Evidence map›Paper›PMID 37291503›Full record

ArticleBMC pregnancy and childbirth2023

Prediction model for day 3 embryo implantation potential based on metabolites in spent embryo culture medium.

Rong Liang, Sheng Nan Duan, Min Fu, Yu Nan Chen, Ping Wang, Yuan Fan, Shihui Meng, Xi Chen, Cheng Shi

Abstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
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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

9 authors.

Rong Liang *Reproductive Medical Center, Department of Obstetrics and Gynecology, Peking University People's Hospital, Peking University, Beijing, China.
Sheng Nan Duan *Reproductive Medical Center, Department of Obstetrics and Gynecology, Peking University People's Hospital, Peking University, Beijing, China.
Min Fu *Reproductive Medical Center, Department of Obstetrics and Gynecology, Peking University People's Hospital, Peking University, Beijing, China.
Yu Nan ChenBeijing National Laboratory for Molecular Sciences (BNLMS), MOE Key Laboratory of Bioorganic Chemistry and Molecular Engineering, College of Chemistry and Molecular Engineering, Peking University, Beijing, China.
Ping WangReproductive Medical Center, Department of Obstetrics and Gynecology, Peking University People's Hospital, Peking University, Beijing, China.
Yuan FanReproductive Medical Center, Department of Obstetrics and Gynecology, Peking University People's Hospital, Peking University, Beijing, China.
Shihui MengReproductive Medical Center, Department of Obstetrics and Gynecology, Peking University People's Hospital, Peking University, Beijing, China.
Xi Chen *Reproductive Medical Center, Department of Obstetrics and Gynecology, Peking University People's Hospital, Peking University, Beijing, China. chenxi@pkuph.edu.cn.ORCID http://orcid.org/0000-0002-1349-9176
Cheng Shi *Reproductive Medical Center, Department of Obstetrics and Gynecology, Peking University People's Hospital, Peking University, Beijing, China. chengshi@bjmu.edu.cn.

Funding

Beijing Natural Science Foundation 7222200 and 7222197the Chinese Medical Association Special funding Project for Clinical Medical Scientific Research 17020530722
6 · The paper itself

Abstract

backgroundMetabolites in spent embryo culture medium correlate with the embryo's viability. However, there is no widely accepted method using metabolite dada to predict successful implantation. We sought to combine metabolomic profiling of spent embryo culture medium and clinical variables to create an implantation prediction model as an adjunct to morphological screening of day 3 embryos.

methodsThis investigation was a prospective, nested case-control study. Forty-two day 3 embryos from 34 patients were transferred, and the spent embryo culture medium was collected. Twenty-two embryos implanted successfully, and the others failed. Metabolites in the medium relevant to implantation were detected and measured by Liquid Chromatography-Mass Spectrometry. Clinical signatures relevant to embryo implantation were subjected to univariate analysis to select candidates for a prediction model. Multivariate logistical regression of the clinical and metabolomic candidates was used to construct a prediction model for embryo implantation potential.

resultsThe levels of 13 metabolites were significantly different between the successful and failed groups, among which five were most relevant and interpretable selected by Least Absolute Shrinkage and Selection Operator regression analysis. None of the clinical variables significantly affected day 3 embryo implantation. The most relevant and interpretable set of metabolites was used to construct a prediction model for day 3 embryo implantation potential with an accuracy of 0.88.

conclusionsDay 3 embryos'implantation potential could be noninvasively predicted by the spent embryo culture medium's metabolites measured by LC-MS. This approach may become a useful adjunct to morphological evaluation of day 3 embryos.

Indexed as

Embryo ImplantationEmbryo TransferCase-Control StudiesCulture MediaFertilization in VitroHumansProspective StudiesCulture MediaHuman day 3 embryosImplantation predictionLC-MSMetabolomicsSpent embryo culture medium

Identifiers

PMID37291503
PMCPMC10249307

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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.