Manitoba Academic Rehabilitation Sciences COVID Interest Group (MARSCI)
Notice bibliographique
Résumé
Many individuals (10-30%) experience persistent and/or new symptoms beyond the acute COVID-19 infection, which can present regardless of initial infection severity. Commonly referred to as “Long COVID” among public advocacy groups, this post-COVID condition affects multiple body systems and is thought to reflect persistent inflammation, thrombosis, and an autoimmune reaction. The most consistent complaints of Long COVID are fatigue, shortness of breath, muscle pain and difficulty concentrating. Many with Long COVID experience loss of income, or struggle to fulfill family duties. Given that there have been over 117,000 PCR-test confirmed COVID-19 cases in Manitoba, it is likely that thousands of Manitobans are affected by Long COVID. Emerging international guidance recommends that policy makers address Long COVID through a multidisciplinary approach, including interprofessional rehabilitation services. With this in mind, we conducted an environmental scan to support and make recommendations for Long COVID management in Manitoba. Our objectives were to 1) identify policy for management of Long COVID, 2) learn about the lived experiences and advocacy priorities of people with lived experiences of Long COVID, and 3) gather information on current Long COVID services in Manitoba. We conducted web searches in July-September 2021 for a) provincial/territorial government policies related to Long COVID, b) peer-reviewed evidence syntheses and original studies about Long COVID, and c) Long COVID public advocacy groups. We collected information on current, publicly-funded Long COVID rehabilitation services in Manitoba, by consulting with service providers, managers and researchers with knowledge of the Manitoba health system. Our policy search identified frameworks for managing Long COVID in just two provinces (Alberta and Saskatchewan); both frameworks incorporate integrated, interprofessional care. We were unable to identify Long COVID policy in any other jurisdiction, and four jurisdictions indicated that Long COVID will be managed using existing programs or global budgets. Public advocacy groups consistently raised the lack of recognition, let alone care, for Long COVID. Concerns about accessibility to appropriate health services were consistently expressed by advocacy groups because established services may not be equipped to address the needs of people with Long COVID. Advocacy groups argue for specialized team-based clinics, with rehabilitation as one of the main components of Long COVID management. Our scan of existing Manitoba services indicated that current rehabilitation services are not designed for the needs of people with Long COVID. Major gaps include Long COVID rehabilitation services for children and youth, and accessible community-based interprofessional care for young and middle-aged adults. Long COVID rehabilitation programs are being developed, but are not yet funded.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,005 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,148 | 0,020 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».