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Transvaginal ultrasonography predictive model for the detection of pelvic congestion syndrome

BACKGROUND: The diagnosis of pelvic congestion syndrome (PCS) remains a challenge given the lack of universally accepted criteria. Although venography (VG) is the current gold standard for the diagnosis of PCS, non-invasive techniques like transvaginal ultrasonography (TVU) appear to be a valid alte...

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Autores principales: Garcia-Jimenez, Rocio, Valero, Irene, Borrero, Carlota, Garcia-Mejido, Jose A., Gonzalez-Herraez, Jose V., Muñoz-Chimbo, Andrea V., Pelayo-Delgado, Irene, Fernandez-Palacin, Ana, Sainz Bueno, Jose A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240031/
https://www.ncbi.nlm.nih.gov/pubmed/37284115
http://dx.doi.org/10.21037/qims-22-898
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author Garcia-Jimenez, Rocio
Valero, Irene
Borrero, Carlota
Garcia-Mejido, Jose A.
Gonzalez-Herraez, Jose V.
Muñoz-Chimbo, Andrea V.
Pelayo-Delgado, Irene
Fernandez-Palacin, Ana
Sainz Bueno, Jose A.
author_facet Garcia-Jimenez, Rocio
Valero, Irene
Borrero, Carlota
Garcia-Mejido, Jose A.
Gonzalez-Herraez, Jose V.
Muñoz-Chimbo, Andrea V.
Pelayo-Delgado, Irene
Fernandez-Palacin, Ana
Sainz Bueno, Jose A.
author_sort Garcia-Jimenez, Rocio
collection PubMed
description BACKGROUND: The diagnosis of pelvic congestion syndrome (PCS) remains a challenge given the lack of universally accepted criteria. Although venography (VG) is the current gold standard for the diagnosis of PCS, non-invasive techniques like transvaginal ultrasonography (TVU) appear to be a valid alternative. The aim of this study was to design a predictive model for the venographic diagnostic of PCS using the parameters identified by TVU in patients with clinical suspicion of PCS, in order to individually assess the need to perform an invasive diagnostic and therapeutic technique such as VG. METHODS: An observational and cross-sectional prospective study was conducted including 61 consecutively recruited patients with clinical suspicion of PCS, who were referred by the Pelvic Floor, Gynecology and Vascular Surgery Units, who were distributed in two groups: 18 belonging to the normal group and 43 to the PCS’s group. We implemented and compared 19 binary logistic regression models, including the parameters that showed statistical significance in the prior univariate analysis. We evaluated individual predictive values with a receiver operating characteristic (ROC) curve and the area under the curve (AUC). RESULTS: The selected model, based on the presence of pelvic veins or venous plexus of 8 mm or larger, observed by transvaginal ultrasound, had an AUC of 0.79 (95% CI: 0.63–0.96; P<0.001), with a sensitivity of 0.90 and specificity of 0.69, while the VG had a sensitivity of 86.05%, a specificity of 66.67%, and a positive predictive value of 86.05%. CONCLUSIONS: This assessment presents a feasible alternative that could potentially be added to our usual gynecological practice.
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spelling pubmed-102400312023-06-06 Transvaginal ultrasonography predictive model for the detection of pelvic congestion syndrome Garcia-Jimenez, Rocio Valero, Irene Borrero, Carlota Garcia-Mejido, Jose A. Gonzalez-Herraez, Jose V. Muñoz-Chimbo, Andrea V. Pelayo-Delgado, Irene Fernandez-Palacin, Ana Sainz Bueno, Jose A. Quant Imaging Med Surg Original Article BACKGROUND: The diagnosis of pelvic congestion syndrome (PCS) remains a challenge given the lack of universally accepted criteria. Although venography (VG) is the current gold standard for the diagnosis of PCS, non-invasive techniques like transvaginal ultrasonography (TVU) appear to be a valid alternative. The aim of this study was to design a predictive model for the venographic diagnostic of PCS using the parameters identified by TVU in patients with clinical suspicion of PCS, in order to individually assess the need to perform an invasive diagnostic and therapeutic technique such as VG. METHODS: An observational and cross-sectional prospective study was conducted including 61 consecutively recruited patients with clinical suspicion of PCS, who were referred by the Pelvic Floor, Gynecology and Vascular Surgery Units, who were distributed in two groups: 18 belonging to the normal group and 43 to the PCS’s group. We implemented and compared 19 binary logistic regression models, including the parameters that showed statistical significance in the prior univariate analysis. We evaluated individual predictive values with a receiver operating characteristic (ROC) curve and the area under the curve (AUC). RESULTS: The selected model, based on the presence of pelvic veins or venous plexus of 8 mm or larger, observed by transvaginal ultrasound, had an AUC of 0.79 (95% CI: 0.63–0.96; P<0.001), with a sensitivity of 0.90 and specificity of 0.69, while the VG had a sensitivity of 86.05%, a specificity of 66.67%, and a positive predictive value of 86.05%. CONCLUSIONS: This assessment presents a feasible alternative that could potentially be added to our usual gynecological practice. AME Publishing Company 2023-05-15 2023-06-01 /pmc/articles/PMC10240031/ /pubmed/37284115 http://dx.doi.org/10.21037/qims-22-898 Text en 2023 Quantitative Imaging in Medicine and Surgery. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Garcia-Jimenez, Rocio
Valero, Irene
Borrero, Carlota
Garcia-Mejido, Jose A.
Gonzalez-Herraez, Jose V.
Muñoz-Chimbo, Andrea V.
Pelayo-Delgado, Irene
Fernandez-Palacin, Ana
Sainz Bueno, Jose A.
Transvaginal ultrasonography predictive model for the detection of pelvic congestion syndrome
title Transvaginal ultrasonography predictive model for the detection of pelvic congestion syndrome
title_full Transvaginal ultrasonography predictive model for the detection of pelvic congestion syndrome
title_fullStr Transvaginal ultrasonography predictive model for the detection of pelvic congestion syndrome
title_full_unstemmed Transvaginal ultrasonography predictive model for the detection of pelvic congestion syndrome
title_short Transvaginal ultrasonography predictive model for the detection of pelvic congestion syndrome
title_sort transvaginal ultrasonography predictive model for the detection of pelvic congestion syndrome
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10240031/
https://www.ncbi.nlm.nih.gov/pubmed/37284115
http://dx.doi.org/10.21037/qims-22-898
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