Cargando…
Diagnostic performance of an automated microscopy and pH test for diagnosis of vaginitis
Vaginitis is a common gynecological problem, nevertheless, its clinical evaluation is often insufficient. This study evaluated the performance of an automated microscope for the diagnosis of vaginitis, by comparison of the investigated test results to a composite reference standard (CRS) of wet moun...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102000/ https://www.ncbi.nlm.nih.gov/pubmed/37055473 http://dx.doi.org/10.1038/s41746-023-00815-w |
_version_ | 1785025609733242880 |
---|---|
author | Lev-Sagie, Ahinoam Strauss, Doris Ben Chetrit, Avraham |
author_facet | Lev-Sagie, Ahinoam Strauss, Doris Ben Chetrit, Avraham |
author_sort | Lev-Sagie, Ahinoam |
collection | PubMed |
description | Vaginitis is a common gynecological problem, nevertheless, its clinical evaluation is often insufficient. This study evaluated the performance of an automated microscope for the diagnosis of vaginitis, by comparison of the investigated test results to a composite reference standard (CRS) of wet mount microscopy performed by a specialist in vulvovaginal disorders, and related laboratory tests. During this single-site cross-sectional prospective study, 226 women reporting vaginitis symptoms were recruited, of which 192 samples were found interpretable and were assessed by the automated microscopy system. Results showed sensitivity between 84.1% (95%CI: 73.67–90.86%) for Candida albicans and 90.9% (95%CI: 76.43–96.86%) for bacterial vaginosis and specificity between 65.9% (95%CI: 57.11–73.64%) for Candida albicans and 99.4% (95%CI: 96.89–99.90%) for cytolytic vaginosis. These findings demonstrate the marked potential of machine learning-based automated microscopy and an automated pH test of vaginal swabs as a basis for a computer-aided suggested diagnosis, for improving the first-line evaluation of five different types of infectious and non-infectious vaginal disorders (vaginal atrophy, bacterial vaginosis, Candida albicans vaginitis, cytolytic vaginosis, and aerobic vaginitis/desquamative inflammatory vaginitis). Using such a tool will hopefully lead to better treatment, decrease healthcare costs, and improve patients’ quality of life. |
format | Online Article Text |
id | pubmed-10102000 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-101020002023-04-15 Diagnostic performance of an automated microscopy and pH test for diagnosis of vaginitis Lev-Sagie, Ahinoam Strauss, Doris Ben Chetrit, Avraham NPJ Digit Med Article Vaginitis is a common gynecological problem, nevertheless, its clinical evaluation is often insufficient. This study evaluated the performance of an automated microscope for the diagnosis of vaginitis, by comparison of the investigated test results to a composite reference standard (CRS) of wet mount microscopy performed by a specialist in vulvovaginal disorders, and related laboratory tests. During this single-site cross-sectional prospective study, 226 women reporting vaginitis symptoms were recruited, of which 192 samples were found interpretable and were assessed by the automated microscopy system. Results showed sensitivity between 84.1% (95%CI: 73.67–90.86%) for Candida albicans and 90.9% (95%CI: 76.43–96.86%) for bacterial vaginosis and specificity between 65.9% (95%CI: 57.11–73.64%) for Candida albicans and 99.4% (95%CI: 96.89–99.90%) for cytolytic vaginosis. These findings demonstrate the marked potential of machine learning-based automated microscopy and an automated pH test of vaginal swabs as a basis for a computer-aided suggested diagnosis, for improving the first-line evaluation of five different types of infectious and non-infectious vaginal disorders (vaginal atrophy, bacterial vaginosis, Candida albicans vaginitis, cytolytic vaginosis, and aerobic vaginitis/desquamative inflammatory vaginitis). Using such a tool will hopefully lead to better treatment, decrease healthcare costs, and improve patients’ quality of life. Nature Publishing Group UK 2023-04-13 /pmc/articles/PMC10102000/ /pubmed/37055473 http://dx.doi.org/10.1038/s41746-023-00815-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Lev-Sagie, Ahinoam Strauss, Doris Ben Chetrit, Avraham Diagnostic performance of an automated microscopy and pH test for diagnosis of vaginitis |
title | Diagnostic performance of an automated microscopy and pH test for diagnosis of vaginitis |
title_full | Diagnostic performance of an automated microscopy and pH test for diagnosis of vaginitis |
title_fullStr | Diagnostic performance of an automated microscopy and pH test for diagnosis of vaginitis |
title_full_unstemmed | Diagnostic performance of an automated microscopy and pH test for diagnosis of vaginitis |
title_short | Diagnostic performance of an automated microscopy and pH test for diagnosis of vaginitis |
title_sort | diagnostic performance of an automated microscopy and ph test for diagnosis of vaginitis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10102000/ https://www.ncbi.nlm.nih.gov/pubmed/37055473 http://dx.doi.org/10.1038/s41746-023-00815-w |
work_keys_str_mv | AT levsagieahinoam diagnosticperformanceofanautomatedmicroscopyandphtestfordiagnosisofvaginitis AT straussdoris diagnosticperformanceofanautomatedmicroscopyandphtestfordiagnosisofvaginitis AT benchetritavraham diagnosticperformanceofanautomatedmicroscopyandphtestfordiagnosisofvaginitis |