Predicting the prevalence and estimating the economic burden of ischemic heart disease in China: Based on long short-term memory model

基于长短期记忆模型预测中国缺血性心脏病的患病率并估算其经济负担

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Abstract

Ischemic heart disease (IHD), characterized by myocardial damage from altered coronary circulation, has become a serious threat to the public health of the population. We aimed to predict the future prevalence of IHD and estimate its economic burden in China. Data on the number of patients with IHD in China were derived from the Global Burden of Disease. Long Short-Term Memory network was trained on data from 1990 to 2015, and validated using data to predict the future prevalence of IHD from 2022 to 2030. We used the bottom-up and human capital approach to estimate the direct and indirect economic burden of IHD, respectively. The model demonstrated a strong fit on the training set, and the results of RMSE (212,356.03), MAE (163,366.30), MAPE (0.57%) and R2 (99.95%) showed that the model fitted well. On the testing set, the results of RMSE (364,393.64), MAE (321,570.00), MAPE (0.54%) and R2 (97.96%) showed that the model predicted well. From 2022 to 2030, the number of patients with IHD is projected to increase from approximately 66 million to 154 million. From 2022 to 2030, the total economic burden of IHD would be approximately $220 billion, $233 billion, $247 billion, $265 billion, $288 billion, $318 billion, $359 billion, $418 billion and $512 billion, respectively. The prevalence and economic burden with IHD in China are projected to increase substantially in the future. These findings underscore the urgent need for collaborative efforts among the state, society, and the public in the prevention and control of IHD to reduce the economic burden.

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