Evidence map›Paper›PMID 32638096›Full record

SynthesisArchives of gynecology and obstetrics2020

The association between vaginal microbiota and female infertility: a systematic review and meta-analysis.

Xiang Hong, Jun Ma, Jiechen Yin, Shenghao Fang, Jia Geng, Hongxia Zhao, Mengwen Zhu, Meng Ye, Xiaoyue Zhu, Yan Xuan and 1 more

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Archives of gynecology and obstetrics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
3.8field-weighted citation impact, top 6% 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

28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 51 citations in OpenAlex.

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  4. Nutrients · 2025
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  19. Effect ofMicroorganisms · 2023
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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

11 authors at 2 institutions in 2 countries.

Xiang HongKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 dingjiaqiao road, gulou district, Nanjing, 210009, Jiangsu, China.
Jun MaKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 dingjiaqiao road, gulou district, Nanjing, 210009, Jiangsu, China.
Jiechen YinKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 dingjiaqiao road, gulou district, Nanjing, 210009, Jiangsu, China.
Shenghao FangMount Sinai Health System, New York, NY, USA.
Jia GengKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 dingjiaqiao road, gulou district, Nanjing, 210009, Jiangsu, China.
Hongxia ZhaoKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 dingjiaqiao road, gulou district, Nanjing, 210009, Jiangsu, China.
Mengwen ZhuKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 dingjiaqiao road, gulou district, Nanjing, 210009, Jiangsu, China.
Meng YeKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 dingjiaqiao road, gulou district, Nanjing, 210009, Jiangsu, China.
Xiaoyue ZhuKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 dingjiaqiao road, gulou district, Nanjing, 210009, Jiangsu, China.
Yan XuanKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 dingjiaqiao road, gulou district, Nanjing, 210009, Jiangsu, China.
Bei WangKey Laboratory of Environmental Medicine and Engineering of Ministry of Education, Department of Epidemiology and Health Statistics, School of Public Health, Southeast University, No. 87 dingjiaqiao road, gulou district, Nanjing, 210009, Jiangsu, China. wangbeilxb@163.com.ORCID http://orcid.org/0000-0002-5232-0933
Southeast University · CNMount Sinai Health System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis study aimed to explore the association between vaginal microbiota and infertility.

methodsWe searched a range of electronic databases for appropriate articles, including PubMed, Web of Science, Embase, Chinese National Knowledge Infrastructure (CNKI), and Wanfang, from inception to 8th September 2019. Identified articles were then screened using strict inclusion and exclusion criteria. By referring to Tamarelle's method, we divided vaginal microbiota into two categories: low-Lactobacillus vaginal microbiota (LL-VMB) and high-Lactobacillus vaginal microbiota (HL-VMB). Patients were defined as HL-VMB if they had a Nugent score of 0-3, a negative Amesel/Spiegel's test, or if the vaginal community status was dominated by either L. crispatus, L. iners, L. gasseri and L. jensenii via 16S rRNA sequencing. Otherwise, cases were regarded as LL-VMB. Statistical analyses were performed with STATA 13.0 statistical software. Effect estimates are presented as odds ratios (ORs) with 95% confidence intervals (CIs).

resultsFifteen articles were included in our final analysis. The HL-VMB was negatively related to infertility; a fixed model showed that the pooled OR was 0.83 (95% CI 0.77-0.90). There was no significant publication bias, as determined by Begg's test (P = 0.488) and Egger's test (P = 0.652). Using a random effect model, the pooled OR for intermediate bacterial vaginitis (BV) and infertility was 1.39 (95% CI 1.10-1.76) and the pooled OR for positive BV was 1.72 (95% CI 1.10-2.69). Subgroup and sensitivity analyses further demonstrated that the associations identified were stable. However, the acquired evidence was not sufficient to make inferences with regards to the mechanisms underlying these relationships.

conclusionThis systematic review and meta-analysis identified a negative correlation between HL-VMB and female infertility. However, due to a variety of limitations, the evidence acquired does not allow us to identify the specific mechanisms underlying this association. Further high-quality studies are needed to verify the causal relationship and explore the molecular mechanisms involved.

Indexed as

FemaleHumansInfertility, FemaleLactobacillusMicrobiotaRNA, Ribosomal, 16SVaginaVaginosis, BacterialRNA, Ribosomal, 16SInfertilityMeta-analysisVaginal microbiomeVaginal microbiota

Identifiers

PMID32638096
OpenAlexW3041545842

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.