Literature DB >> 25862023

Validation of automated Greulich-Pyle bone age determination in children with chronic renal failure?

Saritha Ranabothu1, Frederick J Kaskel.   

Abstract

Growth failure is a common problem in children with chronic kidney disease (CKD). The causes are multifactorial and are associated with increased mortality and morbidity. Standard deviations of bone age versus chronological age in children with CKD have not been developed to date. Accurate and early treatment of bone age is an important component of determining the utility of GH therapy. Improvements in bone age assessments are being evaluated to optimize the understanding of growth delay in CKD.

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Year:  2015        PMID: 25862023     DOI: 10.1007/s00467-015-3103-9

Source DB:  PubMed          Journal:  Pediatr Nephrol        ISSN: 0931-041X            Impact factor:   3.714


  11 in total

1.  K/DOQI clinical practice guidelines for bone metabolism and disease in chronic kidney disease.

Authors: 
Journal:  Am J Kidney Dis       Date:  2003-10       Impact factor: 8.860

2.  Clinical application of automated Greulich-Pyle bone age determination in children with short stature.

Authors:  David D Martin; Dorothee Deusch; Roland Schweizer; Gerhard Binder; Hans Henrik Thodberg; Michael B Ranke
Journal:  Pediatr Radiol       Date:  2009-03-31

Review 3.  Are the new automated methods for bone age estimation advantageous over the manual approaches?

Authors:  Vincenzo De Sanctis; Ashraf T Soliman; Salvatore Di Maio; Said Bedair
Journal:  Pediatr Endocrinol Rev       Date:  2014-12

4.  Automated Greulich-Pyle bone age determination in children with chronic kidney disease.

Authors:  Eva Nüsken; Darja Imschinetzki; Kai-Dietrich Nüsken; Friederike Körber; Hans-Joachim Mentzel; Joachim Peitz; Martin Bald; Rainer Büscher; Ulrike John; Günter Klaus; Martin Konrad; Lars Pape; Burkhard Tönshoff; David Martin; Lutz Weber; Jörg Dötsch
Journal:  Pediatr Nephrol       Date:  2015-03-19       Impact factor: 3.714

5.  Automation of bone age reading and a new prediction model improve adult height prediction in children with short stature.

Authors:  Marina Unrath; Hans Henrik Thodberg; Roland Schweizer; Michael B Ranke; Gerhard Binder; David D Martin
Journal:  Horm Res Paediatr       Date:  2013-01-05       Impact factor: 2.852

6.  Bone age assessment of children using a digital hand atlas.

Authors:  Arkadiusz Gertych; Aifeng Zhang; James Sayre; Sylwia Pospiech-Kurkowska; H K Huang
Journal:  Comput Med Imaging Graph       Date:  2007-03-26       Impact factor: 4.790

7.  Validation of automatic bone age determination in children with congenital adrenal hyperplasia.

Authors:  David D Martin; Katharina Heil; Conrad Heckmann; Angelika Zierl; Jürgen Schaefer; Michael B Ranke; Gerhard Binder
Journal:  Pediatr Radiol       Date:  2013-10-05

8.  Prediction of adult height based on automated determination of bone age.

Authors:  Hans Henrik Thodberg; Oskar G Jenni; Jon Caflisch; Michael B Ranke; David D Martin
Journal:  J Clin Endocrinol Metab       Date:  2009-11-19       Impact factor: 5.958

Review 9.  Clinical review: An automated method for determination of bone age.

Authors:  Hans Henrik Thodberg
Journal:  J Clin Endocrinol Metab       Date:  2009-04-28       Impact factor: 5.958

Review 10.  The consequences of chronic kidney disease on bone metabolism and growth in children.

Authors:  Justine Bacchetta; Jérôme Harambat; Pierre Cochat; Isidro B Salusky; Katherine Wesseling-Perry
Journal:  Nephrol Dial Transplant       Date:  2012-08       Impact factor: 5.992

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  2 in total

1.  Role of Medical IoT-Based Bone Age Determination in the Diagnosis and Clinical Treatment of Dwarfism Disease Monitoring.

Authors:  Shaoxia Wu
Journal:  Contrast Media Mol Imaging       Date:  2022-09-30       Impact factor: 3.009

2.  Applicability of two commonly used bone age assessment methods to twenty-first century UK children.

Authors:  Khalaf Alshamrani; Amaka C Offiah
Journal:  Eur Radiol       Date:  2019-08-01       Impact factor: 5.315

  2 in total

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