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Neonatal Morbidity Associated with Shoulder Dystocia Maneuvers Conclusions These models display potential for further development and evaluation in LMICs to detect infants in need of further nutritional management, especially where traditional methods of risk management such as birthweight for gestational age percentiles may be variable
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We applied a sex-specific approach to anthropometric estimation of neonatal fat mass, demonstrating the influence of the testing sample size on the final model performance. Birthweight percentiles could also identify low and high BF% neonates with AUCs of 0.792 (0.74, 0.85) and 0.834 (0.79, 0.88). For identifying composite morbidity, BF% as measured via air displacement plethysmography showed strong predictive ability (AUC 0.786 (0.70, 0.88)), while birthweight percentiles had a lower AUC (0.695 (0.57, 0.82)). The greatest area under receiver-operator characteristic curves (AUC with 95% confidence intervals (CI)) for identifying composite morbidity was 0.740 (0.63, 0.85), resulting from the combination of birthweight, length, chest and mid-thigh circumferences. Results We fitted logistic regression models combining up to four anthropometric variables to predict composite morbidity and low and high BF% neonates. We then developed linear regression models for the estimation of neonatal fat mass as an assessment of body composition and nutritional status. We first adopted a logistic regression approach to screen for a composite neonatal morbidity, low and high body fat (BF%) infants. Methods We developed a range of models to aid in identifying neonates at risk of malnutrition. Anthropometry continues to play a major role in characterising growth and nutritional status. Jeffery, Heather E.īackground With the greatest burden of infant undernutrition and morbidity in low and middle income countries (LMICs), there is a need for suitable approaches to monitor infants in a simple, low-cost and effective manner. An anthropometric approach to characterising neonatal morbidity and body composition, using air displacement plethysmography as a criterion methodĬarberry, Angela E.