{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T18:47:38Z","timestamp":1791830858833,"version":"4.3.4"},"reference-count":0,"publisher":"Bioscientifica","license":[{"start":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T00:00:00Z","timestamp":1791763200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["journals.bioscientifica.com"],"crossmark-restriction":true},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Gestational diabetes mellitus (GDM) is associated with a significantly increased risk of adverse pregnancy outcomes. This study aimed to develop and internally validate a nomogram integrating integrating first-trimester metabolic and angiogenic markers to predict composite adverse pregnancy outcomes in GDM.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective cohort study of 1,000 GDM patients (training set n=700, validation set n=300). Multivariable logistic regression was used to identify independent predictors and construct a nomogram. Model performance was assessed by discrimination (area under the receiver operating characteristic curve [AUC]), calibration (Hosmer-Lemeshow test, calibration plots), and decision curve analysis (DCA).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Six variables were retained as independent predictors: pre-pregnancy BMI, FPG, TG, HOMA-IR, PIGF, and sFlt-1. The full model showed excellent discrimination in internal validation, with an AUC of 0.87 (95% CI 0.84\u20130.90) in the training set and 0.84 (95% CI 0.80\u20130.88) in the validation set, significantly outperforming a metabolic-only model without PIGF\/sFlt-1 (AUC 0.82, p=0.01). Calibration was good (Hosmer-Lemeshow p=0.36 and 0.42, respectively). DCA demonstrated clinical net benefit across threshold probabilities of 0.15\u20130.35. Subgroup analyses confirmed stable performance across age, BMI, treatment, and parity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The nomogram incorporating first-trimester metabolic and angiogenic markers accurately predicts adverse pregnancy outcomes in GDM patients in this internal validation cohort.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1530\/ec-26-0478","type":"journal-article","created":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T18:18:51Z","timestamp":1791829131000},"update-policy":"https:\/\/doi.org\/10.1530\/crossmarkpolicy-10","source":"Crossref","is-referenced-by-count":0,"title":["A nomogram integrating first-trimester metabolic and angiogenic markers for predicting adverse pregnancy outcomes in gestational diabetes mellitus: development and internal validation"],"prefix":"10.1530","author":[{"given":"Jingli","family":"Fu","sequence":"first","affiliation":[{"name":"Department of Obstetrics, Women and Children\u2019s Hospital, School of Medicine, Xiamen University 1 , , ,","place":["Xiamen, Fujian, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Zhong","sequence":"additional","affiliation":[{"name":"Department of Obstetrics, Women and Children\u2019s Hospital, School of Medicine, Xiamen University 1 , , ,","place":["Xiamen, Fujian, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Obstetrics, Women and Children\u2019s Hospital, School of Medicine, Xiamen University 1 , , ,","place":["Xiamen, Fujian, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siying","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Department of Obstetrics, Women and Children\u2019s Hospital, School of Medicine, Xiamen University 1 , , ,","place":["Xiamen, Fujian, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1135-9158","authenticated-orcid":true,"given":"Weiwei","family":"Yu","sequence":"additional","affiliation":[{"name":"Department of Obstetrics, Women and Children\u2019s Hospital, School of Medicine, Xiamen University 1 , , ,","place":["Xiamen, Fujian, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"416","published-online":{"date-parts":[[2026,10,12]]},"container-title":["Endocrine Connections"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.bioscientifica.com\/ec\/article-pdf\/doi\/10.1530\/EC-26-0478\/526427\/ec-26-0478.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/journals.bioscientifica.com\/ec\/article-pdf\/doi\/10.1530\/EC-26-0478\/526427\/ec-26-0478.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T18:18:52Z","timestamp":1791829132000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.bioscientifica.com\/ec\/article\/doi\/10.1530\/EC-26-0478\/78365\/A-nomogram-integrating-first-trimester-metabolic"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,12]]},"references-count":0,"URL":"https:\/\/doi.org\/10.1530\/ec-26-0478","relation":{},"ISSN":["2049-3614"],"issn-type":[{"value":"2049-3614","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,12]]},"article-number":"EC-26-0478"}}