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  • Title: Weight loss thresholds to detect early hypernatremia in newborns.
    Author: Ferrández-González M, Bosch-Giménez V, López-Lozano J, Moreno-López N, Palazón-Bru A, Cortés-Castell E.
    Journal: J Pediatr (Rio J); 2019; 95(6):689-695. PubMed ID: 30030986.
    Abstract:
    OBJECTIVE: The literature indicates a single universal cut-off point for weight loss after birth for the risk of hypernatremia, without considering other factors. The aim of this study was to construct and internally validate cut-off points for the percentage weight loss associated with the risk of hypernatremia, taking into account risk factors. METHODS: A prospective study with a three-day follow-up was conducted in 165 neonates with a gestational age ≥35 weeks. The main outcome variable was mild or moderate hypernatremia (serum sodium≥145mmol/L). Secondary variables (risk factors) were maternal and infant variables. A multivariate logistic regression model was constructed to predict hypernatremia, obtaining its probability and the optimal discriminant cut-off point for hypernatremia (receiver operating characteristic analysis). Based on this point, threshold weight loss values were obtained according to the other variables. These values were internally validated by bootstrapping. RESULTS: There were 51 cases (30.9%) of hypernatremia. The mean percentage weight loss for hypernatremic infants was 8.6% and 6.0% for the rest. Associated variables in the multivariate model included greater weight loss, male gender, higher education level, multiparity, and cesarean delivery. The model had an area under the receiver operating characteristic curve of 0.84 (sensitivity=77.6%; specificity=73.2%). Similar values were obtained in the bootstrapping validation. The lowest percentage weight loss was 4.77%, for cesarean delivery in male infants of mothers with a higher education level. CONCLUSIONS: The weight loss percentage values depended on the type of delivery, parity, newborn gender, and level of maternal education. External studies are required to validate these values.
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