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

Özet

Assessment and management of children with growth failure has improved greatly over recent years. However, there remains a strongpotential for further improvements by using novel digital techniques. A panel of experts discussed developments in digitalization of anumber 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 newalgorithms have been devised that are providing more sensitive referral for short stature. In addition, computer programs have improvedways in which diagnoses are coded for use by various groups including healthcare providers and government health systems. Innovativecranial imaging techniques have been devised that are considered safer than using gadolinium contrast agents and are also moresensitive and accurate. Deep-learning neural networks are changing the way that bone age and bone health are assessed, which are moreobjective than standard methodologies. Models for prediction of growth response to growth hormone (GH) treatment are being improvedby applying novel artificial intelligence methods that can identify non-linear and linear factors that relate to response, providing moreaccurate predictions. Determination and interpretation of insulin-like growth factor-1 (IGF-1) levels are becoming more standardizedand consistent, for evaluation across different patient groups, and computer-learning models indicate that baseline IGF-1 standarddeviation score is among the most important indicators of GH therapy response. While physicians involved in child growth and treatmentof disorders resulting in growth failure need to be aware of, and keep abreast of, these latest developments, treatment decisions andmanagement should continue to be based on clinical decisions. New digital technologies and advancements in the field should be aimedat improving clinical decisions, making greater standardization of assessment and facilitating patient-centered approaches.