Evidence map›Paper›PMID 38983691›Full record

ReviewReproductive medicine and biology

Developmental perturbation in human embryos: Clinical and biological significance learned from time-lapse images.

Kenji Ezoe, Tsubasa Takahashi, Tetsuya Miki, Keiichi Kato

Abstract readReview
In one paragraph

Review in Reproductive medicine and biology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
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  5. Review
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Kenji EzoeKato Ladies Clinic Tokyo Japan.ORCID https://orcid.org/0000-0002-3778-2259
Tsubasa TakahashiKato Ladies Clinic Tokyo Japan.
Tetsuya MikiKato Ladies Clinic Tokyo Japan.ORCID https://orcid.org/0000-0003-0563-5358
Keiichi KatoKato Ladies Clinic Tokyo Japan.ORCID https://orcid.org/0000-0002-1394-4532

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Time-lapse technology (TLT) has gained widespread adoption worldwide. In addition to facilitating the undisturbed culture of embryos, TLT offers the unique capability of continuously monitoring embryos to detect spatiotemporal changes. Although these observed phenomena play a role in optimal embryo selection/deselection, the clinical advantages of introducing TLT remain unclear. However, manual annotation of embryo perturbation could facilitate a comprehensive assessment of developmental competence. This process requires a thorough understanding of embryo observation and the biological significance associated with developmental dogma and variation. This review elucidates the typical behavior and variation of each phenomenon, exploring their clinical significance and research perspectives. Methods: The MEDLINE database was searched using PubMed for peer-reviewed English-language original articles concerning human embryo development. Main findings: TLT allows the observation of consecutive changes in embryo morphology, serving as potential biomarkers for embryo assessment. In assisted reproductive technology laboratories, several phenomena have not revealed their mechanism, posing difficulties such as fertilization deficiency and morula arrest. Conclusion: A profound understanding of the biological mechanisms and significance of each phenomenon is crucial. Further collaborative efforts between the clinical and molecular fields following translational studies are required to advance embryonic outcomes and assessment.

Indexed as

assisted reproductive technologydevelopmental competenceembryo developmentembryo selectiontime‐lapse imaging

Identifiers

PMID38983691
PMCPMC11232294

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.