Evidence map›Paper›PMID 40991055›Full record

Trial reportLasers in medical science2025

Efficacy of non-ablative vaginal erbium laser for rUTI prevention in postmenopausal women.

Jiqiong Zheng, Minyan Li, Yezi Chen, Zhengwang Zhang

Abstract readRandomized Controlled Trial
PubMed Publisher
In one paragraph

Trial report in Lasers in medical science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

4 authors.

Jiqiong ZhengDepartment of Urology, Huadong Hospital affiliated to Fudan University, Shanghai, China.
Minyan LiInternational Healthcare Center, Yuanyi Clinic, Sir Run Run Shaw Hospital, Hangzhou, China.
Yezi ChenInternational Healthcare Center, Yuanyi Clinic, Sir Run Run Shaw Hospital, Hangzhou, China.
Zhengwang ZhangDepartment of Urology, Huadong Hospital affiliated to Fudan University, Shanghai, China. zhengwang_zhang@fudan.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To evaluate the effect of vaginal erbium laser (VEL) for recurrent urinary tract infection (rUTI) prevention in postmenopausal women (PMW). 80 PMW with past histories of rUTI were recruited and randomized into local estrogen therapy (LET) or VEL group. The LET group was prescribed 12 weeks of vaginal estrogen, while treatment in the VEL group consisted of three VEL sessions at a 30-day interval. Primary outcomes were the number of UTI episodes and the percentage of cured and improved participants. Vaginal pH, lactobacillus flora, and vaginal health index score (VHIS) were assessed as secondary outcomes. The actual number of cumulative UTI episodes in VEL and LET were significantly lower than predictive numbers. No significant difference was found in the percentages of cured and improved participants between the two groups. Persistent improvement of vaginal health was observed in VEL. Only 54.8% of participants in LET still maintained vaginal lactobacillus predominance at the follow-up endpoint compared with 93.3% in VEL (p = 0.002). Consistently and significantly lower vaginal pH and higher VHIS scores were observed in VEL compared to LET at the same time-points. In comparison to vaginal estrogen, VEL showed a non-inferior and more sustained effect for rUTI prevention in PMW.

Indexed as

Lasers, Solid-StateUrinary Tract InfectionsVaginaAgedEstrogensFemaleHumansLactobacillusMiddle AgedPostmenopauseTreatment OutcomeEstrogensGenitourinary syndrome of menopauseLocal estrogen therapyPostmenopausal womenUrinary tract infectionVaginal erbium laser

Identifiers

What OpenQuestion holds

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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.