Cargando…

A Weight Estimation Strategy for Preterm and Full-Term Infants

Weight is the foremost marker of health outcomes in infants; however, the majority of community workers and health care providers in remote, resource-constrained settings have limited access to functional scales. This study develops and validates a simple weight estimation strategy for infants that...

Descripción completa

Detalles Bibliográficos
Autores principales: Abdel-Rahman, Susan M., Paul, Ian M., Delmore, Paula, James, Laura, Fearn, Laura, Atz, Andrew, Poindexter, Brenda, Al-Uzri, Amira, Lewandowski, Andrew, Harper, Barrie, Smith, P. Brian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751918/
https://www.ncbi.nlm.nih.gov/pubmed/29308426
http://dx.doi.org/10.1177/2333794X17748775
Descripción
Sumario:Weight is the foremost marker of health outcomes in infants; however, the majority of community workers and health care providers in remote, resource-constrained settings have limited access to functional scales. This study develops and validates a simple weight estimation strategy for infants that addresses the limitations of current approaches. Circumferential and segmental anthropometric measures were evaluated for their relationship to infant weight and length. Data derived from 2097 US infants (n = 1681 for model development, n = 416 for validation). Statistical and practical considerations informed final measurement selection. Head circumference and chest circumference demonstrated the best correlations with weight (r = 0.89) and length (r = 0.94 and 0.93), and were among the most reproducible as reflected by intraclass correlation coefficients (>0.98). The head circumference and chest circumference combination offered better goodness-of-fit and smaller limits of agreement than did either measure alone. The final model predicted weight within 10% and 15% of actual for 84% and 94% of infants, respectively, with no bias for postnatal age (P = .76), gestational age (P = .10), and sex (P = .25). The model requires simple summation to generate a weight estimate and can be embodied as a low-cost, paper-based device.