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Phenotyping chronic tinnitus patients using self-report questionnaire data: cluster analysis and visual comparison
Chronic tinnitus is a complex, multi-factorial symptom that requires careful assessment and management. Evidence-based therapeutic approaches involve audiological and psychological treatment components. However, not everyone benefits from treatment. The identification and characterisation of patient...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532444/ https://www.ncbi.nlm.nih.gov/pubmed/33009468 http://dx.doi.org/10.1038/s41598-020-73402-8 |
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author | Niemann, Uli Brueggemann, Petra Boecking, Benjamin Mebus, Wilhelm Rose, Matthias Spiliopoulou, Myra Mazurek, Birgit |
author_facet | Niemann, Uli Brueggemann, Petra Boecking, Benjamin Mebus, Wilhelm Rose, Matthias Spiliopoulou, Myra Mazurek, Birgit |
author_sort | Niemann, Uli |
collection | PubMed |
description | Chronic tinnitus is a complex, multi-factorial symptom that requires careful assessment and management. Evidence-based therapeutic approaches involve audiological and psychological treatment components. However, not everyone benefits from treatment. The identification and characterisation of patient subgroups (or “phenotypes”) may provide clinically relevant information. Due to the large number of assessment tools, data-driven methods appear to be promising. The acceptance of these empirical results can be further strengthened by a comprehensive visualisation. In this study, we used cluster analysis to identify distinct tinnitus phenotypes based on self-report questionnaire data and implemented a visualisation tool to explore phenotype idiosyncrasies. 1228 patients with chronic tinnitus from the Charité Tinnitus Center in Berlin were included. At baseline, each participant completed 14 questionnaires measuring tinnitus distress, -loudness, frequency and location, depressivity, perceived stress, quality of life, physical and mental health, pain perception, somatic symptom expression and coping attitudes. Four distinct patient phenotypes emerged from clustering: avoidant group (56.8%), psychosomatic group (14.1%), somatic group (15.2%), and distress group (13.9%). Radial bar- and line charts allowed for visual inspection and juxtaposition of major phenotype characteristics. The phenotypes differed in terms of clinical information including psychological symptoms, quality of life, coping attitudes, stress, tinnitus-related distress and pain, as well as socio-demographics. Our findings suggest that identifiable patient subgroups and their visualisation may allow for stratified treatment strategies and research designs. |
format | Online Article Text |
id | pubmed-7532444 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75324442020-10-06 Phenotyping chronic tinnitus patients using self-report questionnaire data: cluster analysis and visual comparison Niemann, Uli Brueggemann, Petra Boecking, Benjamin Mebus, Wilhelm Rose, Matthias Spiliopoulou, Myra Mazurek, Birgit Sci Rep Article Chronic tinnitus is a complex, multi-factorial symptom that requires careful assessment and management. Evidence-based therapeutic approaches involve audiological and psychological treatment components. However, not everyone benefits from treatment. The identification and characterisation of patient subgroups (or “phenotypes”) may provide clinically relevant information. Due to the large number of assessment tools, data-driven methods appear to be promising. The acceptance of these empirical results can be further strengthened by a comprehensive visualisation. In this study, we used cluster analysis to identify distinct tinnitus phenotypes based on self-report questionnaire data and implemented a visualisation tool to explore phenotype idiosyncrasies. 1228 patients with chronic tinnitus from the Charité Tinnitus Center in Berlin were included. At baseline, each participant completed 14 questionnaires measuring tinnitus distress, -loudness, frequency and location, depressivity, perceived stress, quality of life, physical and mental health, pain perception, somatic symptom expression and coping attitudes. Four distinct patient phenotypes emerged from clustering: avoidant group (56.8%), psychosomatic group (14.1%), somatic group (15.2%), and distress group (13.9%). Radial bar- and line charts allowed for visual inspection and juxtaposition of major phenotype characteristics. The phenotypes differed in terms of clinical information including psychological symptoms, quality of life, coping attitudes, stress, tinnitus-related distress and pain, as well as socio-demographics. Our findings suggest that identifiable patient subgroups and their visualisation may allow for stratified treatment strategies and research designs. Nature Publishing Group UK 2020-10-02 /pmc/articles/PMC7532444/ /pubmed/33009468 http://dx.doi.org/10.1038/s41598-020-73402-8 Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Niemann, Uli Brueggemann, Petra Boecking, Benjamin Mebus, Wilhelm Rose, Matthias Spiliopoulou, Myra Mazurek, Birgit Phenotyping chronic tinnitus patients using self-report questionnaire data: cluster analysis and visual comparison |
title | Phenotyping chronic tinnitus patients using self-report questionnaire data: cluster analysis and visual comparison |
title_full | Phenotyping chronic tinnitus patients using self-report questionnaire data: cluster analysis and visual comparison |
title_fullStr | Phenotyping chronic tinnitus patients using self-report questionnaire data: cluster analysis and visual comparison |
title_full_unstemmed | Phenotyping chronic tinnitus patients using self-report questionnaire data: cluster analysis and visual comparison |
title_short | Phenotyping chronic tinnitus patients using self-report questionnaire data: cluster analysis and visual comparison |
title_sort | phenotyping chronic tinnitus patients using self-report questionnaire data: cluster analysis and visual comparison |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532444/ https://www.ncbi.nlm.nih.gov/pubmed/33009468 http://dx.doi.org/10.1038/s41598-020-73402-8 |
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