Construction and validation of nomogram prediction model for ketoacidosis in elderly diabetic patients based on baseline data and glycolipid metabolism

IF 3 3区医学 Q2 ENDOCRINOLOGY & METABOLISM

Journal of Diabetes Investigation Pub Date : 2025-05-07 DOI:10.1111/jdi.70058

Aijin Niu, Jing Zhuang, Yangdi Li, Wei Wei

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Abstract

Objective

To explore the risk factors of ketoacidosis (DKA) in elderly patients with diabetes and to construct a nomogram prediction model to guide clinical practice.

Methods

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).

Results

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 χ² = 12.750, P = 0.120 and χ² = 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.

Conclusion

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.

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基于基线数据和糖脂代谢的老年糖尿病酮症酸中毒nomogram预测模型的构建与验证

目的：探讨老年糖尿病患者酮症酸中毒（DKA）的危险因素，建立nomogram预测模型，指导临床实践。方法：收集基线、糖脂代谢及相关数据。通过多因素logistic回归分析筛选危险因素，构建模型。采用受试者工作特征（ROC）曲线、校正曲线分析和决策曲线分析（DCA）评价模型的有效性。结果：Logistic回归分析显示，年龄、糖尿病病程、FBG、2hPG、HbA1c、TG、TC、C肽水平是老年糖尿病患者DKA的独立危险因素（χ2 = 12.750, P = 0.120, χ2 = 8.325, P = 0.402）。ROC曲线显示，预测老年糖尿病患者DKA发生的训练集和验证集nomogram model的AUC分别为0.866和0.879。结论：基于基线数据和糖脂代谢指标的Nomogram预测模型在训练集和验证集均具有较好的预测效率。年龄、糖尿病病程、FBG、2hPG、HbA1c、TG、TC、C肽水平是老年糖尿病患者DKA的独立危险因素。

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来源期刊

Journal of Diabetes Investigation ENDOCRINOLOGY & METABOLISM-

CiteScore

6.50

自引率

9.40%

发文量

218

审稿时长

6-12 weeks

期刊介绍： Journal of Diabetes Investigation is your core diabetes journal from Asia; the official journal of the Asian Association for the Study of Diabetes (AASD). The journal publishes original research, country reports, commentaries, reviews, mini-reviews, case reports, letters, as well as editorials and news. Embracing clinical and experimental research in diabetes and related areas, the Journal of Diabetes Investigation includes aspects of prevention, treatment, as well as molecular aspects and pathophysiology. Translational research focused on the exchange of ideas between clinicians and researchers is also welcome. Journal of Diabetes Investigation is indexed by Science Citation Index Expanded (SCIE).