What Patients Do Following a New Diagnosis of Knee Osteoarthritis
Notice bibliographique
Résumé
Objective To describe patient use of health services and products within 6 months of a new diagnosis of knee OA. Methods Patients with knee pain and no previous diagnosis of knee OA were recruited by community pharmacists using a simple questionnaire to determine the likelihood of knee OA. In total, 194 participants considered likely to have knee OA were referred to a rheumatologist for a standardized knee exam and radiograph. Of these, 190 were confirmed to have knee OA and were subsequently followed for a period of 6 months. At baseline, 1, 3 and 6 months, a survey was administered that contained questions designed to elicit information on participants' health service and product use. Categories included pain-relieving medication, exercise (e.g., walking), treatments/aids (e.g., knee taping/brace, acupuncture, Arthritis Society Management Program, shoe inserts) and supplements (e.g., glucosamine). In addition, to assess participant satisfaction with pharmacy services, participants were asked to rate their levels of agreement with 4 statements using a five-point Likert scale. Results Follow-up data for all 3 time points were available for 124 (65%) participants. Of these, 64% were female, the mean age was 63 years and 67% were considered either obese or overweight according to their body mass index (BMI). By 6 months, 93% had visited their primary care practitioner for OA, 74% had initiated exercise, 59% had started supplements, 51% had taken pain-relieving medications and 45% had used activity aids. When asked “who gave you this advice,” the majority of participants stated “on my own” for all categories. This was followed by “family physician” for all categories except supplements, which were recommended by “family/friend” 20% of the time. Participants selected “pharmacist” least frequently in all categories, including for the initiation of pain-relieving medication, where only 2% reported a pharmacist recommendation. Of those taking pain-relieving medications, 49% took NSAIDs, 28% took acetaminophen and 12% took a combination of both. The majority of participants were very satisfied with the pharmacy services received (>90%) and few reported any complaints (>10%). While 18% of participants thought that pharmacy services could be better, only 17% thought that pharmacy services were just about perfect. Conclusion Following a diagnosis of knee OA, the majority of participants sought out an intervention, the most popular being exercise and natural medicine supplements. Despite the initial diagnosis by a pharmacist and self-reported satisfaction with pharmacy services, few participants attributed interventions to pharmacists. Even with recent evidence showing that pharmacist involvement can reduce potentially dangerous NSAIDs use in knee OA, most participants appeared to make lifestyle changes independent of health professional advice, and pharmacists played a very small role in this. These results suggest that more work is needed to expand the role of pharmacists toward chronic disease management.
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 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 ».