Literature DB >> 33492033

Classification algorithm for the International Classification of Diseases-11 chronic pain classification: development and results from a preliminary pilot evaluation.

Beatrice Korwisi1, Ginea Hay1, Nadine Attal2, Qasim Aziz3, Michael I Bennett4, Rafael Benoliel5, Milton Cohen6, Stefan Evers7,8, Maria Adele Giamberardino9,10, Stein Kaasa11,12,13, Eva Kosek14,15, Patricia Lavand'homme16, Michael Nicholas17, Serge Perrot18, Stephan Schug19, Blair H Smith20, Peter Svensson21, Johan W S Vlaeyen22,23,24, Shuu-Jiun Wang25,26, Rolf-Detlef Treede27, Winfried Rief1, Antonia Barke28.   

Abstract

ABSTRACT: The International Classification of Diseases-11 (ICD-11) chronic pain classification includes about 100 chronic pain diagnoses on different diagnostic levels. Each of these diagnoses requires specific operationalized diagnostic criteria to be present. The classification comprises more than 200 diagnostic criteria. The aim of the Classification Algorithm for Chronic Pain in ICD-11 (CAL-CP) is to facilitate the use of the classification by guiding users through these diagnostic criteria. The diagnostic criteria were ordered hierarchically and visualized in accordance with the standards defined by the Society for Medical Decision Making Committee on Standardization of Clinical Algorithms. The resulting linear decision tree underwent several rounds of iterative checks and feedback by its developers, as well as other pain experts. A preliminary pilot evaluation was conducted in the context of an ecological implementation field study of the classification itself. The resulting algorithm consists of a linear decision tree, an introduction form, and an appendix. The initial decision trunk can be used as a standalone algorithm in primary care. Each diagnostic criterion is represented in a decision box. The user needs to decide for each criterion whether it is present or not, and then follow the respective yes or no arrows to arrive at the corresponding ICD-11 diagnosis. The results of the pilot evaluation showed good clinical utility of the algorithm. The CAL-CP can contribute to reliable diagnoses by structuring a way through the classification and by increasing adherence to the criteria. Future studies need to evaluate its utility further and analyze its impact on the accuracy of the assigned diagnoses.
Copyright © 2021 International Association for the Study of Pain.

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Year:  2021        PMID: 33492033     DOI: 10.1097/j.pain.0000000000002208

Source DB:  PubMed          Journal:  Pain        ISSN: 0304-3959            Impact factor:   6.961


  3 in total

1.  The relationship between pain intensity and insomnia in women with deep endometriosis, a cross-sectional study.

Authors:  Ricardo José de Souza; Nivaldo Ribeiro Vilella; Marco Aurelio Pinho Oliveira
Journal:  Sleep Breath       Date:  2022-04-27       Impact factor: 2.816

Review 2.  A Systematic Review of the Variation in Pain Catastrophizing Scale Reference Scores Based on Language Version and Country in Patients with Chronic Primary (Non-specific) Pain.

Authors:  Kazuhiro Hayashi; Tatsunori Ikemoto; Yukiko Shiro; Young-Chang Arai; Anna Marcuzzi; Daniel Costa; Paul J Wrigley
Journal:  Pain Ther       Date:  2022-05-14

3.  Hierarchical clustering by patient-reported pain distribution alone identifies distinct chronic pain subgroups differing by pain intensity, quality, and clinical outcomes.

Authors:  Benedict J Alter; Nathan P Anderson; Andrea G Gillman; Qing Yin; Jong-Hyeon Jeong; Ajay D Wasan
Journal:  PLoS One       Date:  2021-08-04       Impact factor: 3.240

  3 in total

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