Quantifying lifetime risk for 1,401 infectious diseases across the diabetes spectrum using a Bayesian approach

Area of Science:

• Endocrinology
• Infectious Diseases
• Biostatistics

Background:

• Diabetes mellitus, encompassing type 1 diabetes (T1D), type 2 diabetes (T2D), and prediabetes, is associated with numerous health complications.
• While some diabetes-associated infections are well-documented, a comprehensive understanding of the infection burden across diverse patient populations and pathogen types remains incomplete.

Purpose of the Study:

• To quantify the risk of a wide spectrum of infectious diseases in patients with T1D, T2D, and prediabetes.
• To compare infection risks across different diabetes statuses and identify specific infection types with elevated risk.
• To investigate potential sociodemographic disparities in infection risk among these patient groups.

Main Methods:

• A Bayesian statistical approach was employed to analyze infection risk.
• Data from 9,476 patients with T1D, 74,270 with T2D, and 32,095 with prediabetes were analyzed.
• Infection risks were assessed for composite outcomes across organ systems and pathogens, as well as for 1,401 individual infection outcomes.

Main Results:

• Patients with T1D, T2D, and prediabetes exhibited substantially increased risks for composite infection outcomes.
• Elevated risks were identified for 880 individual infections in T1D, 1,047 in T2D, and 991 in prediabetes.
• Increased risks were observed for both established diabetes-associated infections (e.g., mucormycosis) and less commonly associated infections (e.g., West Nile Virus encephalitis).
• Significant disparities in infection risk were found across sociodemographic subgroups, including age, sex, ethnicity, ancestry, and insurance status.

Conclusions:

• This study provides a comprehensive quantification of infection risks associated with T1D, T2D, and prediabetes using an innovative Bayesian methodology.
• The findings highlight a broad and significant increase in susceptibility to diverse infections in individuals with diabetes and prediabetes.
• Addressing sociodemographic disparities is crucial for mitigating infection risks in these vulnerable populations.