Molina-Luque Rafael, Ulloa Natalia, Gleisner Andrea, Zilic Martin, Romero-Saldaña Manuel, Molina-Recio Guillermo
Grupo Asociado de Investigación Estilos de Vida, Innovación y Salud, Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), 14004 Córdoba, Spain.
Departamento de Enfermería, Farmacología y Fisioterapia, Facultad de Medicina y Enfermería, Universidad de Córdoba, 14004 Córdoba, Spain.
Children (Basel). 2020 Dec 17;7(12):304. doi: 10.3390/children7120304.
Metabolic Syndrome (MetS) has a high prevalence in children, and its presence increases in those with a high BMI. This fact confirms the need for early detection to avoid the development of other comorbidities. Non-invasive variables are presented as a cost-effective and easy to apply alternative in any clinical setting.
To propose a non-invasive method for the early diagnosis of MetS in overweight and obese Chilean children.
We conducted a cross-sectional study on 221 children aged 6 to 11 years. We carried out multivariate logistic regressions, receiver operating characteristic curves, and discriminant analysis to determine the predictive capacity of non-invasive variables. The proposed new method for early detection of MetS is based on clinical decision trees.
The prevalence of MetS was 26.7%. The area under the curve for the BMI and waist circumference was 0.827 and 0.808, respectively. Two decision trees were calculated: the first included blood pressure (≥104.5/69 mmHg), BMI (≥23.5 Kg/m) and WHtR (≥0.55); the second used BMI (≥23.5 Kg/m) and WHtR (≥0.55), with validity index of 74.7% and 80.5%, respectively.
Early detection of MetS is possible through non-invasive methods in overweight and obese children. Two models (Clinical decision trees) based on anthropometric (non-invasive) variables with acceptable validity indexes have been presented. Clinical decision trees can be applied in different clinical and non-clinical settings, adapting to the tools available, being an economical and easy to measurement option. These methods reduce the use of blood tests to those patients who require confirmation.
代谢综合征（MetS）在儿童中患病率很高，且在BMI较高的儿童中更为常见。这一事实证实了早期检测以避免其他合并症发生的必要性。无创变量在任何临床环境中都是一种具有成本效益且易于应用的替代方法。
提出一种用于早期诊断智利超重和肥胖儿童MetS的无创方法。
我们对221名6至11岁的儿童进行了横断面研究。我们进行了多变量逻辑回归、受试者工作特征曲线分析和判别分析，以确定无创变量的预测能力。所提出的早期检测MetS的新方法基于临床决策树。
MetS的患病率为26.7%。BMI和腰围的曲线下面积分别为0.827和0.808。计算了两个决策树：第一个包括血压（≥104.5/69 mmHg）、BMI（≥23.5 Kg/m²）和腰高比（WHtR，≥0.55）；第二个使用BMI（≥23.5 Kg/m²）和WHtR（≥0.55），有效性指数分别为74.7%和80.5%。
通过无创方法可以在超重和肥胖儿童中早期检测出MetS。我们提出了两种基于人体测量学（无创）变量且有效性指数可接受的模型（临床决策树）。临床决策树可应用于不同的临床和非临床环境，根据可用工具进行调整，是一种经济且易于测量的选择。这些方法减少了对需要确诊的患者进行血液检测的使用。
