{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,9]],"date-time":"2026-11-09T23:00:59Z","timestamp":1794265259471,"version":"4.9.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T00:00:00Z","timestamp":1763769600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T00:00:00Z","timestamp":1767052800000},"content-version":"vor","delay-in-days":38,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Pregnancy Childbirth"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Pregestational diabetes mellitus (PREGDM) confers a high risk of maternal and perinatal morbidity. Identifying early, reliable biomarkers is critical for risk stratification. The atherogenic index of plasma (AIP) and triglyceride\u2013glucose (TyG) index are inexpensive metabolic markers reflecting dyslipidemia and insulin resistance, but their role in PREGDM remains underexplored.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>In this retrospective cohort study, medical records of 628 women (314 with PREGDM, 314 controls) delivering at a tertiary referral center were reviewed. First-trimester fasting blood samples were analyzed to calculate AIP [log\u2081\u2080(TG\/HDL-C)] and TyG [ln(TG\u00d7glucose\/2)]. Maternal and perinatal outcomes assessed included preeclampsia, preterm birth, macrosomia, fetal growth restriction (FGR), NICU admission, Apgar\u2009&lt;\u20097 at 1 and 5\u00a0min, and a composite adverse perinatal outcome (CAPO). Logistic regression adjusted for age, BMI, parity, smoking, HbA1c, and fasting glucose; predictive ability was evaluated by ROC analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Compared with controls, women with PREGDM had significantly higher AIP (0.171\u2009\u00b1\u20090.207 vs. 0.148\u2009\u00b1\u20090.029,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001) and TyG (9.33\u2009\u00b1\u20090.65 vs. 8.90\u2009\u00b1\u20090.10,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). PREGDM was associated with higher rates of preeclampsia (13.1% vs. 4.5%), preterm birth (21.7% vs. 10.8%), macrosomia (13.4% vs. 5.7%), FGR (8.3% vs. 3.8%), NICU admission (23.6% vs. 8.9%), and CAPO (29.3% vs. 9.9%) (all\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.01). In multivariate models, TyG independently predicted preterm birth (OR 1.62, 95% CI 1.28\u20132.04), macrosomia (OR 1.48, 95% CI 1.10\u20131.99), CAPO (OR 1.78, 95% CI 1.35\u20132.33), and low Apgar at 1\u00a0min (OR 1.84, 95% CI 1.40\u20132.42). AIP was inversely associated with FGR (OR 0.68, 95% CI 0.51\u20130.92). ROC analysis showed high accuracy of TyG for predicting low Apgar at 1\u00a0min (AUC 0.88) and NICU admission (AUC 0.76).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Both AIP and TyG are elevated in PREGDM compared with controls. TyG is a robust predictor of preterm birth, macrosomia, neonatal compromise, and CAPO, whereas AIP provides complementary insight into vascular dysfunction and FGR in PREGDM group. These indices, easily derived from routine first-trimester tests, may offer practical tools for early obstetric risk stratification.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12884-025-08491-2","type":"journal-article","created":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T13:52:55Z","timestamp":1763819575000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["First-trimester atherogenic index of plasma and triglyceride\u2013glucose indices in pregestational diabetes mellitus: associations with adverse pregnancy outcomes"],"prefix":"10.1186","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6465-325X","authenticated-orcid":false,"given":"Serenat Eris","family":"Yalcin","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nuray","family":"Nerez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yakup","family":"Yalcin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bilge Demir","family":"Cetinkaya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,22]]},"reference":[{"issue":"1","key":"8491_CR1","doi-asserted-by":"publisher","first-page":"9017","DOI":"10.1038\/s41598-024-59465-x","volume":"14","author":"M Oros Ruiz","year":"2024","unstructured":"Oros Ruiz M, Perej\u00f3n L\u00f3pez D, Serna Arnaiz C, Siscart Viladegut J, \u00c0ngel Bald\u00f3 J, Sol J. 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