Data-Driven Phenotyping Reveals Non-Uniform Association between Age and Mortality After Aortic Surgery: A Retrospective Cohort Study of UK Biobank Data
ABSTRACT
Background:
Life expectancy and age are frequently considered factors to assess peri- and post-operative mortality risks in patients affected by aortic pathologies, which can affect the decision whether to suggest invasive treatment.
Objective:
To investigate the association between age and all-cause mortality after invasive aortic treatment.
Methods:
Unsupervised clustering (k-means) utilizing data from the UK Biobank was conducted for patients with aortic pathologies (ICD-10 group I71) receiving endovascular or open surgical treatment. Clustering variables encompassed demographic and clinical parameters. Survival analyses between clusters and cluster-derived age groups were conducted.
Results:
The study included 1,801 individuals undergoing surgical or endovascular repair for aortic aneurysms. Unsupervised cluster analysis identified distinct groups primarily based on age, both in models using 2 or 3 clusters. Clusters with older patients at surgery exhibited lower post-operative survival, with peri-operative mortality disproportionately affecting these groups. While age was significantly associated with post-operative mortality overall (HR: 1.07, 95%CI: 1.05 – 1.08), this association diminished in older clusters after excluding peri-operative deaths, a trend confirmed in analyses adjusted for relevant confounders.
Conclusions:
Unsupervised cluster analysis revealed age as the primary factor distinguishing patient groups undergoing invasive treatment for aortic pathologies. However, age at surgery appears to have different consequences in certain age brackets indicating a complex non-linear relationship.
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