Distribution of traditional Chinese medicine constitution and construction of a risk prediction model in patients with impaired awareness of hypoglycemia
10.3760/cma.j.cn211501-20240712-01841
- VernacularTitle:低血糖意识受损患者中医体质分布及发生风险预测模型的构建
- Author:
Zhijia SHEN
1
;
Qiaoyan LIU
;
Zhijie QIAN
;
Wentao SHI
;
Limei YIN
;
Lu XU
Author Information
1. 南京中医药大学常熟附属医院内分泌科，常熟 215500
- Publication Type:Journal Article
- Keywords:
Diabetes mellitus;
Chinese traditional medicine;
Impaired awareness of hypoglycemia;
Traditional Chinese medicine constitution;
Risk prediction model
- From:
Chinese Journal of Practical Nursing
2025;41(15):1157-1167
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the distribution of Traditional Chinese Medicine constitution among patients with impaired awareness of hypoglycemia (IAH) and identify risk factors for IAH in patients with diabetes mellitus, to develop a risk prediction model. The aim is to validate the models′ predictive accuracy to facilitate early prevention and treatment of IAH.Methods:A case control study employing convenience sampling model was conducted on 1351 hospitalized patients with diabetes mellitus in the endocrinology departments of Changshu Hospital Affiliated to Nanjing University of Chinese Medicine and Affiliated Hospital of Jiangsu University, between August 2021 and December 2023. Traditional Chinese medicine constitution types were determined using the Traditional Chinese Medicine Constitution Classification and Judgment (ZYYXH/T157-2009). Data were divided into training and test sets at a ratio of 7∶3. Two prediction models were developed: Model 1, a conventional IAH prediction model for patients with diabetes mellitus, and Model 2, an IAH prediction model for patients with diabetes mellitus incorporating traditional Chinese medicine constitution. Nomograms were drawn for both models. The Hosmer-Lemeshow goodness-of-fit test, calibration curve, receiver operating characteristic (ROC) curve, and area under the curve (AUC) were calculated to evaluate the effectiveness of models 1 and 2. The improvement in prediction performance between Models 1 and 2 was assessed using Delong test, AUC, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA).Results:The study included 1 283 patients with diabetes mellitus, including 578 males and 705 females, aged (59.61 ± 14.09) years. The incidence of IAH among patients with diabetes mellitus was 20.50% (263/1283), with yang deficiency constitution being the most prevalent traditional Chinese medicine constitution type, at 47.53% (125/263). Multivariate analysis revealed that age, body mass index, course of diabetes, neurological hypoglycemia symptoms, hypoglycemia symptoms and severe hypoglycemia history were the influencing factors of Model 1 (all P<0.05); age, body mass index, neurological hypoglycemic symptoms, hypoglycemic symptoms, history of severe hypoglycemia, and traditional Chinese medicine constitution were the influencing factors of Model 2 (all P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed a good fit of Model 2 [training set ( χ2=8.48, P>0.05), test set ( χ2=3.92, P>0.05)]. The Delong test results showed that the AUC for Model 2 was 0.96 for both the training and test sets, significantly higher than the AUCs of the 0.90 and 0.91 for Model 1 ( Z=-7.27, -3.70, both P<0.01). Furthermore, NRI was 0.66 ( 95%CI 0.53-0.79, P<0.01) and IDI was 0.02 (95% CI 0.01-0.03, P<0.05) for Model 2. Comparative analysis of clinical utility demonstrated that the net benefit of Model 2 for predicting IAH in patients with diabetes mellitus surpassed that of Model 1 across threshold probabilities ranging from 5% to 100%. Conclusions:The study constructed a nomogram prediction model included traditional Chinese medicine constitution with good predictive performance for IAH in patients with diabetes mellitus, and is of significant clinical value for identifying high-risk IAH populations.IAH patients mainly have a biased constitution, indicating that medical staff can reduce the incidence of IAH by improving the patients′ constitution.
