Maternal colonization with group B Streptococcus (GBS) is a risk factor for neonatal GBS disease. Whereas serotypes Ia, Ib, II, III, and V are prevalent in the United States, types VI and VIII predominate in Japan. Recently, a serotype VIII strain was detected among 114 clinical GBS isolates from a Boston, Mass., hospital.
Children born preterm, low birth weight (LBW) or with other perinatal risk factors are at high‐risk of malnutrition. Regular growth monitoring and early intervention are essential to promote optimal feeding and growth; however, monitoring growth in preterm infants can be complex. This study evaluated growth monitoring of infants under 6 months enrolled in Paediatric Development Clinics (PDCs) in rural Rwanda. We reviewed electronic medical records (EMR) of infants enrolled in PDCs before age 2 months with their first visit between January 2015 and December 2016 and followed them until age 6 months. Nurse classification of anthropometric measures and nutritional status were extracted from the EMR. Interval growth and length‐for‐age, weight‐for‐length, and weight‐for‐age z‐scores were calculated using World Health Organization anthropometry software as a ‘gold standard’ comparison to nurse classifications. Two hundred and ninety‐four patients enrolled and had 2,033 visits during the study period. Referral reasons included prematurity/LBW (73.8%) and hypoxic ischemic encephalopathy (28.2%). Nurses assessed interval growth at 58.7% of visits, length‐for‐age at 66.4%, weight‐for‐length at 65.6% and weight‐for‐age at 66.4%. Nurses and gold standard assessment agreed on interval growth at 53.3% of visits and length‐for‐age at 63.7%, weight‐for‐length at 78.2% and weight‐for‐age at 66.3%. At 6 months, 46.5% were stunted, 19.9% were wasted and 44.2% were underweight. There were significant challenges to optimizing growth and growth monitoring among high‐risk infants served by PDCs, including incomplete and inaccurate assessments. Developing tools for clinician decision support in assessing growth and providing specialized nutritional counselling are essential to supporting optimal outcomes in this population.
Background: Sufficient knowledge of the disproportionate burden of undernutrition among vulnerable children is required for accelerating undernutrition reduction in low-income countries. Objectives: We aimed to assess the prevalence of stunting, underweight and wasting and associated factors among high-risk children born preterm, with low birth weight or other birth and neurodevelopmental injuries, who received nutritional support and clinical care follow-up in a Pediatric Development Clinic (PDC) in rural Rwanda. Methods: This cross-sectional study included all children from rural areas enrolled in PDC between April 2014-September 2017 aged 6-59 months at their last visit during this period. Anthropometric measurements, socioeconomic and clinical characteristics were extracted from an electronic medical records system. We used the World Health Organization child growth standards to classify stunting, underweight and wasting. Factors associated with undernutrition were identified using logistic regression analysis. Results: Of 641 children, 58.8% were stunted, 47.5% were underweight and 25.8% were wasted. Small for gestational age was associated with increased odds of stunting [
Infants born preterm, low birthweight or with other perinatal complications require frequent and accurate growth monitoring for optimal nutrition and growth. We implemented an mHealth tool to improve growth monitoring and nutritional status assessment of high risk infants. We conducted a pre-post quasi-experimental study with a concurrent control group among infants enrolled in paediatric development clinics in two rural Rwandan districts. During the pre-intervention period (August 2017-January 2018), all clinics used standard paper-based World Health Organization (WHO) growth charts. During the intervention period (August 2018-January 2019), Kirehe district adopted an mHealth tool for child growth monitoring and nutritional status assessment. Data on length/height; weight; length/ height-for-age (L/HFA), weight-for-length/height (WFL/H) and weight-for-age (WFA) z-scores; and interval growth were tracked at each visit. We conducted a 'difference-in-difference' analysis to assess whether the mHealth tool was associated with greater improvements in completion and accuracy of nutritional assessments and nutritional status at 2 and 6 months of age. We observed 3529 visits. mHealth intervention clinics showed significantly greater improvements on completeness for corrected age (endline: 65% vs. 55%; p = 0.036), L/HFA (endline: 82% vs. 57%; p ≤ 0.001), WFA (endline: 93% vs. 67%; p ≤ 0.001) and WFL/H (endline: 90% vs. 59%; p ≤ 0.001) z-scores compared with control sites. Accuracy of growth monitoring did not improve. Prevalence of stunting, underweight and inadequate interval growth at 6-months corrected age decreased significantly more in the intervention clinics than in control clinics. Results suggest that integrating mHealth nutrition interventions is feasible and can improve child nutrition outcomes.Improved tool design may better promote accuracy.
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