Which chart and which cut-point: deciding on the INTERGROWTH, World Health Organization, or Hadlock fetal growth chart

Abstract

Objective To determine how various centile cut points on the INTERGROWTH-21st (INTERGROWTH), World Health Organization (WHO), and Hadlock fetal growth charts predict perinatal morbidity/mortality, and how this relates to choosing a fetal growth chart for clinical use. Methods We linked antenatal ultrasound measurements for fetuses > 28 weeks’ gestation from the British Columbia Women’s hospital ultrasound unit with the provincial perinatal database. We estimated the risk of perinatal morbidity/mortality (decreased cord pH, neonatal seizures, hypoglycemia, and perinatal death) associated with select centiles on each fetal growth chart (the 3rd, 10th, the centile identifying 10% of the population, and the optimal cut-point by Youden’s Index), and determined how well each centile predicted perinatal morbidity/mortality. Results Among 10,366 pregnancies, the 10th centile cut-point had a sensitivity of 11% (95% CI 8, 14), 13% (95% CI 10, 16), and 12% (95% CI 10, 16), to detect fetuses with perinatal morbidity/mortality on the INTERGROWTH, WHO, and Hadlock charts, respectively. All charts performed similarly in predicting perinatal morbidity/mortality (area under the curve [AUC] =0.54 for all three charts). The statistically optimal cut-points were the 39th, 31st, and 32nd centiles on the INTERGROWTH, WHO, and Hadlock charts respectively. Conclusion The INTERGROWTH, WHO, and Hadlock fetal growth charts performed similarly in predicting perinatal morbidity/mortality, even when evaluating multiple cut points. Deciding which cut-point and chart to use may be guided by other considerations such as impact on workflow and how the chart was derived.

The clinical performance and population health impact of birth weight-for-gestational age indices with regard to adverse neonatal outcomes in term infants

“…Theoretically, such diagnoses could be used as inputs for improving obstetric and neonatal management in conjunction with other markers and pregnancy complications. However, as previous studies have shown 14,15,[23][24][25][26]36 and our study confirms, SGA or LGA diagnosis, when used in isolation without other predictors, performs poorly for predicting SNMM; in other words, the probability of SNMM (or neonatal death) is not materially changed by such a diagnosis. In our study, the expected risk of SNMM changed marginally from 20.2 per 1,000 live births to 23.8, 36.1 and 54.4 per 1,000 live births using a mild (10% increase in odds), moderate (50%) or extreme (100%) definition of SGA among female singletons at 39 weeks' gestation (Table 1).…”

“…Although the newly created normative/prescriptive Intergrowth 21 st Project and World Health Organization (WHO) birth weight-for-gestational age standards 1-4 represent a conceptual departure from previous descriptive, population-based references 5-11 and offer several theoretical advantages, studies comparing existing references and the new standards have not succeeded in establishing a preferred method for identifying SGA and LGA infants. 12-26…”

“…Although the newly created normative/prescriptive Intergrowth 21 st Project and World Health Organization (WHO) birth weight-for-gestational age standards [1][2][3][4] represent a conceptual departure from previous descriptive, population-based references [5][6][7][8][9][10][11] and offer several theoretical advantages, studies comparing existing references and the new standards have not succeeded in establishing a preferred method for identifying SGA and LGA infants. [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26] One study, 22 which contrasted the Intergrowth standard with population-based references from 15 European countries, showed that infants classified as AGA by the Intergrowth standard and SGA by the 15 national references had a 2.7-fold higher risk of perinatal death (compared with infants deemed AGA by both). Conversely, infants categorized as LGA by the Intergrowth standard but AGA by the national references were at significantly reduced risk of perinatal death.…”

Desempeño predictivo de los criterios diagnósticos de restricción de crecimiento fetal para resultados adversos perinatales en un hospital de Popayán, Colombia

“…Los resultados presentados en cuanto a la capacidad predictiva son similares a la publicación de Molina et al 12 , quienes en un análisis secundario de un estudio prospectivo realizaron una validación de los criterios del consenso Delphi comparándolo con la definición de RCF de SMMF/ACOG, encontrando que ninguno de los dos criterios aporta un AUC aceptable para predicción de RANC: 0,50 (IC 95 %: 0,48-0,53) y 0,53 (IC 95 %: 0,50-0,55) para SMMF/ACOG y consenso Delphi. Resultados, a su vez, consistentes con los encontrados por Liauw et al 16 ; AUC: 0,54 para predicción de RANC con fetos menores al percentil 10 de crecimiento. Por otra parte, los hallazgos de baja sensibilidad para predicción de RANC encontrados en el presente estudio son similares a los informados por Roeckner et al 17 , con una sensibilidad de 15,1 % y de 10,1 % para SMMF/ACOG y consenso Delphi, respectivamente.…”

Complicaciones De Preeclampsia: Actualización

“…En una investigación en la que se compara pre maturidad y RCIU en mujeres con eclampsia y mujeres con síndrome HELLP, se encontró 66,6% de prematuridad en síndrome HELLP vs 0% en eclampsia y RCIU con per centil menor de 3 %, en eclampsia 16,7% vs 26,6% en síndrome HELLP; además muerte perinatal en 11,1% de síndrome HELLP vs 0 % en eclampsia [109]. [110,111].…”