Department of Legal Medicine, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, Japan.
Department of Clinical Research and Development, National Cerebral and Cardiovascular Center, 6-1 Kishibe-Shimmachi, Suita, Osaka, Japan.
Sci Rep. 2023 Mar 16;13(1):4352. doi: 10.1038/s41598-023-31600-0.
We aimed to identify combinations of clinical factors that predict heart failure (HF) onset using a novel limitless-arity multiple-testing procedure (LAMP). We also determined if increases in numbers of predictive combinations of factors increases the probability of developing HF. We recruited people without HF who received health check-ups in 2010, who were followed annually for 4 years. Using 32,547 people, LAMP was performed to identify combinations of factors of fewer than four factors that could predict the onset of HF. The ability of the method to predict the probability of HF onset based on the number of matching predictive combinations of factors was determined in 275,658 people. We identified 549 combinations of factors for the onset of HF. Then we classified 275,658 people into six groups who had 0, 1-50, 51-100, 101-150, 151-200 or 201-250 predictive combinations of factors for the onset of HF. We found that the probability of HF progressively increased as the number of predictive combinations of factors increased. We identified combinations of variables that predict HF onset. An increased number of matching predictive combinations for the onset of HF increased the probability of HF onset.
我们旨在使用一种新的无限复杂度多重检验程序（LAMP）来确定预测心力衰竭（HF）发生的临床因素组合。我们还确定了预测因素组合数量的增加是否会增加发生 HF 的概率。我们招募了 2010 年接受健康检查且没有 HF 的人群，并在接下来的 4 年中每年对其进行随访。使用 32547 人，通过 LAMP 确定了少于四个因素的可预测 HF 发生的因素组合。在 275658 人中确定了该方法基于匹配的预测因素组合数量预测 HF 发生概率的能力。我们确定了 549 个与 HF 发生相关的因素组合。然后我们将 275658 人分为六组，这些组的人分别具有 0、1-50、51-100、101-150、151-200 或 201-250 个预测 HF 发生的因素组合。我们发现，随着预测因素组合数量的增加，HF 的发生概率逐渐增加。我们确定了可预测 HF 发生的变量组合。预测 HF 发生的匹配预测组合数量的增加会增加 HF 发生的概率。
