STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium.
Academic Centre of General Practice, Department of Public Health and Primary Care, KU Leuven, Belgium.
J Gerontol A Biol Sci Med Sci. 2021 Jun 14;76(7):1234-1241. doi: 10.1093/gerona/glaa278.
The prevalence of multimorbidity is increasing in recent years, and patients with multimorbidity often have a decrease in quality of life and require more health care. The aim of this study was to explore the evolution of multimorbidity taking the sequence of diseases into consideration.
We used a Belgian database collected by extracting coded parameters and more than 100 chronic conditions from the Electronic Health Records of general practitioners to study patients older than 40 years with multiple diagnoses between 1991 and 2015 (N = 65 939). We applied Markov chains to estimate the probability of developing another condition in the next state after a diagnosis. The results of Weighted Association Rule Mining (WARM) allow us to show strong associations among multiple conditions.
About 66.9% of the selected patients had multimorbidity. Conditions with high prevalence, such as hypertension and depressive disorder, were likely to occur after the diagnosis of most conditions. Patterns in several disease groups were apparent based on the results of both Markov chain and WARM, such as musculoskeletal diseases and psychological diseases. Psychological diseases were frequently followed by irritable bowel syndrome.
Our study used Markov chains and WARM for the first time to provide a comprehensive view of the relations among 103 chronic conditions, taking sequential chronology into consideration. Some strong associations among specific conditions were detected and the results were consistent with current knowledge in literature, meaning the approaches were valid to be used on larger data sets, such as National Health care Systems or private insurers.
近年来，多种疾病的患病率不断上升，患有多种疾病的患者生活质量往往下降，需要更多的医疗保健。本研究旨在探讨考虑疾病序列的情况下，多种疾病的演变。
我们使用了一个比利时数据库，该数据库通过从全科医生的电子健康记录中提取编码参数和 100 多种慢性疾病来收集数据，研究了 1991 年至 2015 年间患有多种诊断的 40 岁以上患者（N=65939）。我们应用马尔可夫链来估计在诊断后下一个状态发生另一种疾病的概率。加权关联规则挖掘（WARM）的结果允许我们展示多种疾病之间的强关联。
约 66.9%的选定患者患有多种疾病。高血压和抑郁障碍等高患病率的疾病很可能在大多数疾病诊断后发生。基于马尔可夫链和 WARM 的结果，几个疾病组的模式是明显的，例如肌肉骨骼疾病和心理疾病。心理疾病经常伴随着肠易激综合征。
我们的研究首次使用马尔可夫链和 WARM 提供了 103 种慢性疾病之间的关系的综合视图，同时考虑了连续的时间顺序。检测到了一些特定条件之间的强关联，结果与文献中的现有知识一致，这意味着这些方法可以在更大的数据集（如国家医疗保健系统或私人保险公司）上有效使用。
