Publication: Utilidad de un nuevo modelo de curvas personalizadas de peso fetal y neonatal
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2022-05-10
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Universidad Complutense de Madrid
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Abstract
OBJETIVO: El objetivo del estudio fue construir un nuevo modelo de curvas personalizadas(CC), considerando la delgadez y la obesidad materna como enfermedad y por tanto como causa de exclusión de los cálculos, y valorar su eficacia para identificara los fetos y recién nacidos pequeños y grandes para la edad gestacional (PEG y GEG) con resultados perinatales adversos, comparándola con la de los modelos de CC convencionales. MATERIAL Y MÉTODOS: Para construir el nuevo modelo de CC se valoraron 20331 gestaciones asistidas en el Hospital Universitario Materno Infantil de Canarias. Además de considerar como criterio de exclusión, de la muestra utilizada para los cálculos del modelo de curvas de peso fetal, la patología materna asociada, la inducida por el embarazo y la fetal, se consideraron enfermedad la delgadez y la obesidad materna de la gestante al inicio del embarazo (índice de masa corporal (IMC) < 18.5 o > 25 kg/m2). La muestra final quedó constituida por 11604 gestantes. Una vez construido el nuevo modelo de CC(18.5-25), se validó internamente, utilizándolo para clasificar por pesos a los recién nacidos incluidos en la totalidad de la muestra. Los resultados perinatales de los grupos de neonatos identificados como AEG, GEG y PEG se compararon con los obtenidos al clasificarlos por pesos según el modelo convencional de CC. La validación externa de las CC(18.5-25) se realizó comparando la eficacia de los modelos para identificar a los recién nacidos AEG, GEG y PEG con riesgo de resultados perinatales adversos en una muestra de 14740 gestantes asistidas en el Hospital Universitario Vall d´Hebrón...
AIM: The aim of the study was determine if customized fetal growth charts developed, excluding obese and underweight mothers (CC(18.5-25)) , are better than customized curves (CC) at identifying small and large fetuses (PEG and GEG) at risk of perinatal morbidity, compared with conventional customized charts. MATERIAL AND METHODS: Data from 20331 infants was used to construct conventional CC and from 11604 for CC(18.5-25), after excluding the cases with abnormal maternal body mass index (BMI), <18.5 and >25 . After building the new CC(18.5-25), it was internally validated, using it to classify newborns included in the sample by weight as SGA (small for gestational age), LGA (large for gestational age) and AGA (appropriate for gestational age) and the perinatal outcomes were compared between LGA or SGA according to each model. In the external validation of the CC (18.5-25), the efficacy of both models for diagnosing AGA, PEG and SGA newborns at risk of adverse perinatal outcomes was compared in a sample of 14740 pregnant women from the Vall d´Hebrón University Hospital. Logistic regression was used to calculate the OR of outcomes by group, taking as reference group AGA7L 73MN 99 (OR=1), and with gestational age as covariable. The confidence intervals of pH were calculated by analysis of covariance...
AIM: The aim of the study was determine if customized fetal growth charts developed, excluding obese and underweight mothers (CC(18.5-25)) , are better than customized curves (CC) at identifying small and large fetuses (PEG and GEG) at risk of perinatal morbidity, compared with conventional customized charts. MATERIAL AND METHODS: Data from 20331 infants was used to construct conventional CC and from 11604 for CC(18.5-25), after excluding the cases with abnormal maternal body mass index (BMI), <18.5 and >25 . After building the new CC(18.5-25), it was internally validated, using it to classify newborns included in the sample by weight as SGA (small for gestational age), LGA (large for gestational age) and AGA (appropriate for gestational age) and the perinatal outcomes were compared between LGA or SGA according to each model. In the external validation of the CC (18.5-25), the efficacy of both models for diagnosing AGA, PEG and SGA newborns at risk of adverse perinatal outcomes was compared in a sample of 14740 pregnant women from the Vall d´Hebrón University Hospital. Logistic regression was used to calculate the OR of outcomes by group, taking as reference group AGA7L 73MN 99 (OR=1), and with gestational age as covariable. The confidence intervals of pH were calculated by analysis of covariance...
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Tesis inédita de la Universidad Complutense de Madrid, Facultad de Medicina, leída el 11-02-2022