Evidence map›Paper›PMID 36900130›Full record

ArticleDiagnostics (Basel, Switzerland)2023

A High-Efficiency Consultation Improves Urological Diagnosis in Patients with Complex LUTS-A Pilot Study.

Alexandru Ciudin, Bernat Padulles, Pasqualino Manasia, Josep Alcoberro, Sanae Ounia, Maria Lopez, Natalia Allue, Joan Maria Ferrer, Jaume Duran, Antonio Aguilar

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Article in Diagnostics (Basel, Switzerland), 2023. 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. Article
  2. Article
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

10 authors.

Alexandru CiudinUrology Department, Hospital Universitari de Mollet, 08100 Barcelona, Spain.ORCID 0000-0002-0091-9688
Bernat PadullesUrology Department, Hospital Universitari de Mollet, 08100 Barcelona, Spain.
Pasqualino ManasiaUrology Department, Hospital Universitari de Mollet, 08100 Barcelona, Spain.
Josep AlcoberroUrology Department, Hospital Universitari de Mollet, 08100 Barcelona, Spain.
Sanae OuniaUrology Department, Hospital Universitari de Mollet, 08100 Barcelona, Spain.
Maria LopezUrology Department, Hospital Universitari de Mollet, 08100 Barcelona, Spain.
Natalia AllueHospital Management, Hospital Universitari de Mollet, 08100 Barcelona, Spain.
Joan Maria FerrerHospital Management, Hospital Universitari de Mollet, 08100 Barcelona, Spain.ORCID 0000-0003-1264-6290
Jaume DuranHospital Management, Hospital Universitari de Mollet, 08100 Barcelona, Spain.
Antonio AguilarUrology Department, Hospital Universitari de Mollet, 08100 Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

(1) Background: The diagnosis of moderate-severe lower urinary tract symptoms (LUTS) is not easy due to the complexity of the micturition act. Sequential diagnostic tests can be time consuming due to waiting lists. Thus, we developed a diagnostic model combining all the tests in a single one-stop consultation. (2) Methods: In a prospective pilot study in patients with complex LUTS, they received all diagnostic tests (ultrasound, uroflowmetry, cystoscopy, pressure-flow study) in a single consultation and by the same doctor. Patients' results were compared with those from a 2021 paired cohort that underwent the classical sequential diagnostic pathway. (3) Results: Per patient, the high-efficiency consultation saved: 175 days of waiting, 60 min doctor time and 120 nursing assistant time and over 300 euros on average. The intervention also saved 120 patient journeys to the hospital, lowering the total carbon footprint by 145.86 kg CO

Indexed as

cystoscopydiagnosticsLUTSpressure-flow studytime to diagnosisultrasounduroflowmetrywaiting list

Identifiers

PMID36900130
PMCPMC10000410

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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.