Nutritional Status of Children with Short Stature Is Oppositely Associated with Growth Hormone Peak in Stimulation Tests and Insulin-like Growth Factor-1 Concentration

Background/Objectives: A blunted growth hormone (GH) response in stimulation tests (GHSTs) in obese patients is well documented, with less evidence for insulin-like growth factor-1 (IGF-1) concentrations. The aim of this study was to assess the relationships between nutritional status, GH peak in GHST, and IGF-1 concentrations, and to develop machine learning prediction models of GH deficiency (GHD) in children with short stature. Methods: A case–control study included 1592 children with short stature, whose height, weight, body mass index (BMI), GH peak in two GHSTs, IGF-1 concentration and bone age (BA) were assessed. The cut-off of GH peak in two GHSTs between GHD and idiopathic short stature (ISS) was 10.0 µg/L; additionally, a lower cut-off of 7.0 µg/L was used in repeated analysis. Univariate statistical analyses and classification models were used to identify variables related to the normal and subnormal results of GHST. Results: Depending on the cut-off of GH peak (10.0 vs. 7.0 µg/L), GHD was diagnosed in 604 vs. 279 patients (37.9% vs. 17.5%). Children with GHD had significantly lower (p < 0.001) BMI SDS and IGF-1 SDS than ones with ISS for both cut-offs of GH peak. Overnutrition was associated with the lowest GH peak but the highest IGF-1 SDS; the opposite results were observed in undernutrition. A decision tree predicted GHD in 156 patients, in 149 based on BMI SDS > 0.91. A Naïve Bayes classifier predicted GHD in 118 cases, with BMI SDS and IGF-1 SDS being the only significant variables. The best multilayer perceptron (MLP) neural network predicted GHD in 310 patients, while a logistic regression model did so in 269 patients. Conclusions: Interpretation of GHST should include the patient’s nutritional status in order to avoid overdiagnosis of GHD in overweight and obese children.