College of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.
Department of Pharmacy, Southeast University Zhongda Hospital, Nanjing, Jiangsu, China.
BMJ Open. 2022 Mar 30;12(3):e055647. doi: 10.1136/bmjopen-2021-055647.
To verify whether a simplified method based on age, body mass index (BMI) and glycated haemoglobin (HbA1c) is feasible in classifying patients with type 2 diabetes (T2D), and evaluate the predictive ability of subgroups in several health and mortality outcomes.
Retrospective cohort study.
The National Health and Nutrition Examination Survey 1999-2014 cycle.
A total of 1960 participants with diabetes and the age at diagnosis greater than 30.
Participants with T2D were assigned to previously defined (by Ahlqvist) subgroups based on five variables: age, BMI, HbA1c, homoeostasis model assessment (HOMA) 2 estimates of β-cell function (HOMA2-B), and insulin resistance (HOMA2-IR), and on three variables: age, BMI and HbA1c. The classification performances of the three variables were evaluated based on 10-fold cross validation, with accuracy, precision and recall as evaluation criteria. Outcomes were assessed using logistic regression and Cox regression analysis.
Without HOMA measurements, it is difficult to identify severe insulin-resistant diabetes, but other subgroups can be ideally identified. There is no significant difference between the five variables and the three variables in the ability to predict the prevalence of poor cardiovascular health (CVH), chronic kidney disease, non-alcoholic fatty liver disease and advanced liver fibrosis, and the risk of all-cause, cardiovascular disease and cancer-related mortality (p>0.05), except the prevalence of poor CVH in mild age-related diabetes (p<0.05).
A simple classification based on age, BMI and HbA1c could be used to identify T2D with several health and mortality risks, which is accessible in most individuals with T2D. Due to its simplicity and practicality, more patients with T2D can benefit from subgroup specific treatment paradigms.
验证基于年龄、体重指数（BMI）和糖化血红蛋白（HbA1c）的简化方法是否适用于 2 型糖尿病（T2D）患者的分类，并评估该方法在多种健康和死亡结局方面对亚组的预测能力。
回顾性队列研究。
1999-2014 年全国健康和营养调查周期。
共纳入 1960 名年龄大于 30 岁且诊断时有糖尿病的参与者。
根据五个变量（年龄、BMI、HbA1c、稳态模型评估（HOMA）2 估计的β细胞功能（HOMA2-B）和胰岛素抵抗（HOMA2-IR））和三个变量（年龄、BMI 和 HbA1c）将 T2D 患者分为之前定义的亚组。基于 10 倍交叉验证，以准确性、精密度和召回率作为评估标准，评估三种变量的分类性能。使用逻辑回归和 Cox 回归分析评估结局。
不测量 HOMA 时，很难识别严重胰岛素抵抗性糖尿病，但可以理想地识别其他亚组。在预测不良心血管健康（CVH）、慢性肾脏病、非酒精性脂肪性肝病和进展性肝纤维化的患病率以及全因、心血管疾病和癌症相关死亡率的风险方面，五个变量与三个变量之间的能力没有显著差异（p>0.05），但在轻度年龄相关性糖尿病中不良 CVH 的患病率除外（p<0.05）。
基于年龄、BMI 和 HbA1c 的简单分类可用于识别具有多种健康和死亡风险的 T2D，这在大多数 T2D 患者中都可以实现。由于其简单性和实用性，更多的 T2D 患者可以从亚组特异性治疗方案中获益。
