Evidence mapPaperPMID 40668382Full record

ArticleWorld journal of urology2025

AI-driven scientometric analysis with recency insights: lower urinary tract symptoms in older and frail populations.

Andries Van Huele, Jelle Demeulemeester, Karel Everaert, Mirko Petrovic, Patrick Calders, François Hervé, Adrian Wagg, George Bou Kheir

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Article in World journal of urology, 2025. 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.

No citing paper in PubMed yet.

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

8 authors.

Andries Van HueleDepartment of Urology, AZ Alma, Eeklo, Belgium. Andries.Vanhuele@ugent.be.
Jelle DemeulemeesterMynd-Ware, Vaartstraat 130, Kortrijk, Belgium.
Karel EveraertDepartment of Urology, Ghent University Hospital, Ghent, Belgium.
Mirko PetrovicDepartment of Geriatrics, Ghent University Hospital, Ghent, Belgium.
Patrick CaldersDepartment of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium.
François HervéDepartment of Urology, Ghent University Hospital, Ghent, Belgium.
Adrian WaggDivision of Geriatric Medicine, University of Alberta, Edmonton, AB, Canada.
George Bou KheirDepartment of Urology, Ghent University Hospital, Ghent, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThis artificial intelligence (AI)-driven scientometric analysis, conducted using the Mynd discovery platform, explores research trends in lower urinary tract symptoms (LUTS) among older patients. By applying its novel recency metric, the study identified emerging areas, longstanding research themes, and critical gaps in literature.

methodsMynd applies AI-driven scientometric analysis to map research trends in LUTS and frailty using PubMed abstracts. A total of 13,737 PubMed-indexed publications were analyzed. Through unsupervised topic modeling, Mynd extracts key terminology and builds hierarchical topic structures to enhance contextual understanding. Quantitative metrics-such as the novel recency metric-measure publication trends, categorizing topics as emerging, mainstream, declining, or hot. This approach enables data-driven insights into LUTS research in older persons.

resultsWhile research on LUTS has grown steadily since the 1980s, a decline in publication output has been observed since 2020. Geographical analysis reflects a shift in scientific prominence towards Asia. More in-depth analysis reveals a shift towards minimally invasive diagnostic methods, with a decline in research interest in invasive urodynamics. A similar pattern is observed in therapeutics. Frailty remains significantly underrepresented in literature, accounting for only 2.5% of the related studies, yet its high recency score indicates a rising focus.

conclusionThese insights underscore the evolving landscape of LUTS research, with growing attention to patient-centered, less invasive management strategies. However, major research gaps persist, particularly in the study of frail patients, necessitating further investigations to ensure evidence-based approaches tailored to aging populations.

Indexed as

Artificial IntelligenceFrail ElderlyFrailtyLower Urinary Tract SymptomsAgedHumansAdultElderFrailFrail olderLower urinary tract symptomsScientometrics

Identifiers

What Socratic 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 Socratic graph.