{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T05:02:08Z","timestamp":1780549328436,"version":"3.54.1"},"reference-count":31,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T00:00:00Z","timestamp":1779408000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>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, C\u00e1diz, Spain. The development cohort comprised 7864 deliveries (2002\u20132021); the validation cohort comprised 4441 deliveries (2022\u20132025). Inclusion criteria: singleton pregnancy, gestational age of 33\u201342 + 6 weeks, birthweight of 500\u20136000 g, known neonatal sex and length, and complete maternal data. The Ponderal Index (PI = weight\/length3 \u00d7 100) stratified by sex and gestational age served as the gold standard (undernutrition: PI &lt; p10; overnutrition: PI &gt; 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 &lt; 0.0001. The cFBMI exhibited excellent temporal stability (\u0394AUC = \u22120.004 for undernutrition, +0.002 for overnutrition) and superior calibration (observed proportions: 9.6%\/81.7%\/8.8% vs. expected 10%\/80%\/10%; \u03c72 = 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.<\/jats:p>","DOI":"10.3390\/diagnostics16111584","type":"journal-article","created":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T12:14:52Z","timestamp":1779452092000},"page":"1584","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Temporal External Validation of a Customized Fetal Body Mass Index Percentile Model for Neonatal Nutritional Status Assessment"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7297-6876","authenticated-orcid":false,"given":"Juan Jes\u00fas","family":"Fern\u00e1ndez Alba","sequence":"first","affiliation":[{"name":"Department of Obstetrics and Gynaecology, University Hospital of Puerto Real, 11510 Cadiz, Spain"},{"name":"Institute of Research and Innovation in Biomedical Sciences of the Province of Cadiz (INiBICA), 11009 Cadiz, Spain"},{"name":"Departamento Materno-Infantil y Radiolog\u00eda, University of C\u00e1diz, 11003 C\u00e1diz, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4380-5621","authenticated-orcid":false,"given":"Mar\u00eda Castillo","family":"Lara","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynaecology, University Hospital of Puerto Real, 11510 Cadiz, Spain"},{"name":"Institute of Research and Innovation in Biomedical Sciences of the Province of Cadiz (INiBICA), 11009 Cadiz, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura","family":"Guti\u00e9rrez Palomino","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynaecology, University Hospital of Puerto Real, 11510 Cadiz, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jos\u00e9","family":"Castro Pe\u00f1as","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynaecology, University Hospital of Puerto Real, 11510 Cadiz, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roc\u00edo","family":"Quintero Prado","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynaecology, University Hospital of Puerto Real, 11510 Cadiz, Spain"},{"name":"Institute of Research and Innovation in Biomedical Sciences of the Province of Cadiz (INiBICA), 11009 Cadiz, Spain"},{"name":"Departamento Materno-Infantil y Radiolog\u00eda, University of C\u00e1diz, 11003 C\u00e1diz, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carmen","family":"Gonz\u00e1lez Mac\u00edas","sequence":"additional","affiliation":[{"name":"Department of Obstetrics and Gynaecology, University Hospital of Puerto Real, 11510 Cadiz, Spain"},{"name":"Institute of Research and Innovation in Biomedical Sciences of the Province of Cadiz (INiBICA), 11009 Cadiz, Spain"},{"name":"Departamento Materno-Infantil y Radiolog\u00eda, University of C\u00e1diz, 11003 C\u00e1diz, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,22]]},"reference":[{"key":"ref_1","first-page":"R1","article-title":"Epigenetic mechanisms in developmental programming of adult disease","volume":"242","author":"Goyal","year":"2019","journal-title":"J. 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