Unveiling patient profiles associated with elevated Lp(a) through an unbiased clustering analysis

通过无偏聚类分析揭示与 Lp(a) 水平升高相关的患者特征

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Abstract

INTRODUCTION: Lipoprotein(a) [Lp(a)] has been recognized as key factor in cardiovascular research. This study aimed to identify key patient profiles based on the characteristics of a Portuguese cohort of adults who were referred for Lp(a) measurement. METHOD: An unsupervised clustering analysis was performed on 661 Portuguese adults to identify patient profiles associated with lipoprotein a [Lp(a)] based on a range of demographic and clinical indicators. Lp(a) levels were deliberately excluded from the algorithm, to ensure an unbiased cluster formation. RESULTS: The analysis revealed two distinct clusters based on Lp(a) levels. Cluster 1 (n = 336) exhibited significantly higher median Lp(a) levels than Cluster 2 (n = 325; p = 0.004), with 46.4% of individuals exceeding the 75 nmol/L (30 mg/dl) risk threshold (p < 0.001). This group was characterized by older age (median 57 vs. 45 years), lower body mass index (27.17 vs. 29.40), and a majority male composition (73.8% vs. 26.5%). Additionally, Cluster 1 displayed a higher prevalence of hypertension (56.5% vs. 31.1%), diabetes mellitus (38.7% vs. 17.2%), and dyslipidemia (88.7% vs. 55.4%). These data suggest that the Cluster 1 profile has a potential increased risk for cardiovascular complications and underscore the importance of considering specific patient profiles for Lp(a) screening and cardiovascular risk assessment. CONCLUSION: Despite the study limitations, including single-institution data and potential selection bias, this study highlights the utility of cluster analysis in identifying clinically meaningful patient profiles and suggests that proactive screening and management of Lp(a) levels, particularly in patients with characteristics resembling those of Cluster 1, may be beneficial.

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