000151697 001__ 151697
000151697 005__ 20250319155218.0
000151697 0247_ $$2doi$$a10.4274/jcrpe.galenos.2020.2020.0206
000151697 0248_ $$2sideral$$a126305
000151697 037__ $$aART-2021-126305
000151697 041__ $$aeng
000151697 100__ $$0(orcid)0000-0003-2832-2266$$aLabarta J.I.$$uUniversidad de Zaragoza
000151697 245__ $$aImportant tools for use by pediatric endocrinologists in the assessment of short stature
000151697 260__ $$c2021
000151697 5060_ $$aAccess copy available to the general public$$fUnrestricted
000151697 5203_ $$aAssessment 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.
000151697 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000151697 590__ $$a2.016$$b2021
000151697 591__ $$aPEDIATRICS$$b87 / 130 = 0.669$$c2021$$dQ3$$eT3
000151697 591__ $$aENDOCRINOLOGY & METABOLISM$$b134 / 146 = 0.918$$c2021$$dQ4$$eT3
000151697 592__ $$a0.398$$b2021
000151697 593__ $$aPediatrics, Perinatology and Child Health$$c2021$$dQ2
000151697 593__ $$aEndocrinology, Diabetes and Metabolism$$c2021$$dQ2
000151697 594__ $$a3.2$$b2021
000151697 655_4 $$ainfo:eu-repo/semantics/review$$vinfo:eu-repo/semantics/publishedVersion
000151697 700__ $$aRanke M.B.
000151697 700__ $$aMaghnie M.
000151697 700__ $$aMartin D.
000151697 700__ $$aGuazzarotti L.
000151697 700__ $$aPfäffle R.
000151697 700__ $$aKoledova E.
000151697 700__ $$aWit J.M.
000151697 7102_ $$11011$$2670$$aUniversidad de Zaragoza$$bDpto. Microb.Ped.Radio.Sal.Pú.$$cÁrea Pediatría
000151697 773__ $$g13, 2 (2021), 124-135$$pJCRPE$$tJCRPE$$x1308-5727
000151697 8564_ $$s204448$$uhttps://zaguan.unizar.es/record/151697/files/texto_completo.pdf$$yVersión publicada
000151697 8564_ $$s2683083$$uhttps://zaguan.unizar.es/record/151697/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000151697 909CO $$ooai:zaguan.unizar.es:151697$$particulos$$pdriver
000151697 951__ $$a2025-03-19-14:21:01
000151697 980__ $$aARTICLE