Details

Autor(en) / Beteiligte

• Talib, Nasreen J.
• Rahm, Ginny
• Abdel-Rahman, Susan M.

Titel

Estimating Weight in Children With Down Syndrome

Ist Teil von

• Global pediatric health, 2015, Vol.2, p.2333794X14568450-2333794X14568450

Ort / Verlag

Los Angeles, CA: SAGE Publications

Erscheinungsjahr

2015

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• Objective. Significant attention has been paid to weight estimation in settings where scales are impractical or unavailable; however, no studies have evaluated the performance of published weight estimation methods in children with Down syndrome. This study was designed to evaluate the predictive performance of various methods in this population with well-established differences in height and weight for age. Methods. This was a prospective study of children aged 0 to 18 years with Down syndrome. Anthropometric measurements including height, weight, humeral length, and mid-upper arm circumference were collected and applied to 4 distinct weight estimation strategies based on age (APLS), length (Broselow), habitus (Cattermole), and length plus habitus (Mercy). Predictive performance was evaluated by examining residual error (RE), percentage error (PE), root mean square error (RMSE), limits of agreement, and intraclass correlation coefficients. Results. A total of 318 children distributed across age, gender, and body mass index percentile were enrolled. APLS and Mercy showed the smallest degree of bias (PE = 7.8 ± 24.5% and −3.9 ± 12.4%, respectively). Broselow suffered the most extreme underestimation (−63%), whereas the APLS suffered the greatest degree of overestimation (107%). Mercy demonstrated the highest intraclass correlation coefficient (0.987 vs 0.867-0.885) and predicted weight within 20% of actual in the largest proportion of participants (88% vs 40% to 76%). All methods were less robust in children with Down syndrome than reported for unaffected children. Conclusions. Mercy offered the best option for weight estimation in children with Down syndrome. Additional anthropometric data collected in this special population would allow investigators to refine existing weight estimation strategies specifically for these children.