Evidence map›Paper›PMID 40473637›Full record

ArticleNPJ biofilms and microbiomes2025

Harnessing vaginal inflammation and microbiome: a machine learning model for predicting IVF success.

Ofri Bar, Stylianos Vagios, Omer Barkai, Joseph Elshirbini, Irene Souter, Jiawu Xu, Kaitlyn James, Charles Bormann, Makiko Mitsunami, Jorge E Chavarro and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ biofilms and microbiomes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
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  5. Article
  6. 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

14 authors.

Ofri Bar *Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA. ofri.bar@mail.huji.ac.il.
Stylianos Vagios *Department of Obstetrics & Gynecology, Tufts University Medical Center, Boston, MA, USA.
Omer Barkai *Harvard Medical School, Boston, MA, USA.
Joseph ElshirbiniRagon Institute of MGH, MIT, and Harvard, Massachusetts General Hospital, Cambridge, MA, USA.
Irene SouterDivision of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Harvard Medical School, Massachusetts General Hospital Fertility Center, Boston, MA, USA.
Jiawu XuRagon Institute of MGH, MIT, and Harvard, Massachusetts General Hospital, Cambridge, MA, USA.
Kaitlyn JamesDepartment of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA.
Charles BormannDivision of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Harvard Medical School, Massachusetts General Hospital Fertility Center, Boston, MA, USA.
Makiko MitsunamiDivision of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Harvard Medical School, Massachusetts General Hospital Fertility Center, Boston, MA, USA.
Jorge E ChavarroDivision of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, Harvard Medical School, Massachusetts General Hospital Fertility Center, Boston, MA, USA.
Philipp FoessleitnerDepartment of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA.
Douglas S KwonHarvard Medical School, Boston, MA, USA.
Moran Yassour *Department of Microbiology and Molecular Genetics, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
Caroline Mitchell *Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA.

Funding

The Harvard Clinical and Translational Science CenterUL1TR002541 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2018 to 2022
$93.0M
NCATS NIH HHS UL1 TR002541
6 · The paper itself

Abstract

Humans are the only species with a commensal Lactobacillus-dominant vaginal microbiota. Reproductive tract microbes have been linked to fertility outcomes, as has intrauterine inflammation, suggesting immune response may mediate adverse outcomes. In this pilot study, we compared vaginal microbiota composition and immune marker concentrations between patients with unexplained or male factor infertility (MFI), as a control. We applied a supervised machine learning algorithm that integrated microbiome and inflammation data to predict pregnancy outcomes.Twenty-eight participants provided vaginal swabs at three IVF cycle time points; 18 achieved pregnancy. Pregnant participants had lower microbial diversity and inflammation. Among them, MFI cases had higher diversity but lower inflammation than those with unexplained infertility. Our model showed the highest prediction accuracy at time point 2 of the IVF cycle. These findings suggest that vaginal microbiota and inflammation jointly impact fertility and can inform predictive tools in reproductive medicine.

Indexed as

Fertilization in VitroInflammationMachine LearningMicrobiotaVaginaAdultFemaleHumansMalePilot ProjectsPregnancyPregnancy Outcome

Identifiers

PMID40473637
PMCPMC12141462

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.