Cui Di, Xu Haiyan, Fu Xiuju, Ma Stefan, Bee Yong Mong
Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (ASTAR), Singapore, Singapore.
Public Health Group, Ministry of Health Singapore, Singapore, Singapore.
Front Endocrinol (Lausanne). 2025 Apr 21;16:1472846. doi: 10.3389/fendo.2025.1472846. eCollection 2025.
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 trajectories were identified as follows: low stable (LowS, 22.2%), moderate low ascending (ModLowA, 12.7%), moderate high ascending (ModHighA, 11.5%), moderate low descending (ModLowD, 17.2%), moderate high descending (ModHighD, 10.1%), moderate high volatility (ModHighV, 10.1%), high with a sharp decline (HighSD, 8.0%), and high volatility (HighV, 10.2%). Using the Class LowS as a reference, the hazard ratios for recurrent HHF for the other classes are as follows: 0.79 for ModLowA, 1.30 for ModHighA, 1.17 for ModLowD, 1.89 for ModHighD, 1.94 for ModHighV, 1.25 for HighSD, and 2.88 for HighV. Considering recurrent HHFs, our NHPP model demonstrated predictive capability for type 2 diabetes patients' future HHF events.
Low baseline HbA1c levels are associated with a lower risk of recurrent HHF, while poor glycemic control significantly increases this risk. Our application of LCGM with splines effectively captures flexible, long-term HbA1c trajectories, while the innovative use of the NHPP model allows for precise modeling of HHF recurrence risk. This approach provides a foundation for personalized risk predictions and future HF management by incorporating dynamically updated risk factors.
许多临床试验在强化糖化血红蛋白控制对2型糖尿病患者心血管疾病的影响方面得出了不一致的结果。我们确定了从糖尿病诊断之日起2型糖尿病患者不同的糖化血红蛋白轨迹及其与心力衰竭再住院（HHF）的关联。
在本研究中，我们纳入了194258名在2013年至2020年期间进入新加坡健康集团糖尿病登记处的患者。他们的2型糖尿病诊断跨越1960年至2020年，包括糖化血红蛋白测量值、HHF记录以及其他心血管并发症记录。使用带样条的潜在类别增长模型（LCGM）来提取具有不同糖化血红蛋白轨迹的亚组。通过非齐次泊松过程（NHPP）研究糖化血红蛋白轨迹与HHF复发风险之间的关联。
确定了八种不同的糖化血红蛋白轨迹，如下所示：低稳定型（LowS，22.2%）、中度低上升型（ModLowA，12.7%）、中度高上升型（ModHighA，11.5%）、中度低下降型（ModLowD，17.2%）、中度高下降型（ModHighD，10.1%）、中度高波动型（ModHighV，10.1%）、高且急剧下降型（HighSD，8.0%）和高波动型（HighV，10.2%）。以LowS类别为参照，其他类别的HHF复发风险比分别为：ModLowA为0.79，ModHighA为1.30，ModLowD为1.17，ModHighD为1.89，ModHighV为1.94，HighSD为1.25，HighV为2.88。考虑到HHF再发情况，我们的NHPP模型显示了对2型糖尿病患者未来HHF事件的预测能力。
较低的基线糖化血红蛋白水平与较低的HHF复发风险相关，而血糖控制不佳会显著增加这种风险。我们应用带样条的LCGM有效地捕捉了灵活的长期糖化血红蛋白轨迹，而NHPP模型的创新使用允许对HHF复发风险进行精确建模。这种方法通过纳入动态更新的风险因素，为个性化风险预测和未来心力衰竭管理提供了基础。
