National Clinical Research Center for Metabolic Diseases, Key Laboratory of Diabetes Immunology, Ministry of Education, Department of Metabolism and Endocrinology, The Second Xiangya Hospital of Central South University, Changsha, China.
Front Endocrinol (Lausanne). 2022 Sep 20;13:948157. doi: 10.3389/fendo.2022.948157. eCollection 2022.
We aimed to explore the performance of detrended fluctuation function (DFF) in distinguishing patients with latent autoimmune diabetes in adults (LADA) from type 2 diabetes mellitus (T2DM) with glucose data derived from continuous glucose monitoring.
In total, 71 LADA and 152 T2DM patients were enrolled. Correlations between glucose parameters including time in range (TIR), mean glucose, standard deviation (SD), mean amplitude of glucose excursions (MAGE), coefficient of variation (CV), DFF and fasting and 2-hour postprandial C-peptide (FCP, 2hCP) were analyzed and compared. Receiver operating characteristics curve (ROC) analysis and 10-fold cross-validation were employed to explore and validate the performance of DFF in diabetes classification respectively.
Patients with LADA had a higher mean glucose, lower TIR, greater SD, MAGE and CV than those of T2DM (<0.001). DFF achieved the strongest correlation with FCP (r = -0.705, <0.001) as compared with TIR (r = 0.485, <0.001), mean glucose (r = -0.337, <0.001), SD (r = -0.645, <0.001), MAGE (r = -0.663, <0.001) and CV (r = -0.639, <0.001). ROC analysis showed that DFF yielded the greatest area under the curve (AUC) of 0.862 (sensitivity: 71.2%, specificity: 84.9%) in differentiating LADA from T2DM as compared with TIR, mean glucose, SD, MAGE and CV (AUC: 0.722, 0.650, 0.800, 0.820 and 0.807, sensitivity: 71.8%, 47.9%, 63.6%, 72.7% and 78.8%, specificity: 67.8%, 83.6%, 80.9%, 80.3% and 72.4%, respectively). The kappa test indicated a good consistency between DFF and the actual diagnosis (kappa = 0.551, <0.001). Ten-fold cross-validation showed a stable performance of DFF with a mean AUC of 0.863 (sensitivity: 78.8%, specificity: 77.8%) in 10 training sets and a mean AUC of 0.866 (sensitivity: 80.9%, specificity: 84.1%) in 10 test sets.
A more violent glucose fluctuation pattern was marked in patients with LADA than T2DM. We first proposed the possible role of DFF in distinguishing patients with LADA from T2DM in our study population, which may assist in diabetes classification.
我们旨在探讨去趋势波动函数（DFF）在利用连续血糖监测获得的血糖数据区分成人隐匿性自身免疫性糖尿病（LADA）与 2 型糖尿病（T2DM）患者中的表现。
共纳入 71 例 LADA 和 152 例 T2DM 患者。分析并比较了血糖参数（TIR、平均血糖、标准差、血糖波动幅度、变异系数）与空腹和餐后 2 小时 C 肽（FCP、2hCP）之间的相关性。采用受试者工作特征曲线（ROC）分析和 10 折交叉验证分别探讨和验证 DFF 在糖尿病分类中的性能。
与 T2DM 患者相比，LADA 患者的平均血糖更高（<0.001），TIR 更低，SD、MAGE 和 CV 更大（<0.001）。与 TIR（r=0.485，<0.001）、平均血糖（r=-0.337，<0.001）、SD（r=-0.645，<0.001）、MAGE（r=-0.663，<0.001）和 CV（r=-0.639，<0.001）相比，DFF 与 FCP 相关性最强（r=-0.705，<0.001）。ROC 分析显示，与 TIR、平均血糖、SD、MAGE 和 CV 相比，DFF 在区分 LADA 与 T2DM 方面的曲线下面积（AUC）最大（AUC：0.862，敏感度：71.2%，特异性：84.9%）（AUC：0.722，0.650，0.800，0.820 和 0.807，敏感度：71.8%，47.9%，63.6%，72.7%和 78.8%，特异性：67.8%，83.6%，80.9%，80.3%和 72.4%）。Kappa 检验表明 DFF 与实际诊断具有较好的一致性（kappa=0.551，<0.001）。10 折交叉验证显示 DFF 在 10 个训练集中的平均 AUC 为 0.863（敏感度：78.8%，特异性：77.8%），在 10 个测试集中的平均 AUC 为 0.866（敏感度：80.9%，特异性：84.1%），表现稳定。
与 T2DM 患者相比，LADA 患者的血糖波动模式更为剧烈。我们首次提出 DFF 在区分本研究人群中 LADA 与 T2DM 患者方面可能发挥作用，有助于糖尿病的分类。
