74224c7f0430cfb1d69a9e95fa50f49c pmc_9920601.pdf 628ccdfd5b7a7194fdd9650dcc0bb8bfd552e711 pmc_9920601.pdf 8471b76779e51f9b68ab3a524f9468d3a89e9d9dfec6dbf093f22af7fff1024c pmc_9920601.pdf Title: Abnormal Maternal Body Mass Index and Customized Fetal Weight Charts: Improving the Identification of Small for Gestational Age Fetuses and Newborns Subject: Background: Obesity and thinness are serious diseases, but cases with abnormal maternal weight have not been excluded from the calculations in the construction of customized fetal growth curves (CCs). Method: To determine if the new CCs, built excluding mothers with an abnormal weight, are better than standard CCs at identifying SGA. A total of 16,122 neonates were identified as SGA, LGA, or AGA, using the two models. Logistic regression and analysis of covariance were used to calculate the OR and CI for adverse outcomes by group. Gestational age was considered as a covariable. Results: The SGA rates by the new CCs and by the standard CCs were 11.8% and 9.7%, respectively. The SGA rate only by the new CCs was 18% and the SGA rate only by the standard CCs was 0.01%. Compared to AGA by both models, SGA by the new CCs had increased rates of cesarean section, (OR 1.53 (95% CI 1.19, 1.96)), prematurity (OR 2.84 (95% CI 2.09, 3.85)), NICU admission (OR 5.41 (95% CI 3.47, 8.43), and adverse outcomes (OR 1.76 (95% CI 1.06, 2.60). The strength of these associations decreased with gestational age. Conclusion: The use of the new CCs allowed for a more accurate identification of SGA at risk of adverse perinatal outcomes as compared to the standard CCs. Keywords: customized growth charts; fetal weight; newborn weight; maternal body mass index; obesity; thinness; small for gestational age; birthweight; newborn weight; perinatal outcomes Author: Nieves Luisa González González, Enrique González Dávila, Agustina González Martín, Marina Armas, Laura Tascón, Alba Farras, Teresa Higueras, Manel Mendoza, Elena Carreras and María Goya Creator: LaTeX with hyperref Producer: pdfTeX-1.40.21 CreationDate: Sun Jan 22 11:45:06 2023 CET ModDate: Sun Jan 22 11:47:27 2023 CET Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 11 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 841993 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- PRJKGQ+VnURWPalladioL-Bold Type 1 Custom yes yes no 10 0 EKBMVV+VnURWPalladioL Type 1 Custom yes yes no 15 0 DSWOVI+URWPalladioL-Bold Type 1 Custom yes yes no 19 0 JXWJTJ+URWPalladioL-Roma Type 1 Custom yes yes no 24 0 EXUOUY+URWPalladioL-Ital Type 1 Custom yes yes no 28 0 HGMNRX+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 46 0 GQWIGS+CMSY10 Type 1 Builtin yes yes no 71 0 JLZORU+EURM10 Type 1 Builtin yes yes no 75 0 QZQLBJ+URWPalladioL-BoldItal Type 1 Custom yes yes no 82 0 CIDFont+F3 CID TrueType Identity-H yes no yes 91 0 CIDFont+F1 CID TrueType Identity-H yes no yes 99 0 CIDFont+F2 CID TrueType Identity-H yes no yes 107 0 CIDFont+F5 CID TrueType Identity-H yes no yes 115 0 Jhove (Rel. 1.22.1, 2019-04-17) Date: 2023-03-28 02:30:51 CEST RepresentationInformation: pmc_9920601.pdf ReportingModule: PDF-hul, Rel. 1.12.1 (2019-04-17) LastModified: 2023-03-23 02:12:20 CET Size: 841993 Format: PDF Version: 1.7 Status: Well-Formed and valid SignatureMatches: PDF-hul MIMEtype: application/pdf PDFMetadata: Objects: 277 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@44c8afef Item: Title: Material and Method Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@7b69c6ba Children: Item: Title: Outcomes Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@46daef40 Item: Title: Subgroups and Comparisons Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@12f41634 Item: Title: Statistical Analysis Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@13c27452 Item: Title: Results Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@262b2c86 Item: Title: Discussion Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@371a67ec Item: Title: Conclusions Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@5ed828d Item: Title: References Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@50d0686 Info: Title: Abnormal Maternal Body Mass Index and Customized Fetal Weight Charts: Improving the Identification of Small for Gestational Age Fetuses and Newborns Author: Nieves Luisa González González, Enrique González Dávila, Agustina González Martín, Marina Armas, Laura Tascón, Alba Farras, Teresa Higueras, Manel Mendoza, Elena Carreras and María Goya Subject: Background: Obesity and thinness are serious diseases, but cases with abnormal maternal weight have not been excluded from the calculations in the construction of customized fetal growth curves (CCs). Method: To determine if the new CCs, built excluding mothers with an abnormal weight, are better than standard CCs at identifying SGA. A total of 16,122 neonates were identified as SGA, LGA, or AGA, using the two models. Logistic regression and analysis of covariance were used to calculate the OR and CI for adverse outcomes by group. Gestational age was considered as a covariable. Results: The SGA rates by the new CCs and by the standard CCs were 11.8% and 9.7%, respectively. The SGA rate only by the new CCs was 18% and the SGA rate only by the standard CCs was 0.01%. Compared to AGA by both models, SGA by the new CCs had increased rates of cesarean section, (OR 1.53 (95% CI 1.19, 1.96)), prematurity (OR 2.84 (95% CI 2.09, 3.85)), NICU admission (OR 5.41 (95% CI 3.47, 8.43), and adverse outcomes (OR 1.76 (95% CI 1.06, 2.60). The strength of these associations decreased with gestational age. Conclusion: The use of the new CCs allowed for a more accurate identification of SGA at risk of adverse perinatal outcomes as compared to the standard CCs. 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