Trial reportHuman reproduction (Oxford, England)2022
A double-blind randomized controlled trial investigating a time-lapse algorithm for selecting Day 5 blastocysts for transfer.
Trial report in Human reproduction (Oxford, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03445923 (Can Time-lapse Parameters be Used to Predict Pregnancy of Human Embryos?), which is not on this map. Cited by 27 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Can Time-lapse Parameters be Used to Predict Pregnancy of Human Embryos?
Who cites it
27 citing papers in PubMed.
- Obstetric and perinatal outcomes from the follow-up of a multicentre randomized controlled trial investigating time-lapse embryo monitoring.Human reproduction (Oxford, England) · 2026Trial
- Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.Nature medicine · 2024Trial
- Correlation between artificial intelligence-based IDAScore and embryo morphokinetic parameters: a retrospective cohort study.BMC pregnancy and childbirth · 2026Article
- Cost-effectiveness of time-lapse monitoring with or without the use of embryo selection software compared to routine incubation and selection.Human reproduction open · 2026Article
- Current progress and open challenges for applying artificial intelligence across thePatterns (New York, N.Y.) · 2025Review
- Article
- Article
- The Istanbul consensus update: a revised ESHRE/ALPHA consensus on oocyte and embryo static and dynamic morphological assessment†,‡.Human reproduction (Oxford, England) · 2025Article
- Application of a methodological framework for the development and multicenter validation of reliable artificial intelligence in embryo evaluation.Reproductive biology and endocrinology : RB&E · 2025Article
- Artificial Intelligence, Clinical Decision Support Algorithms, Mathematical Models, Calculators Applications in Infertility: Systematic Review and Hands-On Digital Applications.Mayo Clinic proceedings. Digital health · 2024Review
- The inconvenient reality of AI-assisted embryo selection in IVF.Nature medicine · 2024Article
- Quantitative Standardized Expansion Assay: An Artificial Intelligence-Powered Morphometric Description of Blastocyst Expansion and Zona Thinning Dynamics.Life (Basel, Switzerland) · 2024Article
- Review
- Correlation between Human Embryo Morphokinetics Observed through Time-Lapse Incubator and Life Birth Rate.Journal of personalized medicine · 2024Article
- METAPHOR: Metabolic evaluation through phasor-based hyperspectral imaging and organelle recognition for mouse blastocysts and oocytes.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Viewing early life without labels: optical approaches for imaging the early embryo†.Biology of reproduction · 2024Review
- BlastAssist: a deep learning pipeline to measure interpretable features of human embryos.Human reproduction (Oxford, England) · 2024Article
- Time-Lapse Incubation for Embryo Culture-Morphokinetics and Environmental Stability May Not Be Enough: Results from a Pilot Randomized Controlled Trial.Journal of clinical medicine · 2024Article
- The prospect of artificial intelligence to personalize assisted reproductive technology.NPJ digital medicine · 2024Review
- Steady morphokinetic progression is an independent predictor of live birth: a descriptive reference for euploid embryos.Human reproduction open · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
21 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
study questionCan use of a commercially available time-lapse algorithm for Day 5 blastocyst selection improve pregnancy rates compared with morphology alone? SUMMARY ANSWER: The use of a time-lapse selection model to choose blastocysts for fresh single embryo transfer on Day 5 did not improve ongoing pregnancy rate compared to morphology alone. WHAT IS KNOWN ALREADY: Evidence from time-lapse monitoring suggests correlations between timing of key developmental events and embryo viability. No good quality evidence exists to support improved pregnancy rates following time-lapse selection. STUDY DESIGN, SIZE, DURATION: A prospective multicenter randomized controlled trial including 776 randomized patients was performed between 2018 and 2021. Patients with at least two good quality blastocysts on Day 5 were allocated by a computer randomization program in a proportion of 1:1 into either the control group, whereby single blastocysts were selected for transfer by morphology alone, or the intervention group whereby final selection was decided by a commercially available time-lapse model. The embryologists at the time of blastocyst morphological scoring were blinded to which study group the patients would be randomized, and the physician and patients were blind to which group they were allocated until after the primary outcome was known. The primary outcome was number of ongoing pregnancies in the two groups. PARTICIPANTS/MATERIALS, SETTING,
methodsFrom 10 Nordic IVF clinics, 776 patients with a minimum of two good quality blastocysts on Day 5 (D5) were randomized into one of the two study groups. A commercial time-lapse model decided the final selection of blastocysts for 387 patients in the intervention (time-lapse) group, and blastocysts with the highest morphological score were transferred for 389 patients in the control group. Only single embryo transfers in fresh cycles were performed. MAIN RESULTS AND THE ROLE OF CHANCE: In the full analysis set, the ongoing pregnancy rate for the time-lapse group was 47.4% (175/369) and 48.1% (181/376) in the control group. No statistically significant difference was found between the two groups: mean difference -0.7% (95% CI -8.2, 6.7, P = 0.90). Pregnancy rate (60.2% versus 59.0%, mean difference 1.1%, 95% CI -6.2, 8.4, P = 0.81) and early pregnancy loss (21.2% versus 18.5%, mean difference 2.7%, 95% CI -5.2, 10.6, P = 0.55) were the same for the time-lapse and the control group. Subgroup analyses showed that patient and treatment characteristics did not significantly affect the commercial time-lapse model D5 performance. In the time-lapse group, the choice of best blastocyst changed on 42% of occasions (154/369, 95% CI 36.9, 47.2) after the algorithm was applied, and this rate was similar for most treatment clinics. LIMITATIONS, REASONS FOR CAUTION: During 2020, the patient recruitment rate slowed down at participating clinics owing to coronavirus disease-19 restrictions, so the target sample size was not achieved as planned and it was decided to stop the trial prematurely. The study only investigated embryo selection at the blastocyst stage on D5 in fresh IVF transfer cycles. In addition, only blastocysts of good morphological quality were considered for transfer, limiting the number of embryos for selection in both groups: also, it could be argued that this manual preselection of blastocysts limits the theoretical selection power of time-lapse, as well as restricting the results mainly to a good prognosis patient group. Most patients were aimed for blastocyst stage transfer when a minimum of five zygotes were available for extended culture. Finally, the primary clinical outcome evaluated was pregnancy to only 6-8 weeks. WIDER IMPLICATIONS OF THE
findingsThe study suggests that time-lapse selection with a commercially available time-lapse model does not increase chance of ongoing pregnancy after single blastocyst transfer on Day 5 compared to morphology alone. STUDY FUNDING/COMPETING INTEREST(S): The study was financed by a grant from the Swedish state under the ALF-agreement between the Swedish government and the county councils (ALFGBG-723141). Vitrolife supported the study with embryo culture dishes and culture media. During the study period, T.H. changed his employment from Livio AB to Vitrolife AB. All other authors have no conflicts of interests to disclose. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov registration number NCT03445923. TRIAL REGISTRATION DATE: 26 February 2018. DATE OF FIRST PATIENT’S ENROLMENT: 11 June 2018.
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