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Rheumatic?—A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study
INTRODUCTION: Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations. It calculates a ri...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9083190/ https://www.ncbi.nlm.nih.gov/pubmed/35547229 http://dx.doi.org/10.3389/fmed.2022.774945 |
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author | Knevel, Rachel Knitza, Johannes Hensvold, Aase Circiumaru, Alexandra Bruce, Tor Evans, Sebastian Maarseveen, Tjardo Maurits, Marc Beaart-van de Voorde, Liesbeth Simon, David Kleyer, Arnd Johannesson, Martina Schett, Georg Huizinga, Tom Svanteson, Sofia Lindfors, Alexandra Klareskog, Lars Catrina, Anca |
author_facet | Knevel, Rachel Knitza, Johannes Hensvold, Aase Circiumaru, Alexandra Bruce, Tor Evans, Sebastian Maarseveen, Tjardo Maurits, Marc Beaart-van de Voorde, Liesbeth Simon, David Kleyer, Arnd Johannesson, Martina Schett, Georg Huizinga, Tom Svanteson, Sofia Lindfors, Alexandra Klareskog, Lars Catrina, Anca |
author_sort | Knevel, Rachel |
collection | PubMed |
description | INTRODUCTION: Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations. It calculates a risk score for several rheumatic diseases. We ran a pilot study retrospectively testing Rheumatic? for its ability to differentiate symptoms from existing or emerging immune-mediated rheumatic diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics. MATERIALS AND METHODS: The performance of Rheumatic? was tested using in three university rheumatology centers: (A) patients at Risk for RA (Karolinska Institutet, n = 50 individuals with musculoskeletal complaints and anti-citrullinated protein antibody positivity) (B) patients with early joint swelling [dataset B (Erlangen) n = 52]. (C) Patients with early arthritis where the clinician considered it likely to be of auto-immune origin [dataset C (Leiden) n = 73]. In dataset A we tested whether Rheumatic? could predict the development of arthritis. In dataset B and C we tested whether Rheumatic? could predict the development of an immune-mediated rheumatic diseases. We examined the discriminative power of the total score with the Wilcoxon rank test and the area-under-the-receiver-operating-characteristic curve (AUC-ROC). Next, we calculated the test characteristics for these patients passing the first or second expert-based Rheumatic? scoring threshold. RESULTS: The total test scores differentiated between: (A) Individuals developing arthritis or not, median 245 vs. 163, P < 0.0001, AUC-ROC = 75.3; (B) patients with an immune-mediated arthritic disease or not median 191 vs. 107, P < 0.0001, AUC-ROC = 79.0; but less patients with an immune-mediated arthritic disease or not amongst those where the clinician already considered an immune mediated disease most likely (median 262 vs. 212, P < 0.0001, AUC-ROC = 53.6). Threshold-1 (advising to visit primary care doctor) was highly specific in dataset A and B (0.72, 0.87, and 0.23, respectively) and sensitive (0.67, 0.61, and 0.67). Threshold-2 (advising to visit rheumatologic care) was very specific in all three centers but not very sensitive: specificity of 1.0, 0.96, and 0.91, sensitivity 0.05, 0.07, 0.14 in dataset A, B, and C, respectively. CONCLUSION: Rheumatic? is a web-based patient-centered multilingual diagnostic tool capable of differentiating immune-mediated rheumatic conditions from other musculoskeletal problems. The current scoring system needs to be further optimized. |
format | Online Article Text |
id | pubmed-9083190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90831902022-05-10 Rheumatic?—A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study Knevel, Rachel Knitza, Johannes Hensvold, Aase Circiumaru, Alexandra Bruce, Tor Evans, Sebastian Maarseveen, Tjardo Maurits, Marc Beaart-van de Voorde, Liesbeth Simon, David Kleyer, Arnd Johannesson, Martina Schett, Georg Huizinga, Tom Svanteson, Sofia Lindfors, Alexandra Klareskog, Lars Catrina, Anca Front Med (Lausanne) Medicine INTRODUCTION: Digital diagnostic decision support tools promise to accelerate diagnosis and increase health care efficiency in rheumatology. Rheumatic? is an online tool developed by specialists in rheumatology and general medicine together with patients and patient organizations. It calculates a risk score for several rheumatic diseases. We ran a pilot study retrospectively testing Rheumatic? for its ability to differentiate symptoms from existing or emerging immune-mediated rheumatic diseases from other rheumatic and musculoskeletal complaints and disorders in patients visiting rheumatology clinics. MATERIALS AND METHODS: The performance of Rheumatic? was tested using in three university rheumatology centers: (A) patients at Risk for RA (Karolinska Institutet, n = 50 individuals with musculoskeletal complaints and anti-citrullinated protein antibody positivity) (B) patients with early joint swelling [dataset B (Erlangen) n = 52]. (C) Patients with early arthritis where the clinician considered it likely to be of auto-immune origin [dataset C (Leiden) n = 73]. In dataset A we tested whether Rheumatic? could predict the development of arthritis. In dataset B and C we tested whether Rheumatic? could predict the development of an immune-mediated rheumatic diseases. We examined the discriminative power of the total score with the Wilcoxon rank test and the area-under-the-receiver-operating-characteristic curve (AUC-ROC). Next, we calculated the test characteristics for these patients passing the first or second expert-based Rheumatic? scoring threshold. RESULTS: The total test scores differentiated between: (A) Individuals developing arthritis or not, median 245 vs. 163, P < 0.0001, AUC-ROC = 75.3; (B) patients with an immune-mediated arthritic disease or not median 191 vs. 107, P < 0.0001, AUC-ROC = 79.0; but less patients with an immune-mediated arthritic disease or not amongst those where the clinician already considered an immune mediated disease most likely (median 262 vs. 212, P < 0.0001, AUC-ROC = 53.6). Threshold-1 (advising to visit primary care doctor) was highly specific in dataset A and B (0.72, 0.87, and 0.23, respectively) and sensitive (0.67, 0.61, and 0.67). Threshold-2 (advising to visit rheumatologic care) was very specific in all three centers but not very sensitive: specificity of 1.0, 0.96, and 0.91, sensitivity 0.05, 0.07, 0.14 in dataset A, B, and C, respectively. CONCLUSION: Rheumatic? is a web-based patient-centered multilingual diagnostic tool capable of differentiating immune-mediated rheumatic conditions from other musculoskeletal problems. The current scoring system needs to be further optimized. Frontiers Media S.A. 2022-04-25 /pmc/articles/PMC9083190/ /pubmed/35547229 http://dx.doi.org/10.3389/fmed.2022.774945 Text en Copyright © 2022 Knevel, Knitza, Hensvold, Circiumaru, Bruce, Evans, Maarseveen, Maurits, Beaart-van de Voorde, Simon, Kleyer, Johannesson, Schett, Huizinga, Svanteson, Lindfors, Klareskog and Catrina. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medicine Knevel, Rachel Knitza, Johannes Hensvold, Aase Circiumaru, Alexandra Bruce, Tor Evans, Sebastian Maarseveen, Tjardo Maurits, Marc Beaart-van de Voorde, Liesbeth Simon, David Kleyer, Arnd Johannesson, Martina Schett, Georg Huizinga, Tom Svanteson, Sofia Lindfors, Alexandra Klareskog, Lars Catrina, Anca Rheumatic?—A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study |
title | Rheumatic?—A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study |
title_full | Rheumatic?—A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study |
title_fullStr | Rheumatic?—A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study |
title_full_unstemmed | Rheumatic?—A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study |
title_short | Rheumatic?—A Digital Diagnostic Decision Support Tool for Individuals Suspecting Rheumatic Diseases: A Multicenter Pilot Validation Study |
title_sort | rheumatic?—a digital diagnostic decision support tool for individuals suspecting rheumatic diseases: a multicenter pilot validation study |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9083190/ https://www.ncbi.nlm.nih.gov/pubmed/35547229 http://dx.doi.org/10.3389/fmed.2022.774945 |
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