Xu G, Chen F, Zhao W, Zheng Y, Zhuang W, Yu F. Establishment and assessment of a nomogram model for predicting the risk of fulminant myocarditis: A STROBE compliant cross-sectional study.
Medicine (Baltimore) 2021;
100:e25317. [PMID:
33907091 PMCID:
PMC8084052 DOI:
10.1097/md.0000000000025317]
[Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 02/19/2021] [Accepted: 03/02/2021] [Indexed: 11/27/2022] Open
Abstract
ABSTRACT
We aimed to identify potential clinical predictors associated with the risk of fulminant myocarditis, and further to establish and assess a nomogram model based on significant attributes for clinical practicability.This is a retrospective, cross-sectional study, involving 28 patients with fulminant myocarditis and 35 age-, and sex-matched patients with non-fulminant myocarditis. Effect-size estimates are expressed as odds ratio (OR) and 95% confidence interval (CI).Fifteen factors were primarily identified to be associated with the significant risk of fulminant myocarditis after adjusting for confounders. Due to strong correlation, 6 factors were retained, including mean arterial pressure (OR, 95% CI, P: .82, .72-.94, .005), creatinine (2.15, 1.13-4.10, 0.020), blood urea nitrogen (1.45, 1.04-2.02, 0.028), aspartate aminotransferase (2.62, 1.16-5.91, 0.021), troponin I (1.43, 1.07-1.90, 0.015), and ventricular wall motion abnormality (25.81, 2.52-264.69, 0.006). The contribution of the 6 significant factors to predicting fulminant myocarditis risk was significant from multi-angle analyses, and regressing these factors in a nomogram model exhibited good predictive accuracy, as reflected by both C-index (>90%, P < .001).We have identified 6 clinical factors in significant association with fulminant myocarditis, and their prediction capability was more obvious in a nomogram model. Further investigations with larger sample sizes and longer follow-up intervals are warranted.
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