ArticleAmerican heart journal plus : cardiology research and practice2026
Trends, disparities and projections of pericardial diseases related mortality in the United States: A 1999-2035 analysis using artificial deep neural network.
Article in American heart journal plus : cardiology research and practice, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Pericardial Diseases (PD) are a significant cause of morbidity and mortality. However, relevant data for PD-related mortality are limited. This study aims to evaluate the demographic and geographical variations in PD-related mortality in the United States and utilize deep learning model to forecast mortality trends. Methods: PD-related deaths in adults aged ≥25 years were identified using CDC WONDER from 1999 to 2019. Age-adjusted mortality rates (AAMRs) per 100,000 were determined. Joinpoint regression was used to calculate annual percentage change (APC) with 95% Confidence Intervals (CIs). A Long Short-Term Memory (LSTM) recurrent neural network was developed to predict future mortality. Results: Between 1999 and 2019, a total of 87,285 deaths were related to PD in the United States. The AAMR declined from 2.36 in 1999 to 1.70 in 2012 (APC: -2.74; 95% CI: -2.97 to -2.49; Conclusion: Despite overall decline, the recent and projected rise in PD-related mortality highlights the urgent need to improve equitable healthcare access, particularly among males, NH Black population, and West region, who exhibit persistent disparities.
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