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Correlation between an annotation-free embryo scoring system based on deep learning and live birth/neonatal outcomes after single vitrified-warmed blastocyst transfer: a single-centre, large-cohort retrospective study.
| Content Provider | Europe PMC |
|---|---|
| Author | Ueno, Satoshi Berntsen, Jørgen Ito, Motoki Okimura, Tadashi Kato, Keiichi |
| Abstract | ProposeDoes an annotation-free embryo scoring system based on deep learning and time-lapse sequence images correlate with live birth (LB) and neonatal outcomes?MethodsPatients who underwent SVBT cycles (3010 cycles, mean age: 39.3 ± 4.0). Scores were calculated using the iDAScore software module in the Vitrolife Technology Hub (Vitrolife, Gothenburg, Sweden). The correlation between iDAScore, LB rates, and total miscarriage (TM), including 1st- and 2nd-trimester miscarriage, was analysed using a trend test and multivariable logistic regression analysis. Furthermore, the correlation between the iDAScore and neonatal outcomes was analysed.ResultsLB rates decreased as iDAScore decreased (P < 0.05), and a similar inverse trend was observed for the TM rates. Additionally, multivariate logistic regression analysis showed that iDAScore significantly correlated with increased LB (adjusted odds ratio: 1.811, 95% CI: 1.666–1.976, P < 0.05) and decreased TM (adjusted odds ratio: 0.799, 95% CI: 0.706–0.905, P < 0.05). There was no significant correlation between iDAScore and neonatal outcomes, including congenital malformations, sex, gestational age, and birth weight. Multivariate logistic regression analysis, which included maternal and paternal age, maternal body mass index, parity, smoking, and presence or absence of caesarean section as confounding factors, revealed no significant difference in any neonatal characteristics.ConclusionAutomatic embryo scoring using iDAScore correlates with decreased miscarriage and increased LB and has no correlation with neonatal outcomes.Supplementary informationThe online version contains supplementary material available at 10.1007/s10815-022-02562-5. |
| Related Links | https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC9475010&blobtype=pdf |
| ISSN | 10580468 |
| Journal | Journal of Assisted Reproduction and Genetics [J Assist Reprod Genet] |
| Volume Number | 39 |
| DOI | 10.1007/s10815-022-02562-5 |
| PubMed Central reference number | PMC9475010 |
| Issue Number | 9 |
| PubMed reference number | 35881272 |
| e-ISSN | 15737330 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2022-07-26 |
| Publisher Place | New York |
| Access Restriction | Open |
| Rights License | Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. © The Author(s) 2022, corrected publication 2022 |
| Subject Keyword | Live birth Single vitrified-warmed blastocyst transfer Artificial intelligence Neonatal outcome Objective assessment |
| Content Type | Text |
| Resource Type | Article |
| Subject | Genetics Developmental Biology Embryology Reproductive Medicine Genetics (clinical) Obstetrics and Gynecology |
