Modeling recurrent heart failure risk in type 2 diabetes: impact of flexible HbA1c trajectories using nonhomogeneous Poisson processes
Di Cui, Haiyan Xu, Xiuju Fu, Stefan Ma, Yong Mong Bee

TL;DR
This study models how changing HbA1c levels over time affect the risk of recurrent heart failure in type 2 diabetes patients.
Contribution
The novel use of nonhomogeneous Poisson processes and LCGM with splines to model dynamic HbA1c trajectories and their impact on heart failure recurrence.
Findings
Eight distinct HbA1c trajectories were identified in type 2 diabetes patients.
High volatility and poor glycemic control are strongly linked to increased heart failure risk.
The NHPP model effectively predicts future heart failure events based on HbA1c trends.
Abstract
Many clinical trials yielded inconsistent results regarding the effect of intensive glycated hemoglobin control on cardiovascular diseases in type 2 diabetes. We identified distinct HbA1c trajectories and their association with the recurrent hospitalization of heart failures (HHF) for patients with type 2 diabetes starting from the date of diabetes diagnosis. In this study, we included 194,258 patients who entered the SingHealth Diabetes Registry from 2013 to 2020. Their diagnoses of type 2 diabetes spanned the years 1960-2020, encompassing HbA1c measurements, records of HHF, and other cardiovascular complications. Latent class growth models (LCGM) with splines were used to extract the subgroups with distinct HbA1c trajectories. The association between HbA1c trajectories and the recurrent risk of HHF was investigated by nonhomogeneous Poisson processes (NHPP). Eight distinct HbA1c…
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Taxonomy
TopicsCardiovascular Function and Risk Factors · Diabetes Management and Research · Diabetes Treatment and Management
