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Enregistrement W4381598230 · doi:10.1177/17407745231182010

Chronic pain trials often exclude people with comorbid depressive symptoms: A secondary analysis of 346 randomized controlled trials

2023· article· en· W4381598230 sur OpenAlexafffund
Darren K. Cheng, Maarij Ullah, Henry Gage, Rahim Moineddin, Abhimanyu Sud

Notice bibliographique

RevueClinical Trials · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueFibromyalgia and Chronic Fatigue Syndrome Research
Établissements canadiensHumber River Regional HospitalMcMaster UniversityUniversity of TorontoLunenfeld-Tanenbaum Research Institute
Organismes subventionnairesCanadian Institutes of Health ResearchUniversity of TorontoMedical Psychiatry Alliance
Mots-clésRandomized controlled trialMedicineDepression (economics)Chronic painPopulationClinical trialPhysical therapyPsychological interventionPsychiatryInternal medicine

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Chronic pain and depression are common comorbid conditions, but there is limited evidence-based guidance for management of the two conditions together. In recent years, there has been an increase in the number of chronic pain randomized controlled trials that collect depression outcomes, but it is unknown how often these trials include people with depression or significant depressive symptoms. If trials do not include participants representative of real-world populations, evidence and guidance generated from these trials risk being inapplicable for large proportions of the target population, or worse, risk harm. Thus, in order to identify pathways to improve the conduct of clinical trials, the aims of this study were to (1) estimate the proportion of randomized controlled trials evaluating chronic pain interventions and reporting depression outcomes that include participants with significant depressive symptoms; and (2) assess the variability of inclusion proportions by pain type, intervention type, gender, country of origin, and publication year. METHODS: Studies were extracted from an umbrella review of interventions for chronic pain that reported depression outcomes. Screening and data extraction were completed in duplicate and conflicts were resolved by a third author. Randomized controlled trials with at least 50% adult participants and validated depression scales were included, and randomized controlled trials with populations whose mean scores were at or above depression thresholds at baseline were considered to have included participants with depression. RESULTS: Of the 346 randomized controlled trials analyzed, 142 (41%) included participants with depression. Eight pain-type groups and nine intervention types were identified. Randomized controlled trials investigating fibromyalgia and mixed chronic pain had the highest proportion of participants with depression, whereas studies of arthritis and axial pain had among the lowest. Randomized controlled trials from the United States had a significantly lower inclusion proportion compared with non-US studies, especially for studies on arthritis. The increase in inclusion proportion by publication year was driven by the increase in fibromyalgia studies. DISCUSSION AND CONCLUSION: This study highlights opportunities to improve the conduct of chronic pain clinical trials. The majority of randomized controlled trials s analyzed evaluated participants without significant depressive symptoms at baseline, thus the findings synthesized in systematic reviews and subsequent guidelines are most applicable to the subset of real-world populations that do not have significant depressive symptoms. As well, systemic biases around psychological conditions and gender may be important contributors to differences in the study of depression in fibromyalgia compared with common conditions such as arthritis and axial pain. In order to better inform clinical practice, future research must intentionally include individuals with comorbid depression in trials of common chronic pain conditions, and consider methods to mitigate biases that may distort study design.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,436
score de la tête « metaresearch » (Gemma)0,537
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Méta-épidémiologie (sens large), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesMétarecherche, Méta-épidémiologie (sens large)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Essai randomisé · Signal consensuel: Essai randomisé
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,328
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,4360,537
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0480,014
Bibliométrie0,0020,003
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0070,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,169
Tête enseignante GPT0,478
Écart entre enseignants0,309 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeEssai randomisé
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations9
Publié2023
Routes d'admission2
Résumé présentoui

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