Evidence map›Paper›PMID 34796252›Full record

ArticleAmerican journal of clinical and experimental urology2021

Irregular bladder shapes identified in women with overactive bladder: an ultrasound nomogram.

Rui Li, Anna S Nagle, Kaitlyn M Maddra, Naomi Vinod, Suzanne A Prince, Sarah I Tensen, Devina Thapa, Blessan Sebastian, Dhruv Sethi, Abraham Alattar and 3 more

Abstract read
In one paragraph

Article in American journal of clinical and experimental urology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. 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

13 authors.

Rui LiDepartment of Mechanical and Nuclear Engineering, Virginia Commonwealth University College of Engineering Richmond 23284, VA, USA.
Anna S NagleDepartment of Mechanical and Nuclear Engineering, Virginia Commonwealth University College of Engineering Richmond 23284, VA, USA.
Kaitlyn M MaddraDepartment of Surgery, Division of Urology, Virginia Commonwealth University School of Medicine Richmond 23298, VA, USA.
Naomi VinodDepartment of Surgery, Division of Urology, Virginia Commonwealth University School of Medicine Richmond 23298, VA, USA.
Suzanne A PrinceDepartment of Mechanical and Nuclear Engineering, Virginia Commonwealth University College of Engineering Richmond 23284, VA, USA.
Sarah I TensenDepartment of Mechanical and Nuclear Engineering, Virginia Commonwealth University College of Engineering Richmond 23284, VA, USA.
Devina ThapaDepartment of Surgery, Division of Urology, Virginia Commonwealth University School of Medicine Richmond 23298, VA, USA.
Blessan SebastianDepartment of Surgery, Division of Urology, Virginia Commonwealth University School of Medicine Richmond 23298, VA, USA.
Dhruv SethiDepartment of Surgery, Division of Urology, Virginia Commonwealth University School of Medicine Richmond 23298, VA, USA.
Abraham AlattarDepartment of Mechanical and Nuclear Engineering, Virginia Commonwealth University College of Engineering Richmond 23284, VA, USA.
Laura R CarucciDepartment of Radiology, Virginia Commonwealth University School of Medicine Richmond 23298, VA, USA.
Adam P KlausnerDepartment of Surgery, Division of Urology, Virginia Commonwealth University School of Medicine Richmond 23298, VA, USA.
John E SpeichDepartment of Mechanical and Nuclear Engineering, Virginia Commonwealth University College of Engineering Richmond 23284, VA, USA.

Funding

The Detrusor Tension Sensor: A Model for Novel Cystometrics in Overactive BladderR01DK101719 · NIDDK · VIRGINIA COMMONWEALTH UNIVERSITY · PI KLAUSNER, ADAM PHILIP, SPEICH, JOHN E · 2015 to 2023
$2.4M
NIDDK NIH HHS R01 DK101719
6 · The paper itself

Abstract

In this study, an ultrasound-based bladder shape nomogram was developed using data from women without overactive bladder (OAB) and tested in women with OAB to identify irregular bladder shapes. The goal was development of a nomogram that can ultimately be used for non-invasive identification of a bladder shape-associated OAB phenotype. Transabdominal 3-dimensional (3D) bladder ultrasound images were collected at 1-minute intervals during urodynamics studies and at 5-10-minute intervals during oral hydration studies. These prospective studies enrolled women with and without OAB based on International Consultation on Incontinence questionnaire on OAB (ICIq-OAB) question 5a (OAB 5a≥2, without OAB 5a<2). Bladder perimeters were manually traced and refined using GE 4D-View software. Nomograms for the transverse, sagittal and coronal perimeter-volume relationships were developed for women without OAB. A power model was used to approximate upper and lower nomogram bounds with 95% confidence intervals. Nomograms were tested using data from women with OAB, and each participant was classified as having an irregular bladder shape based on the number of perimeter values outside the nomogram bounds. Nomograms were developed using 533 images from 27 women without OAB (14 from urodynamics and 13 from hydration studies) and were tested using 264 images from 24 women with OAB (16 urodynamics and 8 hydration). The sagittal perimeter nomogram provided the best results, with irregular sagittal perimeters identified in 6/24 (25%) women with OAB and 0/27 (0%) without OAB. An irregular sagittal perimeter was significantly associated with OAB (P<0.05). Ultrasound-based nomograms may enable feasible, non-invasive identification of a subgroup of women with bladder shape-associated OAB.

Indexed as

lower urinary tract symptomsphenotypeultrasound imagingUrodynamics

Identifiers

PMID34796252
PMCPMC8595087

What OpenQuestion 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 OpenQuestion graph.