| dc.description.abstract | Background/Objectives: Accurate identification of neonatal malnutrition is essential for
optimizing perinatal care and reducing adverse outcomes. Traditional birthweight-based
methods fail to account for body proportionality, limiting their ability to distinguish constitutionally
small or large neonates from those with true nutritional abnormalities. We
previously developed a customized fetal body mass index (cFBMI) percentile model that
incorporates both weight and length, adjusted for maternal and fetal characteristics. This
study aims to perform a temporal external validation of the cFBMI model following the
Riley et al. framework, comparing its performance against the GROW customized birthweight
model and the INTERGROWTH-21st population-based standard. Methods: A
temporal validation study was conducted using singleton deliveries from Hospital Universitario
de Puerto Real, Cádiz, Spain. The development cohort comprised 7864 deliveries
(2002–2021); the validation cohort comprised 4441 deliveries (2022–2025). Inclusion criteria:
singleton pregnancy, gestational age of 33–42 + 6 weeks, birthweight of 500–6000 g,
known neonatal sex and length, and complete maternal data. The Ponderal Index (PI =
weight/length3 × 100) stratified by sex and gestational age served as the gold standard
(undernutrition: PI < p10; overnutrition: PI > p90). Discrimination was assessed using the
area under the receiver operating characteristic curve (AUC) with bootstrap 95% confidence
intervals (2000 iterations) and DeLong tests. Calibration was evaluated by comparing
observed versus expected proportions across percentile categories. Clinical utility was
assessed using decision curve analysis (DCA). Temporal stability was quantified by comparing
AUCs and Brier scores between the development and validation cohorts. Results:
In the validation cohort (n = 4441), cFBMI demonstrated superior discrimination for both
undernutrition (AUC: 0.962) and overnutrition (AUC: 0.961) compared with GROW
(AUC: 0.751 and 0.676, respectively) and INTERGROWTH-21st (AUC: 0.756 and 0.682,
respectively); all DeLong comparisons p < 0.0001. The cFBMI exhibited excellent temporal
stability (ΔAUC = −0.004 for undernutrition, +0.002 for overnutrition) and superior calibration
(observed proportions: 9.6%/81.7%/8.8% vs. expected 10%/80%/10%; χ2 = 9.22, p =
0.010). The decision curve analysis confirmed the superior net benefit of cFBMI across all
threshold probabilities. Conclusions: The customized fetal BMI percentile model demonstrates
excellent and temporally stable discriminative performance in this single-institution
temporal validation study, with superior calibration and apparent advantages in clinical utility as determined by decision curve analysis compared with existing methods.
Its integration of body proportionality provides conceptual alignment with the Ponderal
Index gold standard. These findings are promising but require confirmation through external
multicenter validation before clinical implementation can be recommended. Although
the mathematical relationship between the index test (weight/length2) and the reference
standard (weight/length3) should be considered when interpreting the magnitude
of discrimination metrics, validation against independent clinical outcomes is an essential
next step. The cFBMI thus provides a proportionality-aware nutritional metric whose primary
discriminative advantage over weight-based methods is realized at and beyond the
moment of birth, and which is forward-compatible with emerging modalities for independent
prenatal fetal length estimation. | es_ES |