Identifying subgroups in sepsis patients with comorbidities by clustering and network analysis
Sepsis is a life-threatening condition caused by severe infection, affecting millions of people worldwide. We analysed hospital records of over 11,000 patients and identified three distinct groups based on their comorbidities (i.e., other diseases the patient has at the same time). We compared and analysed the comorbidity structures and clinical differences among these groups, finding significant variations in disease patterns and outcomes. These findings contribute to a deeper understanding of the heterogeneity among sepsis patients and provide evidence to inform personalised treatment strategies for different subgroups.
Keywords
part of my PhD research
Staff
Areti Manataki, Martin McKechnie