Mimar Sinan Güzel Sanatlar Üniversitesi Açık Bilim, Sanat Arşivi

Açık Bilim, Sanat Arşivi, Mimar Sinan Güzel Sanatlar Üniversitesi tarafından doğrudan ve dolaylı olarak yayınlanan; kitap, makale, tez, bildiri, rapor gibi tüm akademik kaynakları uluslararası standartlarda dijital ortamda depolar, Üniversitenin akademik performansını izlemeye aracılık eder, kaynakları uzun süreli saklar ve yayınların etkisini artırmak için telif haklarına uygun olarak Açık Erişime sunar.

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dc.contributor.authorOzer, Gonul
dc.contributor.authorAkca, Aysu
dc.contributor.authorYuksel, Beril
dc.contributor.authorDuzguner, Ipek
dc.contributor.authorPehlivanli, Ayca Cakmak
dc.contributor.authorKahraman, Semra
dc.date.accessioned2025-01-09T20:14:25Z
dc.date.available2025-01-09T20:14:25Z
dc.date.issued2023
dc.identifier.issn1058-0468
dc.identifier.issn1573-7330
dc.identifier.urihttps://doi.org/10.1007/s10815-022-02645-3
dc.identifier.urihttps://hdl.handle.net/20.500.14124/9050
dc.description.abstractPurpose Can the risk factors that cause first trimester pregnancy loss in good-quality frozen-thawed embryo transfer (FET) cycles be predicted using machine learning algorithms? Methods This is a retrospective cohort study conducted at Sisli Memorial Hospital, ART and Reproductive Genetics Center, between January 2011 and May 2021. A total of 3805 good-quality FET cycles were included in the study. First trimester pregnancy loss rates were evaluated according to female age, paternal age, body mass index (BMI), diagnosis of infertility, endometrial preparation protocols (natural/artificial), embryo quality (top/good), presence of polycystic ovarian syndrome (PCOS), history of recurrent pregnancy loss (RPL), recurrent implantation failure (RIF), severe male infertility, adenomyosis and endometriosis. Results The first trimester pregnancy loss rate was 18.2% (693/ 3805). The presence of RPL increased first trimester pregnancy loss (OR = 7.729, 95%CI = 5.908-10.142, P = 0.000). BMI, which is > 30, increased first trimester pregnancy loss compared to < 25 (OR = 1.418, 95%CI = 1.025-1.950, P = 0.033). Endometrial preparation with artificial cycle increased first trimester pregnancy loss compared to natural cycle (OR = 2.101, 95%CI = 1.630-2.723, P = 0.000). Female age, which is 35-37, increased first trimester pregnancy loss compared to < 30 (OR = 1.617, 95%CI = 1.120-2.316, P = 0.018), and female age, which is > 37, increased first trimester pregnancy loss compared to < 30 (OR = 2.286, 95%CI = 1.146-4,38, P = 0.016). The presence of PCOS increased first trimester pregnancy loss (OR = 1.693, 95%CI = 1.198-2.390, P = 0.002). The number of previous IVF cycles, which is > 3, increased first trimester pregnancy loss compared to < 3 (OR = 2.182, 95%CI = 1.708-2.790, P = 0.000). Conclusions History of RPL, RIF, advanced female age, presence of PCOS, and high BMI (> 30 kg/m(2)) were the factors that increased first trimester pregnancy loss.en_US
dc.language.isoengen_US
dc.publisherSpringer/Plenum Publishersen_US
dc.relation.ispartofJournal of Assisted Reproduction and Geneticsen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectFirst trimester pregnancy lossen_US
dc.subjectFrozen-thawed embryo transfer (FET) cyclesen_US
dc.subjectIn vitro fertilization (IVF)en_US
dc.subjectMachine learning algorithmsen_US
dc.subjectInfertilityen_US
dc.titlePrediction of risk factors for first trimester pregnancy loss in frozen-thawed good-quality embryo transfer cycles using machine learning algorithmsen_US
dc.typearticleen_US
dc.authoridCakmak Pehlivanli, Ayca/0000-0001-9884-6538
dc.authoridozer, gonul/0000-0003-2900-8623
dc.departmentMimar Sinan Güzel Sanatlar Üniversitesien_US
dc.identifier.doi10.1007/s10815-022-02645-3
dc.identifier.volume40en_US
dc.identifier.issue2en_US
dc.identifier.startpage279en_US
dc.identifier.endpage288en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.wosqualityQ2
dc.identifier.wosWOS:000885205800001
dc.identifier.scopus2-s2.0-85142150612
dc.identifier.pmid36399255
dc.identifier.scopusqualityQ1
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.snmzKA_20250105


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