Near-Adult Heights and Adult Height Predictions Using Automated and Conventional Greulich–Pyle Bone Age Determinations in Children with Chronic Endocrine Diseases
Objectives To validate adult height predictions (BX) using automated and Greulich–Pyle bone age determinations in children with chronic endocrine diseases. Methods Heights and near-adult heights were measured in 82 patients (48 females) with chronic endocrinopathies at the age of 10.45 ± 2.12 y and...
Saved in:
Published in | Indian journal of pediatrics Vol. 89; no. 7; pp. 692 - 698 |
---|---|
Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
New Delhi
Springer India
01.07.2022
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Objectives
To validate adult height predictions (BX) using automated and Greulich–Pyle bone age determinations in children with chronic endocrine diseases.
Methods
Heights and near-adult heights were measured in 82 patients (48 females) with chronic endocrinopathies at the age of 10.45 ± 2.12 y and at time of transition to adult care (17.98 ± 3.02 y). Further, bone age (BA) was assessed using the conventional Greulich–Pyle (GP) method by three experts, and by BoneXpert™. PAH were calculated using conventional BP tables and BoneXpert™.
Results
The conventional and the automated BA determinations revealed a mean difference of 0.25 ± 0.72 y (
p
= 0.0027). The automated PAH by BoneXpert™ were 156.26 ± 0.86 cm (SDS − 2.01 ± 1.07) in females and 171.75 ± 1.6 cm (SDS − 1.29 ± 1.06) in males, compared to 153.95 ± 1.12 cm (SDS − 2.56 ± 1.5) in females and 169.31 ± 1.6 cm (SDS − 1.66 ± 1.56) in males by conventional BP, respectively and in comparison to near-adult heights 156.38 ± 5.84 cm (SDS − 1.91 ± 1.15) in females and 168.94 ± 8.18 cm (SDS − 1.72 ± 1.22) in males, respectively.
Conclusion
BA ratings and adult height predictions by BoneXpert™ in children with chronic endocrinopathies abolish rater-dependent variability and enhance reproducibility of estimates thereby refining care in growth disorders. Conventional methods may outperform automated analyses in specific cases. |
---|---|
Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0019-5456 0973-7693 |
DOI: | 10.1007/s12098-021-04009-8 |