Niu Aijin, Zhuang Jing, Li Yangdi, Wei Wei
Department of Endocrinology, Henan Provincial People's Hospital, Zhengzhou, China.
Department of Endocrinology, Zhengzhou University People's Hospital, Zhengzhou, China.
J Diabetes Investig. 2025 Jul;16(7):1338-1345. doi: 10.1111/jdi.70058. Epub 2025 May 7.
To explore the risk factors of ketoacidosis (DKA) in elderly patients with diabetes and to construct a nomogram prediction model to guide clinical practice.
Baseline, glycolipid metabolism, and related data were collected. Risk factors were screened by multifactor logistic regression analysis to construct a model. The effectiveness of the model was evaluated by Receiver Operating Characteristiv (ROC) curve, calibration curve analysis, and decision curve analysis (DCA).
Logistic regression analysis showed that age, duration of diabetes, FBG, 2hPG, HbA1c, TG, TC, and C peptide level were the independent risk factors for DKA in elderly diabetic patients (P < 0.05). The nomogram prediction model constructed based on these factors showed good prediction performance in both the training set and the verification set, with the C-index indexes being 0.880 and 0.918, respectively, and the average absolute errors of coincidence between the predicted value and the true value being 0.102 and 0.075, respectively. The results of the Hosmer-Lemeshow test were χ = 12.750, P = 0.120 and χ = 8.325, P = 0.402, respectively. The ROC curve showed that the AUC of the nomogram model in the training set and the verification set for predicting the occurrence of DKA in elderly diabetic patients was 0.866 and 0.879, respectively.
Nomogram prediction model based on baseline data and glucose and lipid metabolism indicators showed good prediction efficiency in both the training set and the verification set. Age, diabetes duration, FBG, 2hPG, HbA1c, TG, TC, and C peptide levels were independent risk factors for DKA in elderly diabetic patients.
探讨老年糖尿病患者发生糖尿病酮症酸中毒（DKA）的危险因素，并构建列线图预测模型以指导临床实践。
收集基线、糖脂代谢及相关数据。通过多因素逻辑回归分析筛选危险因素以构建模型。采用受试者操作特征（ROC）曲线、校准曲线分析和决策曲线分析（DCA）评估模型的有效性。
逻辑回归分析显示，年龄、糖尿病病程、空腹血糖（FBG）、餐后2小时血糖（2hPG）、糖化血红蛋白（HbA1c）、甘油三酯（TG）、总胆固醇（TC）及C肽水平是老年糖尿病患者发生DKA的独立危险因素（P＜0.05）。基于这些因素构建的列线图预测模型在训练集和验证集均显示出良好的预测性能，C指数分别为0.880和0.918，预测值与真实值之间的平均绝对误差符合率分别为0.102和0.075。Hosmer-Lemeshow检验结果分别为χ² = 12.750，P = 0.120和χ² = 8.325，P = 0.402。ROC曲线显示，列线图模型在训练集和验证集预测老年糖尿病患者发生DKA的曲线下面积（AUC）分别为0.866和0.879。
基于基线数据及糖脂代谢指标的列线图预测模型在训练集和验证集均显示出良好的预测效率。年龄、糖尿病病程、FBG、2hPG、HbA1c、TG、TC及C肽水平是老年糖尿病患者发生DKA的独立危险因素。
