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33 ANTHROPOMETRIC CHARTS FOR ACHONDROPLASIA AND OTHER SKELETAL DYSPLASIAS.
  1. J. E. Hoover-Fong1,2,
  2. J. McGready1,3,
  3. K. J. Schulze1,3,
  4. H. Barnes2,
  5. C. I. Scott4
  1. 1Johns Hopkins University, Baltimore, MD
  2. 2McKusick-Nathans Institute of Genetic Medicine, Greenberg Center for Skeletal Dysplasias
  3. 3Bloomberg School of Public Health, Baltimore, MD
  4. 4AI DuPont Hospital for Children, Wilmington, DE

Abstract

Accurate assessment of growth parameters in skeletal dysplasia patients is problematic with current growth curves. Most were constructed from a relatively small number of patients with a paucity of longitudinal data, from multiple clinical settings, using potentially nonstandardized observational methods. Furthermore, the curves were derived from very basic parametric analysis. Of clinical significance, weight-for-age norms are currently unavailable, despite significant negative orthopedic, neurologic, and general health sequelae caused by unrecognized and untreated obesity in the short-stature population. We have collected extensive, longitudinal anthropometric data from medical records of patients with a variety of skeletal dysplasias including achondroplasia, hypochondroplasia, spondyloepiphyseal dysplasia congenita, diastrophic dysplasia, Morquio syndrome, Kniest and metatropic dysplasia. Parameters extracted include weight, length/height, head circumference, upper and lower segments, arm span, chest circumference, inner and outer canthal distance, hand and middle digit length, gender, age, and gestational age. The primary data presented here were from subjects with achondroplasia (n = 334), the most common short-stature skeletal dysplasia, with Å2,000 data points for height, weight, and head circumference. Age-specific percentiles (5, 25, 50, 75, and 95th) for all parameters were estimated separately for males and females over 0-36 months and 2-20 years, corresponding to the CDC growth curve format for average stature individuals. A 6-month wide “moving window” (± 3 months from age of interest) was used to estimate all age-specific percentiles. Percentiles were then smoothed using a quadratic penalized smoother, with degrees of freedom and smoothing parameter estimated by a semiparametric model approach. The magnitude and longitudinal nature of this retrospective, single-observer cohort study improve the precision of the percentile estimates as compared to all previous studies. Most importantly, novel weight for age charts for patients with achondroplasia are now available for clinical use. This methodology may be easily applied to other confirmed, nonskeletal dysplasia diagnoses to assess growth in these disorders.

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