Stoltenberg Carsten Wridt, Hangaard Stine, Hejlesen Ole, Kronborg Thomas, Vestergaard Peter, Jensen Morten Hasselstrøm
Aalborg University, Gistrup, Denmark.
Steno Diabetes Center North Denmark, Aalborg, Denmark.
J Diabetes Sci Technol. 2024 Sep 20:19322968241280096. doi: 10.1177/19322968241280096.
Glycemic control is crucial for people with type 2 diabetes. However, only about half achieve the advocated HbA1c target of ≤7%. Identifying those who will probably struggle to reach this target may be valuable as they require additional support. Thus, the aim of this study was to develop a model to predict people with type 2 diabetes not achieving HbA1c target after initiating fast-acting insulin.
Data from a randomized controlled trial (NCT01819129) of participants with type 2 diabetes initiating fast-acting insulin were used. Data included demographics, clinical laboratory values, self-monitored blood glucose (SMBG), health-related quality of life (SF-36), and body measurements. A logistic regression was developed to predict HbA1c target nonachievers. A potential of 196 features was input for a forward feature selection. To assess the performance, a 20-repeated stratified 5-fold cross-validation with area under the receiver operating characteristics curve (AUROC) was used.
Out of the 467 included participants, 98 (21%) did not achieve HbA1c target of ≤7%. The forward selection identified 7 features: baseline HbA1c (%), mean postprandial SMBG at all meals 3 consecutive days before baseline (mmol/L), sex, no ketones in urine, baseline albumin (g/dL), baseline low-density lipoprotein cholesterol (mmol/L), and traces of protein in urine. The model had an AUROC of 0.745 [95% CI = 0.734, 0.756].
The model was able to predict those who did not achieve HbA1c target with promising performance, potentially enabling early identification of people with type 2 diabetes who require additional support to reach glycemic control.
血糖控制对于2型糖尿病患者至关重要。然而，只有约一半的患者能达到建议的糖化血红蛋白（HbA1c）目标值≤7%。识别那些可能难以达到该目标的患者可能很有价值，因为他们需要额外的支持。因此，本研究的目的是建立一个模型，以预测2型糖尿病患者在开始使用速效胰岛素后无法达到HbA1c目标的情况。
使用一项针对开始使用速效胰岛素的2型糖尿病参与者的随机对照试验（NCT01819129）的数据。数据包括人口统计学信息、临床实验室值、自我监测血糖（SMBG）、健康相关生活质量（SF - 36）和身体测量数据。开发了一个逻辑回归模型来预测未达到HbA1c目标的患者。将196个潜在特征输入进行前向特征选择。为评估模型性能，采用了20次重复的分层5折交叉验证，并计算受试者工作特征曲线下面积（AUROC）。
在纳入的467名参与者中，98名（21%）未达到HbA1c目标值≤7%。前向选择确定了7个特征：基线HbA1c（%）、基线前连续3天所有餐次的餐后平均SMBG（mmol/L）、性别、尿中无酮体、基线白蛋白（g/dL）、基线低密度脂蛋白胆固醇（mmol/L）和尿中微量蛋白。该模型的AUROC为0.745 [95%置信区间 = 0.734, 0.756]。
该模型能够以良好的性能预测未达到HbA1c目标的患者，有可能早期识别出需要额外支持以实现血糖控制的2型糖尿病患者。
