Novel weight estimation equation for children with cerebral palsy in low-resource settings: Validation in a population-based cohort

ISRAT JAHAN; M MERCEDES RUIZ BRUNNER; MOHAMMAD MUHI; ISKANDER HOSSAIN; EDUARDO CUESTAS; M. ELISABETH CIERI; ANA L. CONDINANZI; L. JOHANA ESCOBAR ZULUAGA; NADIA BADAWI; GULAM KHANDAKER

DEVELOPMENTAL MEDICINE AND CHILD NEUROLOGY

WILEY-BLACKWELL PUBLISHING, INC

Lugar: Londres; Año: 2023

0012-1622

AbstractAim: To validate a novel equation to estimate weight from mid-upper arm circumference (MUAC) among children with cerebral palsy (CP) in rural Bangladesh.Method: Children with CP aged 2 to 18 years registered in the Bangladesh CP Register were randomly selected. Data on sociodemographics, Gross Motor Function Classification System level, and anthropometric measurements were extracted. Bland?Altman plots with a 95% agreement limit and Lin´s concordance correlation coefficient with 95% confidence intervals (CI) were reported to measure agreement between observed and estimated weight. Percentage error was used to determinate the method´s accuracy.Results: There were 497 participants with a mean age at assessment of 9 years (SD 4 years 11months) (47.7% female). Lin´s concordance correlation coefficient between the observed and estimated weights was 0.90 (95% CI 0.89?0.92). Bland?Altman plots showed a reasonable accuracy of the equation in the study cohort. The mean percentage error of the equation was 5.04%. The average difference between observed and estimated weights was −1.02 kg (SD 5.1). The differences between observed and estimated weights were significantly greater among children with weight-for-age, height-for-age, or BMI-for-age z-scores less than or equal to −4.Interpretation: It is possible to predict the weight of children with CP from MUAC with sufficient accuracy. The equation can be used for populations in low-resources and low- and middle-income countries.