Evidence map›Paper›PMID 38659758›Full record

ArticleResearch square2024

Preoperative Vaginal Microbiome as a Predictor of Postoperative Urinary Tract Infection.

John A Occhino, Jenifer N Byrnes, Pei-Ying Wu, Marina R Walther-Antonio, Jun Chen

Open access · greenAbstract readPreprint
In one paragraph

Article in Research square, 2024. 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
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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 2 countries.

John A OcchinoMayo Clinic.
Jenifer N ByrnesMayo Clinic.
Pei-Ying WuNational Cheng Kung University Hospital, National Cheng Kung University.
Marina R Walther-AntonioMayo Clinic.
Jun ChenMayo Clinic.
WinnMed · USNational Cheng Kung University Hospital · TW

Funding

Use of microfluidic tumor cultures to enable clinical trials of therapies for ovarian cancerP50CA136393 · NCI · MAYO CLINIC ROCHESTER · PI ELLEN L. GOODE · 2009 to 2026
$37.0M
Institutional Career Development CoreKL2TR002379 · NCATS · MAYO CLINIC ROCHESTER · PI NILUFER ERTEKIN-TANER · 2017 to 2026
$14.9M
NCATS NIH HHS KL2 TR002379NCI NIH HHS P50 CA136393
6 · The paper itself

Abstract

This is a single Institute, prospective cohort study. We collected twenty- two postmenopausal women with pelvic organ prolapse planning to undergo vaginal hysterectomy with transvaginal pelvic reconstructive surgery, with or without a concomitant anti-incontinence procedure. Vaginal swabs and urine samples were longitudinally collected at five time points: preoperative consult visit (T1), day of surgery prior to surgical scrub (T2), immediately postoperative (T3), day of hospital discharge (T4), and at the postoperative exam visit (T5). Women experiencing urinary tract infection symptoms provided a sample set prior to antibiotic administration (T6). Microbiome analysis on vaginal and urinary specimens at each time point. Region V3-V5 of the 16S ribosomal RNA gene was amplified and sequenced. Sample DNA was analyzed with visit T1, T2, T5 and T6. Six (27.3%) participants developed postoperative urinary tract infection whose vaginal sample at first clinical visit (T1) revealed beta-diversity analysis with significant differences in microbiome structure and composition. Women diagnosed with a postoperative urinary tract infection had a vaginal microbiome characterized by low abundance of Lactobacillus and high prevalence of Prevotella and Gardnerella species. In our cohort, preoperative vaginal swabs can predict who will develop a urinary tract infection following transvaginal surgery for pelvic organ prolapse.

Identifiers

PMID38659758
PMCPMC11042435
OpenAlexW4394769438

What OpenQuestion holds

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LicenceCC BY
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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.