Xiuqi Qiao, Xinda Chen, Weihao Wang, Lixin Guo, Qi Pan
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引用次数: 0
Abstract
Background: To explore the precise classification of elderly patients with multimorbidity and identify subgroups with an increased prevalence of related diseases.
Methods: A data-driven clustering analysis (K-means clustering) was conducted on individuals aged 60 years or older with comorbidities. The clustering was based on five essential and routinely measured variables: body mass index (BMI), intrinsic capacity (IC), low-density lipoprotein cholesterol (LDL-c), fasting plasma glucose (FPG), and systolic blood pressure (SBP). Logistic regression models were used to compare the prevalence of diabetes, coronary heart disease, hypertension, osteoporosis, sarcopenia, and frailty among the clusters.
Results: A total of 350 elderly patients with a mean age of 78.74 ± 8.27 years were included. Four subtypes of elderly patients with multimorbidity were identified, with significant differences in disease prevalence observed among the groups. Specifically, cluster 1 included 70 participants who exhibited the highest levels of LDL-c and BMI, as well as relatively higher IC scores. Cluster 2 consisted of 117 participants, who had the highest IC scores among all clusters and similar BMI levels to cluster 1. Cluster 3 included 77 participants and was distinguished by the highest SBP levels. Cluster 4, comprising 86 participants, had the lowest IC and BMI levels. Compared with cluster 2, cluster 4 had significantly higher prevalence of hypertension and frailty. Cluster 3 and 4 had higher prevalence of coronary heart disease compared with cluster 1, and cluster 4 had the highest prevalence of osteoporosis and sarcopenia.
Conclusion: There is significant pathophysiological heterogeneity among individuals with elderly multimorbidity. This classification method provides a crucial foundation for understanding disease complexity in this population. Future research, including intervention studies based on these classifications, is needed to evaluate their potential clinical utility.
期刊介绍：
Clinical Interventions in Aging, is an online, peer reviewed, open access journal focusing on concise rapid reporting of original research and reviews in aging. Special attention will be given to papers reporting on actual or potential clinical applications leading to improved prevention or treatment of disease or a greater understanding of pathological processes that result from maladaptive changes in the body associated with aging. This journal is directed at a wide array of scientists, engineers, pharmacists, pharmacologists and clinical specialists wishing to maintain an up to date knowledge of this exciting and emerging field.
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