MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1016/j.jpain.2014.01.004

Медицинская библиотека · The journal of pain · 2014

The ACTTION-American Pain Society Pain Taxonomy (AAPT): an evidence-based and multidimensional approach to classifying chronic pain conditions.

Fillingim Roger B, Bruehl Stephen, Dworkin Robert H, Dworkin Samuel F, Loeser John D, Turk Dennis C, Widerstrom-Noga Eva, Arnold Lesley, Bennett Robert, Edwards Robert R, Freeman Roy, Gewandter Jennifer, Hertz Sharon, Hochberg Marc, Krane Elliot, Mantyh Patrick W, Markman John, Neogi Tuhina, Ohrbach Richard, Paice Judith A, Porreca Frank, Rappaport Bob A, Smith Shannon M, Smith Thomas J, Sullivan Mark D, Verne G Nicholas, Wasan Ajay D, Wesselmann Ursula

Consensus StatementСтатьяПоддержка исследования: вне правительства СШАПеревод в очереди

Аннотация

UNLABELLED: Current approaches to classification of chronic pain conditions suffer from the absence of a systematically implemented and evidence-based taxonomy. Moreover, existing diagnostic approaches typically fail to incorporate available knowledge regarding the biopsychosocial mechanisms contributing to pain conditions. To address these gaps, the Analgesic, Anesthetic, and Addiction Clinical Trial Translations Innovations Opportunities and Networks (ACTTION) public-private partnership with the U.S. Food and Drug Administration and the American Pain Society (APS) have joined together to develop an evidence-based chronic pain classification system called the ACTTION-APS Pain Taxonomy. This paper describes the outcome of an ACTTION-APS consensus meeting, at which experts agreed on a structure for this new taxonomy of chronic pain conditions. Several major issues around which discussion revolved are presented and summarized, and the structure of the taxonomy is presented. ACTTION-APS Pain Taxonomy will include the following dimensions: 1) core diagnostic criteria; 2) common features; 3) common medical comorbidities; 4) neurobiological, psychosocial, and functional consequences; and 5) putative neurobiological and psychosocial mechanisms, risk factors, and protective factors. In coming months, expert working groups will apply this taxonomy to clusters of chronic pain conditions, thereby developing a set of diagnostic criteria that have been consistently and systematically implemented across nearly all common chronic pain conditions. It is anticipated that the availability of this evidence-based and mechanistic approach to pain classification will be of substantial benefit to chronic pain research and treatment.

PERSPECTIVE: The ACTTION-APS Pain Taxonomy is an evidence-based chronic pain classification system designed to classify chronic pain along the following dimensions: 1) core diagnostic criteria; 2) common features; 3) common medical comorbidities; 4) neurobiological, psychosocial, and functional consequences; and 5) putative neurobiological and psychosocial mechanisms, risk factors, and protective factors.

Для цитирования: Fillingim Roger B, Bruehl Stephen, Dworkin Robert H, Dworkin Samuel F, Loeser John D, Turk Dennis C, Widerstrom-Noga Eva, Arnold Lesley, Bennett Robert, Edwards Robert R, Freeman Roy, Gewandter Jennifer, Hertz Sharon, Hochberg Marc, Krane Elliot, Mantyh Patrick W, Markman John, Neogi Tuhina, Ohrbach Richard, Paice Judith A, Porreca Frank, Rappaport Bob A, Smith Shannon M, Smith Thomas J, Sullivan Mark D, Verne G Nicholas, Wasan Ajay D, Wesselmann Ursula. The ACTTION-American Pain Society Pain Taxonomy (AAPT): an evidence-based and multidimensional approach to classifying chronic pain conditions.. The journal of pain. 2014. DOI: 10.1016/j.jpain.2014.01.004.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.