Cargando…

Predictors of pelvic pain in a general urology clinic population

OBJECTIVES: To assess the prevalence and predictors of chronic pelvic pain in a general urology population presenting for evaluation of unrelated non‐painful complaints. Generalized pelvic pain is estimated to afflict between 6% and 26% of women and is often multifactorial in aetiology. A paucity of...

Descripción completa

Detalles Bibliográficos
Autores principales: Prillaman, Grace, Zillioux, Jacqueline, Beller, Haerin, Yeaman, Clinton, Rapp, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560618/
https://www.ncbi.nlm.nih.gov/pubmed/37818032
http://dx.doi.org/10.1002/bco2.262
_version_ 1785117763170205696
author Prillaman, Grace
Zillioux, Jacqueline
Beller, Haerin
Yeaman, Clinton
Rapp, David
author_facet Prillaman, Grace
Zillioux, Jacqueline
Beller, Haerin
Yeaman, Clinton
Rapp, David
author_sort Prillaman, Grace
collection PubMed
description OBJECTIVES: To assess the prevalence and predictors of chronic pelvic pain in a general urology population presenting for evaluation of unrelated non‐painful complaints. Generalized pelvic pain is estimated to afflict between 6% and 26% of women and is often multifactorial in aetiology. A paucity of prospective research exists to characterize chronic pelvic pain patterns and to understand related predictors. MATERIALS AND METHODS: This is a prospective, cross‐sectional survey‐based study of female patients presenting to a general urology clinic over a 10‐month period (7/2018–5/2019). Patients completed a 32‐item survey with questions pertaining to demographics, comorbidities and chronic pelvic pain characteristics. Comparison tests (chi‐squared, Fisher's exact) and stepwise multivariable logistic modelling were performed to assess for predictors of chronic pelvic pain. RESULTS: A total of 181 women completed the survey, with a mean age of 56 years. Overall, 75 (41%) women reported chronic pelvic pain. Those with chronic pelvic pain were younger compared to those without (52 vs 59 years, p = 0.001). Univariable logistic regression analysis identified BMI, depression, fibromyalgia, overactive bladder and any bowel symptoms as possible positive predictors of chronic pelvic pain. Final best‐fit multivariable model found overactive bladder, fibromyalgia and presence of bowel symptoms as independent positive predictors of chronic pelvic pain. CONCLUSIONS: Our study is one of the few studies that has prospectively analysed chronic pelvic pain and its predictors. The present study identified significant associations with overactive bladder, fibromyalgia and bowel symptoms. Further research is needed to better understand the aetiologies of chronic pelvic pain and the possible relationship with identified clinical predictors.
format Online
Article
Text
id pubmed-10560618
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-105606182023-10-10 Predictors of pelvic pain in a general urology clinic population Prillaman, Grace Zillioux, Jacqueline Beller, Haerin Yeaman, Clinton Rapp, David BJUI Compass Original Articles OBJECTIVES: To assess the prevalence and predictors of chronic pelvic pain in a general urology population presenting for evaluation of unrelated non‐painful complaints. Generalized pelvic pain is estimated to afflict between 6% and 26% of women and is often multifactorial in aetiology. A paucity of prospective research exists to characterize chronic pelvic pain patterns and to understand related predictors. MATERIALS AND METHODS: This is a prospective, cross‐sectional survey‐based study of female patients presenting to a general urology clinic over a 10‐month period (7/2018–5/2019). Patients completed a 32‐item survey with questions pertaining to demographics, comorbidities and chronic pelvic pain characteristics. Comparison tests (chi‐squared, Fisher's exact) and stepwise multivariable logistic modelling were performed to assess for predictors of chronic pelvic pain. RESULTS: A total of 181 women completed the survey, with a mean age of 56 years. Overall, 75 (41%) women reported chronic pelvic pain. Those with chronic pelvic pain were younger compared to those without (52 vs 59 years, p = 0.001). Univariable logistic regression analysis identified BMI, depression, fibromyalgia, overactive bladder and any bowel symptoms as possible positive predictors of chronic pelvic pain. Final best‐fit multivariable model found overactive bladder, fibromyalgia and presence of bowel symptoms as independent positive predictors of chronic pelvic pain. CONCLUSIONS: Our study is one of the few studies that has prospectively analysed chronic pelvic pain and its predictors. The present study identified significant associations with overactive bladder, fibromyalgia and bowel symptoms. Further research is needed to better understand the aetiologies of chronic pelvic pain and the possible relationship with identified clinical predictors. John Wiley and Sons Inc. 2023-07-01 /pmc/articles/PMC10560618/ /pubmed/37818032 http://dx.doi.org/10.1002/bco2.262 Text en © 2023 The Authors. BJUI Compass published by John Wiley & Sons Ltd on behalf of BJU International Company. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Prillaman, Grace
Zillioux, Jacqueline
Beller, Haerin
Yeaman, Clinton
Rapp, David
Predictors of pelvic pain in a general urology clinic population
title Predictors of pelvic pain in a general urology clinic population
title_full Predictors of pelvic pain in a general urology clinic population
title_fullStr Predictors of pelvic pain in a general urology clinic population
title_full_unstemmed Predictors of pelvic pain in a general urology clinic population
title_short Predictors of pelvic pain in a general urology clinic population
title_sort predictors of pelvic pain in a general urology clinic population
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10560618/
https://www.ncbi.nlm.nih.gov/pubmed/37818032
http://dx.doi.org/10.1002/bco2.262
work_keys_str_mv AT prillamangrace predictorsofpelvicpaininageneralurologyclinicpopulation
AT zilliouxjacqueline predictorsofpelvicpaininageneralurologyclinicpopulation
AT bellerhaerin predictorsofpelvicpaininageneralurologyclinicpopulation
AT yeamanclinton predictorsofpelvicpaininageneralurologyclinicpopulation
AT rappdavid predictorsofpelvicpaininageneralurologyclinicpopulation