among survivors ( p = 0.032). Serum creatinine increased by 108% among non-survivors, but decreased by 8.5% among survivors ( p = 0.005). The receiver operating characteristic curve suggested an increase in serum creatinine by 68% within 24 h after ECMO support was associated with increased mortality with an area under the curve of 0.91. (4) Conclusions: V-A ECMO is an excellent tool to support FM patients with cardiogenic shock. The early dynamic change of renal function and cardiac enzymes may be useful for outcome assessment.
Keyphrases
- extracorporeal membrane oxygenation
- acute respiratory distress syndrome
- young adults
- respiratory failure
- end stage renal disease
- newly diagnosed
- ejection fraction
- prognostic factors
- computed tomography
- risk factors
- healthcare
- heart failure
- left ventricular
- intensive care unit
- cardiovascular disease
- metabolic syndrome
- deep learning
- machine learning
- electronic health record
- patient reported