Evidence map›Paper›PMID 34045577›Full record

ArticleScientific reports2021

Mobile sonouroflowmetry using voiding sound and volume.

Elie El Helou, Joy Naba, Karim Youssef, Georges Mjaess, Ghassan Sleilaty, Samar Helou

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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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

8 citing papers in PubMed.

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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

6 authors.

Elie El HelouFaculty of Medicine, Saint Joseph University, Beirut, Lebanon. elie.helou@usj.edu.lb.
Joy NabaFaculty of Medicine, Saint Joseph University, Beirut, Lebanon.
Karim YoussefCollege of Engineering and Technology, American University of the Middle East, Egaila, Kuwait.
Georges MjaessFaculty of Medicine, Saint Joseph University, Beirut, Lebanon.
Ghassan SleilatyFaculty of Medicine, Saint Joseph University, Beirut, Lebanon.
Samar HelouGlobal Center for Medical Engineering and Informatics, Osaka University, Osaka, Japan. samar@bpe.es.osaka-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Uroflowmetry (UF) is a common clinic-based non-invasive test to diagnose Lower Urinary Tract Dysfunction (LUTD). Accurate home-based uroflowmetry methods are needed to conveniently conduct repeated uroflowmetries when patients are physiologically ready to urinate. To this end, we propose and evaluate a novel mobile sonouroflowmetry (SUF) method that estimates the urinary flow rate from a sound signal recorded using a mobile phone. By linearly mapping the total sound energy to the total voided volume, the sound energy curve is transformed to a flow rate curve allowing the estimation of the flow rate over time. An evaluation using data from 44 healthy young men showed high similarity between the UF and SUF flow rates with a mixed-effects model correlation coefficient of 0.993 and a mean root mean square error of 2.37 ml/s. Maximum flow rates were estimated with an average absolute error of 2.41 ml/s. Future work on mobile uroflowmetry can use these results as an initial benchmark for flow rate estimation accuracy.

Indexed as

Diagnostic Techniques, UrologicalAdultHumansLower Urinary Tract SymptomsMaleMiddle AgedSoundUrinary BladderUrinationUrodynamicsYoung Adult

Identifiers

PMID34045577
PMCPMC8159949

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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.