Weight loss thresholds to detect early hypernatremia in newborns / Limites de perda de peso para detecção de hipernatremia precoce em recém-nascidos

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 ≥ 145 mmol/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.

RESUMO Objetivo: A literatura indica um único ponto de corte universal na perda de peso após o nascimento para risco de hipernatremia, sem considerar outros fatores. Nosso objetivo foi criar e validar internamente pontos de corte para o percentual de perda de peso associado ao risco de hipernatremia considerando fatores de risco. Métodos: Foi feito um estudo prospectivo que incluiu 165 neonatos com idade gestacional ≥ 35 semanas, acompanhados por três dias. A principal variável de resultado foi hipernatremia leve ou moderada (sódio sérico ≥ 145 mmol/L). As variáveis secundárias (fatores de risco) foram variáveis maternas e dos neonatos. Um modelo multivariado de regressão logística foi criado para diagnosticar hipernatremia, obteve sua probabilidade e o ponto de corte discriminativo ideal para hipernatremia (análise da Característica de Operação do Receptor). Com base nesse ponto, obtivemos então os valores limites de perda de peso de acordo com as outras variáveis. Esses valores foram internamente validados por. Resultados: Há 51 casos (30,9%) de hipernatremia. O percentual de perda de peso para neonatos hipernatrêmicos foi 8,6% e 6,0% para o restante. As variáveis associadas no modelo multivariado incluíram maior perda de peso, sexo masculino, maior nível de escolaridade, multiparidade e cesárea. O modelo apresentou uma área sob a curva da Característica de Operação do Receptor de 0,84 (sensibilidade = 77,6%; especificidade = 73,2%). Valores semelhantes foram obtidos na validação da bootstrapping. O menor percentual de perda de peso foi 4,77% para cesárea em neonatos do sexo masculino de mães com maior nível de escolaridade. Conclusões: Os valores percentuais de perda de peso dependem do tipo de parto, paridade, sexo do recém-nascido e nível de escolaridade materna. São necessários estudos externos para validar esses valores.

Weight loss thresholds to detect early hypernatremia in newborns.

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.

Six simple questions to detect malnutrition or malnutrition risk in elderly women.

UNLABELLED: Of the numerous instruments available to detect nutritional risk, the most widely used is the Mini Nutritional Assessment (MNA), but it takes 15-20 min to complete and its systematic administration in primary care units is not feasible in practice. We developed a tool to evaluate malnutrition risk that can be completed more rapidly using just clinical variables. Between 2008 and 2013, we conducted a cross-sectional study of 418 women aged ≥60 years from Mexico. Our outcome was positive MNA and our secondary variables included were: physical activity, diabetes mellitus, hypertension, educational level, dentition, psychological problems, living arrangements, history of falls, age and the number of tablets taken daily. The sample was divided randomly into two groups: construction and validation. Construction: a risk table was constructed to estimate the likelihood of the outcome, and risk groups were formed. VALIDATION: the area under the ROC curve (AUC) was calculated and we compared the expected and the observed outcomes. The following risk factors were identified: physical activity, hypertension, diabetes, dentition, psychological problems and living with the family. The AUC was 0.77 (95% CI [0.68-0.86], p < 0.001). No differences were found between the expected and the observed outcomes (p = 0.902). This study presents a new malnutrition screening test for use in elderly women. The test is based on six very simple, quick and easy-to-evaluate questions, enabling the MNA to be reserved for confirmation. However, it should be used with caution until validation studies have been performed in other geographical areas.