Cátedras CONACYT (Consejo Nacional de Ciencia y Tecnología, México), Mexico; Departamento de Ingeniería Eléctrica, Universidad Autónoma Metropolitana, Unidad Iztapalapa, Mexico.
Departamento de Ingeniería Eléctrica, Universidad Autónoma Metropolitana, Unidad Iztapalapa, Mexico.
Endocrinol Diabetes Nutr (Engl Ed). 2020 May;67(5):333-341. doi: 10.1016/j.endinu.2019.08.006. Epub 2019 Nov 30.
It is estimated that 37% of Mexican adults have undiagnosed diabetes, and are therefore at high risk of developing the severe and devastating complications associated to it. In recent years, a variety of screening tools based on the characteristics of the adult Mexican population have been proposed in order to reduce the negative effects of the disease.
To assess the performance of screening models to diagnose diabetes in the Mexican adult population and to propose a screening model based on HbA1c measurements.
Data from the 2016 Halfway National Health and Nutrition Survey (NHNS) were used to assess the screening models and to develop and validate the proposed 2016 NHNS model, built using a multivariate logistic regression model. Explanatory variables included in the 2016 NHNS 2016 model were selected through a stepwise backward procedure, using sensitivity and specificity as performance indicators.
Of the screening models assessed, only the model based on the 2006 NHNS survey showed a performance consistent with previous reports. The proposed 2016 NHNS model included age, waist circumference, and systolic blood pressure as explanatory variables and showed a sensitivity of 0.72 and a specificity of 0.80 in the validation data set.
Age, waist circumference, and systolic blood pressure are variables of special importance for early detection of undiagnosed diabetes in Mexican adults. Based on the consistent performance of the 2006 NHNS model in different data sets, its use as a screening tool for adults with undiagnosed diabetes in Mexico is recommended.
据估计，37%的墨西哥成年人患有未确诊的糖尿病，因此他们面临着严重且破坏性的并发症的高风险。近年来，为了降低该疾病的负面影响，已经提出了各种基于墨西哥成年人特征的筛查工具。
评估用于诊断墨西哥成年人群中糖尿病的筛查模型的性能，并提出一种基于糖化血红蛋白测量的筛查模型。
使用 2016 年 halfway 全国健康和营养调查（NHNS）的数据来评估筛查模型，并开发和验证所提出的 2016 NHNS 模型，该模型使用多变量逻辑回归模型构建。纳入 2016 NHNS 2016 模型的解释变量是通过逐步向后程序选择的，使用敏感性和特异性作为性能指标。
在所评估的筛查模型中，只有基于 2006 NHNS 调查的模型显示出与先前报告一致的性能。所提出的 2016 NHNS 模型包括年龄、腰围和收缩压作为解释变量，在验证数据集的敏感性为 0.72，特异性为 0.80。
年龄、腰围和收缩压是墨西哥成年人早期发现未确诊糖尿病的特殊重要变量。基于 2006 NHNS 模型在不同数据集的一致性能，建议将其用作墨西哥未确诊糖尿病成人的筛查工具。
