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A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery
BACKGROUND: Pelvic organ prolapse (POP) and stress urinary incontinence (SUI) are common conditions affecting women's health and quality of life. In 50% of cases, SUI occurs after POP surgery, which is called de novo SUI. Predicting the risk of de novo SUI is a complex multi-attribute decision-...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8451324/ https://www.ncbi.nlm.nih.gov/pubmed/34552451 http://dx.doi.org/10.1097/CU9.0000000000000035 |
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author | Moosavi, Seyyde Yalda Samad-Soltani, Taha Hajebrahimi, Sakineh |
author_facet | Moosavi, Seyyde Yalda Samad-Soltani, Taha Hajebrahimi, Sakineh |
author_sort | Moosavi, Seyyde Yalda |
collection | PubMed |
description | BACKGROUND: Pelvic organ prolapse (POP) and stress urinary incontinence (SUI) are common conditions affecting women's health and quality of life. In 50% of cases, SUI occurs after POP surgery, which is called de novo SUI. Predicting the risk of de novo SUI is a complex multi-attribute decision-making process. The current study made available a Decision Support System in the form of a fuzzy calculator web-based application to help surgeons predict the risk of de novo SUI. MATERIALS AND METHODS: We first identified 12 risk factors and the diagnostic criteria for de novo SUI by means of a systematic review of the literature. Then based upon an expert panel, all risk factors were prioritized. A set of 232 fuzzy rules for the prediction of de novo SUI was determined. A fuzzy expert system was developed using MATLAB software and Mamdani Inference System. The risk prediction model was then evaluated using retrospective data extracted from 30 randomly selected medical records of female patients over the age of 50 without symptoms of urinary incontinence who had undergone POP surgery. Finally, the proposed results of the predictive system were compared with the results of retrospective medical record data review. RESULTS: The results of this online calculator show that the accuracy of this risk prediction model, at more than 90%, compared favorably to other SUI risk prediction models. CONCLUSIONS: A fuzzy logic-based clinical Decision Support System in the form of an online calculator for calculating SUI prognosis after POP surgery in women can be helpful in predicting de novo SUI. |
format | Online Article Text |
id | pubmed-8451324 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-84513242021-09-21 A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery Moosavi, Seyyde Yalda Samad-Soltani, Taha Hajebrahimi, Sakineh Curr Urol Editor Recommendation BACKGROUND: Pelvic organ prolapse (POP) and stress urinary incontinence (SUI) are common conditions affecting women's health and quality of life. In 50% of cases, SUI occurs after POP surgery, which is called de novo SUI. Predicting the risk of de novo SUI is a complex multi-attribute decision-making process. The current study made available a Decision Support System in the form of a fuzzy calculator web-based application to help surgeons predict the risk of de novo SUI. MATERIALS AND METHODS: We first identified 12 risk factors and the diagnostic criteria for de novo SUI by means of a systematic review of the literature. Then based upon an expert panel, all risk factors were prioritized. A set of 232 fuzzy rules for the prediction of de novo SUI was determined. A fuzzy expert system was developed using MATLAB software and Mamdani Inference System. The risk prediction model was then evaluated using retrospective data extracted from 30 randomly selected medical records of female patients over the age of 50 without symptoms of urinary incontinence who had undergone POP surgery. Finally, the proposed results of the predictive system were compared with the results of retrospective medical record data review. RESULTS: The results of this online calculator show that the accuracy of this risk prediction model, at more than 90%, compared favorably to other SUI risk prediction models. CONCLUSIONS: A fuzzy logic-based clinical Decision Support System in the form of an online calculator for calculating SUI prognosis after POP surgery in women can be helpful in predicting de novo SUI. Lippincott Williams & Wilkins 2021-09 2021-08-09 /pmc/articles/PMC8451324/ /pubmed/34552451 http://dx.doi.org/10.1097/CU9.0000000000000035 Text en Copyright © 2021 The Authors. Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
spellingShingle | Editor Recommendation Moosavi, Seyyde Yalda Samad-Soltani, Taha Hajebrahimi, Sakineh A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery |
title | A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery |
title_full | A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery |
title_fullStr | A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery |
title_full_unstemmed | A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery |
title_short | A web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery |
title_sort | web-based fuzzy risk predictive-decision model of de novo stress urinary incontinence in women undergoing pelvic organ prolapse surgery |
topic | Editor Recommendation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8451324/ https://www.ncbi.nlm.nih.gov/pubmed/34552451 http://dx.doi.org/10.1097/CU9.0000000000000035 |
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