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Performance evaluation of automated urine microscopy as a rapid, non-invasive approach for the diagnosis of non-gonococcal urethritis
OBJECTIVES: Gram-stained urethral smear (GSUS), the standard point-of-care test for non-gonococcal urethritis (NGU) is operator dependent and poorly specific. The performance of rapid automated urine flow cytometry (AUFC) of first void urine (FVU) white cell counts (UWCC) for predicting Mycoplasma g...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4413809/ https://www.ncbi.nlm.nih.gov/pubmed/25614466 http://dx.doi.org/10.1136/sextrans-2014-051761 |
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author | Pond, Marcus J Nori, Achyuta V Patel, Sheel Laing, Ken Ajayi, Margarita Copas, Andrew J Butcher, Philip D Hay, Phillip Sadiq, Syed Tariq |
author_facet | Pond, Marcus J Nori, Achyuta V Patel, Sheel Laing, Ken Ajayi, Margarita Copas, Andrew J Butcher, Philip D Hay, Phillip Sadiq, Syed Tariq |
author_sort | Pond, Marcus J |
collection | PubMed |
description | OBJECTIVES: Gram-stained urethral smear (GSUS), the standard point-of-care test for non-gonococcal urethritis (NGU) is operator dependent and poorly specific. The performance of rapid automated urine flow cytometry (AUFC) of first void urine (FVU) white cell counts (UWCC) for predicting Mycoplasma genitalium and Chlamydia trachomatis urethral infections was assessed and its application to asymptomatic infection was evaluated. METHODS: Receiver operating characteristic curve analysis, determining FVU-UWCC threshold for predicting M. genitalium or C. trachomatis infection was performed on 208 ‘training’ samples from symptomatic patients and subsequently validated using 228 additional FVUs obtained from prospective unselected patients. RESULTS: An optimal diagnostic threshold of >29 UWC/µL gave sensitivities and specificities for either infection of 81.5% (95% CI 65.1% to 91.6%) and 85.8% (79.5% to 90.4%), respectively, compared with 86.8% (71.1% to 95%) and 64.7% (56.9% to 71.7%), respectively, for GSUS, using the training set samples. FVU-UWCC demonstrated sensitivities and specificities of 69.2% (95% CI 48.1% to 84.9%) and 92% (87.2% to 95.2%), respectively, when using validation samples. In asymptomatic patients where GSUS was not used, AUFC would have enabled more infections to be detected compared with clinical considerations only (71.4% vs 28.6%; p=0.03). The correlation between UWCC and bacterial load was stronger for M. genitalium compared with C. trachomatis (τ=0.426, p≤0.001 vs τ=0.295, p=0.022, respectively). CONCLUSIONS: AUFC offers improved specificity over microscopy for predicting C. trachomatis or M. genitalium infection. Universal AUFC may enable non-invasive diagnosis of asymptomatic NGU at the PoC. The degree of urethral inflammation exhibits a stronger association with pathogen load for M. genitalium compared with C. trachomatis. |
format | Online Article Text |
id | pubmed-4413809 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-44138092015-05-11 Performance evaluation of automated urine microscopy as a rapid, non-invasive approach for the diagnosis of non-gonococcal urethritis Pond, Marcus J Nori, Achyuta V Patel, Sheel Laing, Ken Ajayi, Margarita Copas, Andrew J Butcher, Philip D Hay, Phillip Sadiq, Syed Tariq Sex Transm Infect Basic Science OBJECTIVES: Gram-stained urethral smear (GSUS), the standard point-of-care test for non-gonococcal urethritis (NGU) is operator dependent and poorly specific. The performance of rapid automated urine flow cytometry (AUFC) of first void urine (FVU) white cell counts (UWCC) for predicting Mycoplasma genitalium and Chlamydia trachomatis urethral infections was assessed and its application to asymptomatic infection was evaluated. METHODS: Receiver operating characteristic curve analysis, determining FVU-UWCC threshold for predicting M. genitalium or C. trachomatis infection was performed on 208 ‘training’ samples from symptomatic patients and subsequently validated using 228 additional FVUs obtained from prospective unselected patients. RESULTS: An optimal diagnostic threshold of >29 UWC/µL gave sensitivities and specificities for either infection of 81.5% (95% CI 65.1% to 91.6%) and 85.8% (79.5% to 90.4%), respectively, compared with 86.8% (71.1% to 95%) and 64.7% (56.9% to 71.7%), respectively, for GSUS, using the training set samples. FVU-UWCC demonstrated sensitivities and specificities of 69.2% (95% CI 48.1% to 84.9%) and 92% (87.2% to 95.2%), respectively, when using validation samples. In asymptomatic patients where GSUS was not used, AUFC would have enabled more infections to be detected compared with clinical considerations only (71.4% vs 28.6%; p=0.03). The correlation between UWCC and bacterial load was stronger for M. genitalium compared with C. trachomatis (τ=0.426, p≤0.001 vs τ=0.295, p=0.022, respectively). CONCLUSIONS: AUFC offers improved specificity over microscopy for predicting C. trachomatis or M. genitalium infection. Universal AUFC may enable non-invasive diagnosis of asymptomatic NGU at the PoC. The degree of urethral inflammation exhibits a stronger association with pathogen load for M. genitalium compared with C. trachomatis. BMJ Publishing Group 2015-05 2015-01-22 /pmc/articles/PMC4413809/ /pubmed/25614466 http://dx.doi.org/10.1136/sextrans-2014-051761 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Basic Science Pond, Marcus J Nori, Achyuta V Patel, Sheel Laing, Ken Ajayi, Margarita Copas, Andrew J Butcher, Philip D Hay, Phillip Sadiq, Syed Tariq Performance evaluation of automated urine microscopy as a rapid, non-invasive approach for the diagnosis of non-gonococcal urethritis |
title | Performance evaluation of automated urine microscopy as a rapid, non-invasive approach for the diagnosis of non-gonococcal urethritis |
title_full | Performance evaluation of automated urine microscopy as a rapid, non-invasive approach for the diagnosis of non-gonococcal urethritis |
title_fullStr | Performance evaluation of automated urine microscopy as a rapid, non-invasive approach for the diagnosis of non-gonococcal urethritis |
title_full_unstemmed | Performance evaluation of automated urine microscopy as a rapid, non-invasive approach for the diagnosis of non-gonococcal urethritis |
title_short | Performance evaluation of automated urine microscopy as a rapid, non-invasive approach for the diagnosis of non-gonococcal urethritis |
title_sort | performance evaluation of automated urine microscopy as a rapid, non-invasive approach for the diagnosis of non-gonococcal urethritis |
topic | Basic Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4413809/ https://www.ncbi.nlm.nih.gov/pubmed/25614466 http://dx.doi.org/10.1136/sextrans-2014-051761 |
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