{"id":41080,"date":"2023-10-16T10:58:54","date_gmt":"2023-10-16T09:58:54","guid":{"rendered":"https:\/\/wames.org.uk\/cms-english\/?p=41080"},"modified":"2023-10-16T10:58:54","modified_gmt":"2023-10-16T09:58:54","slug":"research-diagnosing-me-cfs-by-analysing-questionnaires-with-machine-learning","status":"publish","type":"post","link":"https:\/\/wames.org.uk\/cms-english\/research-diagnosing-me-cfs-by-analysing-questionnaires-with-machine-learning\/","title":{"rendered":"Research: Diagnosing ME\/CFS by analysing questionnaires with Machine Learning"},"content":{"rendered":"<h2><strong>Machine learning analysis of SF-36 Health questionnaire could be as diagnostic tool for ME\/CFS<\/strong><\/h2>\n<p>&nbsp;<\/p>\n<p><img data-recalc-dims=\"1\" decoding=\"async\" class=\"alignright size-medium wp-image-41135 lazyload\" data-src=\"https:\/\/i0.wp.com\/wames.org.uk\/cms-english\/wp-content\/uploads\/2023\/10\/machine-learning-4129175_640.jpg?resize=300%2C200&#038;ssl=1\" alt=\"\" width=\"300\" height=\"200\" data-srcset=\"https:\/\/i0.wp.com\/wames.org.uk\/cms-english\/wp-content\/uploads\/2023\/10\/machine-learning-4129175_640.jpg?resize=300%2C200&amp;ssl=1 300w, https:\/\/i0.wp.com\/wames.org.uk\/cms-english\/wp-content\/uploads\/2023\/10\/machine-learning-4129175_640.jpg?resize=150%2C100&amp;ssl=1 150w, https:\/\/i0.wp.com\/wames.org.uk\/cms-english\/wp-content\/uploads\/2023\/10\/machine-learning-4129175_640.jpg?w=640&amp;ssl=1 640w\" data-sizes=\"(max-width: 300px) 100vw, 300px\" src=\"data:image\/svg+xml;base64,PHN2ZyB3aWR0aD0iMSIgaGVpZ2h0PSIxIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciPjwvc3ZnPg==\" style=\"--smush-placeholder-width: 300px; --smush-placeholder-aspect-ratio: 300\/200;\" \/>Spanish researchers looked for an alternative to using an expensive and invasive exercise test (<a href=\"https:\/\/me-pedia.org\/wiki\/Cardiopulmonary_exercise_test\" target=\"_blank\" rel=\"noopener\">CPET<\/a>) as a diagnostic biomarker in patients with ME\/CFS. They found that using <a href=\"https:\/\/en.wikipedia.org\/wiki\/Machine_learning\" target=\"_blank\" rel=\"noopener\">Machine Learning<\/a> to analyse the answers to the <a href=\"https:\/\/me-pedia.org\/wiki\/Short_Form_36-Item_Health_Survey\" target=\"_blank\" rel=\"noopener\">Short Form-36<\/a> (SF-36) questionnaire could predict oxygen consumption and reveal sub-types.<\/p>\n<p>&nbsp;<\/p>\n<p><a href=\"https:\/\/www.clinicaltherapeutics.com\/article\/S0149-2918(23)00352-1\/fulltext\" target=\"_blank\" rel=\"noopener\">Unsupervised cluster analysis reveals distinct subtypes of ME\/CFS patients based on peak oxygen consumption and SF-36 scores<\/a>, by Marcos Lacasa, Patricia Launois, Ferran Prados, Jos\u00e9 Alegre, Jordi Casas-Roma <span style=\"text-decoration: underline;\">in<\/span> <em>Clinical Therapeutics<\/em> Oct 4, 2023 [doi.org\/10.1016\/j.clinthera.2023.09.007]<\/p>\n<p>HIGHLIGHTS<\/p>\n<ul>\n<li>ME\/CFS is a disabling chronic disease with a lack of diagnostic tests.<\/li>\n<li>Oxygen consumption is a possible biomarker of CFS.<\/li>\n<li>O2 consumption allows classifying patients status according to the Weber&#8217;s classification.<\/li>\n<li>A worse Weber&#8217;s classification infers a worse outcome on the SF-36 questionnaire.<\/li>\n<li>Unsupervised machine learning is a powerful tool for analyzing data.<\/li>\n<\/ul>\n<p><strong>Research abstract<\/strong><\/p>\n<p><strong>Purpose<\/strong><br \/>\nMyalgic encephalomyelitis, commonly referred to as chronic fatigue syndrome (ME\/CFS), is a severe, disabling chronic disease and an objective assessment of prognosis is crucial to evaluate the efficacy of future drugs. Attempts are ongoing to find a biomarker to objectively assess the health status of (ME\/CFS), patients.<\/p>\n<p>This study therefore aims to demonstrate that oxygen consumption is a biomarker of ME\/CFS provides a method to classify patients diagnosed with ME\/CFS based on their responses to the Short Form-36 (SF-36) questionnaire, which can predict oxygen consumption using cardiopulmonary exercise testing (CPET).<\/p>\n<p><strong>Methods<\/strong><br \/>\nTwo datasets were used in the study. The first contained SF-36 responses from 2,347 validated records of ME\/CFS diagnosed participants, and an unsupervised machine learning model was developed to cluster the data. The second dataset was used as a validation set and included the cardiopulmonary exercise test (CPET) results of 239 participants diagnosed with ME\/CFS. Participants from this dataset were grouped by peak oxygen consumption according to Weber&#8217;s classification.<\/p>\n<p>he SF-36 questionnaire was correctly completed by only 92 patients, who were clustered using the machine learning model. Two categorical variables were then entered into a contingency table: the cluster with values {0,1} and Weber classification {A, B, C, D} were assigned. Finally, the Chi-square test of independence was used to assess the statistical significance of the relationship between the two parameters.<\/p>\n<p><strong>Findings<\/strong><br \/>\nThe results indicate that the Weber classification is directly linked to the score on the SF-36 questionnaire. Furthermore, the 36-response matrix in the machine learning model was shown to give more reliable results than the subscale matrix (p\u00a0\u2212\u00a0value\u00a0&lt; 0.05) for classifying patients with ME\/CFS.<\/p>\n<p><strong>Implications<\/strong><br \/>\nLow oxygen consumption on CPET can be considered a biomarker in patients with ME\/CFS. Our analysis showed a close relationship between the cluster based on their SF-36 questionnaire score and the Weber classification, which was based on peak oxygen consumption during CPET. The dataset for the training model comprised raw responses from the SF-36 questionnaire, which is proven to better preserve the original information, thus improving the quality of the model.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Machine learning analysis of SF-36 Health questionnaire could be as diagnostic tool for ME\/CFS &nbsp; Spanish researchers looked for an alternative to using an expensive and invasive exercise test (CPET) as a diagnostic biomarker in patients with ME\/CFS. They found &hellip; <a href=\"https:\/\/wames.org.uk\/cms-english\/research-diagnosing-me-cfs-by-analysing-questionnaires-with-machine-learning\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[1],"tags":[],"class_list":["post-41080","post","type-post","status-publish","format-standard","hentry","category-news"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p5qkYK-aGA","_links":{"self":[{"href":"https:\/\/wames.org.uk\/cms-english\/wp-json\/wp\/v2\/posts\/41080","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wames.org.uk\/cms-english\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wames.org.uk\/cms-english\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wames.org.uk\/cms-english\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/wames.org.uk\/cms-english\/wp-json\/wp\/v2\/comments?post=41080"}],"version-history":[{"count":6,"href":"https:\/\/wames.org.uk\/cms-english\/wp-json\/wp\/v2\/posts\/41080\/revisions"}],"predecessor-version":[{"id":41138,"href":"https:\/\/wames.org.uk\/cms-english\/wp-json\/wp\/v2\/posts\/41080\/revisions\/41138"}],"wp:attachment":[{"href":"https:\/\/wames.org.uk\/cms-english\/wp-json\/wp\/v2\/media?parent=41080"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wames.org.uk\/cms-english\/wp-json\/wp\/v2\/categories?post=41080"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wames.org.uk\/cms-english\/wp-json\/wp\/v2\/tags?post=41080"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}