ISSN: 1308-5727 | E-ISSN: 1308-5735
Volume : 13 Issue : 2 Year : 2024
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Turkish Society for Pediatric Endocrinology and Diabetes
Important Tools for Use by Pediatric Endocrinologists in the Assessment of Short Stature [J Clin Res Pediatr Endocrinol]
J Clin Res Pediatr Endocrinol. 2021; 13(2): 124-135 | DOI: 10.4274/jcrpe.galenos.2020.2020.0206

Important Tools for Use by Pediatric Endocrinologists in the Assessment of Short Stature

José I. Labarta1, Michael B. Ranke2, Mohamad Maghnie3, David Martin4, Laura Guazzarotti5, Roland Pfäffle6, Ekaterina Koledova7, Jan M. Wit8
1University of Zaragoza, Children’s Hospital Miguel Servet, Instituto de Investigación Sanitaria de Aragón, Unit of Endocrinology, Zaragoza, Spain
2University of Tübingen, Children’s Hospital, Clinic of Pediatric Endocrinology, Tübingen, Germany
3University of Genova, Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Genova, Italy & IRCCS Instituto Giannina Gaslini, Department of Pediatrics, Genova, Italy
4University of Witten/Herdecke and Tübingen University, Tübingen, Germany
5University of Milan, Luigi Sacco Hospital, Clinic of Pediatric, Milan, Italy
6University of Leipzig, Department of Pediatrics, Leipzig, Germany
7Global Medical Affairs, Merck KGaA, Darmstadt, Germany
8Leiden University Medical Centre, Department of Paediatrics, Leiden, Netherlands

Assessment and management of children with growth failure has improved greatly over recent years. However, there remains a strong potential for further improvements by using novel digital techniques. A panel of experts discussed developments in digitalization of a number of important tools used by pediatric endocrinologists at the third 360° European Meeting on Growth and Endocrine Disorders, funded by Merck KGaA, Germany, and this review is based on those discussions. It was reported that electronic monitoring and new algorithms have been devised that are providing more sensitive referral for short stature. In addition, computer programs have improved ways in which diagnoses are coded for use by various groups including healthcare providers and government health systems. Innovative cranial imaging techniques have been devised that are considered safer than using gadolinium contrast agents and are also more sensitive and accurate. Deep-learning neural networks are changing the way that bone age and bone health are assessed, which are more objective than standard methodologies. Models for prediction of growth response to growth hormone (GH) treatment are being improved by applying novel artificial intelligence methods that can identify non-linear and linear factors that relate to response, providing more accurate predictions. Determination and interpretation of insulin-like growth factor-1 (IGF-1) levels are becoming more standardized and consistent, for evaluation across different patient groups, and computer-learning models indicate that baseline IGF-1 standard deviation score is among the most important indicators of GH therapy response. While physicians involved in child growth and treatment of disorders resulting in growth failure need to be aware of, and keep abreast of, these latest developments, treatment decisions and management should continue to be based on clinical decisions. New digital technologies and advancements in the field should be aimed at improving clinical decisions, making greater standardization of assessment and facilitating patient-centered approaches.

Keywords: Short stature, height monitoring, bone age, cranial imaging, growth hormone treatment, prediction models

José I. Labarta, Michael B. Ranke, Mohamad Maghnie, David Martin, Laura Guazzarotti, Roland Pfäffle, Ekaterina Koledova, Jan M. Wit. Important Tools for Use by Pediatric Endocrinologists in the Assessment of Short Stature. J Clin Res Pediatr Endocrinol. 2021; 13(2): 124-135
Manuscript Language: English
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