Evidence map›Paper›PMID 41286009›Full record

ArticleScientific reports2025

Development and validation of a nomogram for predicting ectopic pregnancy in patients receiving double fresh cleavage stage embryo transfer.

Yimeng Ge, Shuo Yang, Caihong Ma, Jie Qiao, Rong Li

Abstract readValidation Study
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yimeng GeState Key Laboratory of Female Fertility Promotion, Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, 100191, China.
Shuo YangState Key Laboratory of Female Fertility Promotion, Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, 100191, China.
Caihong MaState Key Laboratory of Female Fertility Promotion, Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, 100191, China.
Jie QiaoState Key Laboratory of Female Fertility Promotion, Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, 100191, China.
Rong LiState Key Laboratory of Female Fertility Promotion, Center for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, 100191, China. roseli001@sina.com.

Funding

National Key Research and Development Program of China 2022YFC2702502National Science Fund for Distinguished Young Scholars 81925013
6 · The paper itself

Abstract

Ectopic pregnancy (EP) is a common yet fatal complication of in vitro fertilization-embryo transfer (IVF-ET) and intracytoplasmic sperm injection (ICSI). We aim to establish and validate a nomogram in patients undergoing double fresh cleavage-stage embryo transfer, which remains a mainstream strategy in infertile patients. Data from 7456 patients were reviewed and divided into training and validation sets. Logistic analyses were conducted to identify the risk factors, with calibration and decision-curve analyses performed to evaluate model performance. The model divided patients into high- and low-risk groups, showing different 48-h serum beta-human chorionic gonadotropin (HCG) rising thresholds. It showed that Tubal factor infertility (Odds Ratio [OR] = 1.680, 95% Confidence Interval [CI] 1.129-2.500, P = 0.011), previous tubal surgery (OR = 2.667, 95% CI 1.772-4.015, P < 0.001), polycystic ovarian syndrome (PCOS) (OR = 1.809, 95% CI 1.169-2.799, P = 0.008), uterine malformation (OR = 5.663, 95% CI 1.524-21.043, P = 0.010), endometrial thickness (OR = 0.585, 95% CI 0.522-0.655, P < 0.001) and serum estradiol levels (OR = 1.000, 95% CI 1.000-1.000, P < 0.001) on triggering day were independent risk factors for EP after double fresh cleavage-stage embryo transfer. The area under curve (AUC) values for the training and validation sets were 0.768 (95% CI 0.732-0.805, P < 0.001) and 0.756 (95% CI 0.703-0.810, P < 0.001), respectively. The nomogram further divided all participants into high EP risk and low EP risk with a cut-off score of 86.1 based on the maximum value of Youden Index in order to investigate different subsequent interventions based on serum HCG level. Patients in high EP risk group suffered significantly higher incidence of EP (OR = 4.902, 95% CI 3.597-6.667, P < 0.001 and OR = 4.587, 95% CI 2.899-7.246, P < 0.001). Higher 48-h serum HCG rising thresholds (2.18 vs. 1.74 and 2.10 vs. 1.66) also applied to patients from high EP risk group. The nomogram effectively predicts individual EP probability in patients receiving double fresh cleavage-stage embryo transfer, thereby aiding screening high-risk patients.

Indexed as

Embryo TransferNomogramsPregnancy, EctopicAdultFemaleFertilization in VitroHumansPregnancyRetrospective StudiesRisk FactorsSperm Injections, IntracytoplasmicEctopic pregnancyInfertilityIVF/ICSINomogramPredictive model

Identifiers

PMID41286009
PMCPMC12644677

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