Evidence map›Paper›PMID 35602891›Full record

ArticlePeerJ2022

Search for morphological indicators that predict implantation by principal component analysis using images of blastocyst.

Daisuke Mashiko, Mikiko Tokoro, Masae Kojima, Noritaka Fukunaga, Yoshimasa Asada, Kazuo Yamagata

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 93% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

6 authors at 1 institution in 1 country.

Daisuke MashikoGraduate School of Biology-Oriented Science and Technology, Kindai University, Kinokawa, Wakayama, Japan.
Mikiko TokoroGraduate School of Biology-Oriented Science and Technology, Kindai University, Kinokawa, Wakayama, Japan.
Masae KojimaAsada Institute for Reproductive Medicine, Asada Ladies Clinic, Nagoya, Aichi, Japan.
Noritaka FukunagaAsada Institute for Reproductive Medicine, Asada Ladies Clinic, Nagoya, Aichi, Japan.
Yoshimasa AsadaAsada Institute for Reproductive Medicine, Asada Ladies Clinic, Nagoya, Aichi, Japan.
Kazuo YamagataGraduate School of Biology-Oriented Science and Technology, Kindai University, Kinokawa, Wakayama, Japan.
Kindai University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Although the current evaluation of human blastocysts is based on the Gardner criteria, there may be other notable parameters. The purpose of our study was to clarify whether the morphology of blastocysts has notable indicators other than the Gardner criteria. Methods: To find such indicators, we compared blastocysts that showed elevated human chorionic gonadotropin (hCG) levels after transplantation (hCG-positive group; Results: The comparison revealed that the hCG-positive group had grainy morphology and the hCG-negative group had non-grainy morphology. Classification of the blastocysts by this indicator did not make a difference in Gardner score. Interestingly, all embryos with ≥20% fragmentation were non-grainy. The visual classification based on this analysis was significantly more accurate than the prediction of implantation using the Gardner score ≥3BB. As graininess can be used in combination with the Gardner score, this indicator will enhance current reproductive technologies.

Indexed as

Chorionic GonadotropinEmbryo ImplantationBlastocystHumansPrincipal Component AnalysisChorionic GonadotropinBlastocyst morphologyMorphometryPrincipal component analysis

Identifiers

PMID35602891
PMCPMC9119295
OpenAlexW4280496083

What OpenQuestion holds

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LicenceCC BY
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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.