ArticleSaudi journal of biological sciences2020
Establishment of predictive model for analyzing clinical pregnancy outcome based on IVF-ET and ICSI assisted reproductive technology.
Article in Saudi journal of biological sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 10 citations in OpenAlex.
- The Influencing Factors and Predictive Algorithm of Pregnancy Outcomes in IVF/ICSI-ET Patients.International journal of women's health · 2026Article
- Effect of basal luteinizing hormone/follicle-stimulating hormone ratio on clinical outcome ofPeerJ · 2024Article
- Nomogram prediction for the prediction of clinical pregnancy in Freeze-thawed Embryo Transfer.BMC pregnancy and childbirth · 2022Article
- Association between baseline LH/FSH and live-birth rate after fresh-embryo transfer in polycystic ovary syndrome women.Scientific reports · 2021Article
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4 authors at 2 institutions in 1 country.
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Abstract
In order to explore the predictive model for analyzing clinical pregnancy outcomes based on IVF-ET (in vitro fertilization and embryo transfer) and ICSI (Intracytoplasmic sperm injection) assisted reproductive technology (ART).
methodsthis study selected the embryo transfer (fresh) patients who received IVF-ET or ICSI treatment in the First Affiliated Hospital of Guangxi Medical University as the subjects. Moreover, the controlled ovarian stimulation (COS) and follow-up were conducted to collect relevant data for analysis, and finally a prediction model was established.
resultsThe results showed that the patients were divided into different ovarian response groups at first. The age, bFSH and bFSH/bLH were the highest in the poor ovarian response group (POR), followed by the normal ovarian response group (NOR) and the lowest in the high ovarian response group (HOR). The area under the ROC curve was 0.669 according to the predictive model of pregnancy-related factors. The confidence interval of 94% was 0.629-0.697, with statistical significance (P = 0.000, P < 0.01).
conclusionit can be concluded that in clinical pregnancy, for many related factors, regression equation can be used to establish a prediction model to diagnose the success rate of pregnancy. In conclusion, a prediction model can be built based on the relevant experimental results, to provide experimental reference ideas for increasing the success rate of ART in late clinical pregnancy, which is of great research significance.
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