Physical functioning over three years in knee osteoarthritis: Role of psychosocial, local mechanical, and neuromuscular factors
Notice bibliographique
Résumé
OBJECTIVE: To identify factors that predict a poor physical function outcome over 3 years in individuals with knee osteoarthritis (OA), in an effort to aid in the development of strategies to prevent such functional limitations and consequential disability. METHODS: Community-recruited individuals with knee OA underwent baseline, 18-month, and 3-year assessments of candidate risk factors and physical function. Risk factors were age, body mass index (BMI), knee pain intensity (on a visual analog scale [VAS]), local mechanical and neuromuscular factors (varus-valgus laxity, malalignment, proprioceptive inaccuracy, quadriceps strength, hamstring strength), activity level (Physical Activity Scale for the Elderly, amount of aerobic exercise), and psychosocial factors (Short-Form 36 [SF-36] mental health and role-functioning emotional subscales, self-efficacy using the Arthritis Self-Efficacy Scale physical function subscale, and social support using the Medical Outcomes Study Social Support Survey). Outcome was assessed using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) physical function scale and rate of chair-stand performance. Participants were grouped by quintile of baseline WOMAC score. The baseline to 3-year outcome was considered "good" when function improved by 1 or more quintiles or remained within the 2 highest function groups, and was considered "poor" when function declined by 1 or more quintiles or remained within the 3 lowest function groups. The same approach was taken for chair-stand outcome. Logistic regression was used to evaluate both the baseline level and the baseline to 18-month change in each factor as a predictor of physical function outcome over 3 years, adjusting for age, BMI, knee pain intensity, disease severity, and additional potential confounders. RESULTS: Factors that significantly increased the likelihood of a poor WOMAC outcome were baseline laxity (crude odds ratio [OR] 1.48/3 degrees, 95% confidence interval [95% CI] 1.02-2.14), BMI (OR 1.26/5 units, 95% CI 1.01-1.57), knee pain intensity (OR 1.21/20 mm on VAS, 95% CI 1.00-1.47), and baseline to 18-month increase in knee pain (OR 1.32/20 mm on VAS, 95% CI 1.06-1.65). Factors that significantly protected against a poor WOMAC outcome were better baseline mental health (OR 0.62/5 points, 95% CI 0.44-0.87), self-efficacy (OR 0.79/5 points, 95% CI 0.67-0.93), and social support (OR 0.86/10 points, 95% CI 0.75-0.98), and greater amount of aerobic exercise (OR 0.75/60 minutes each week, 95% CI 0.63-0.89). Factors that increased the likelihood for a poor function outcome by the chair-stand performance rate were age and proprioceptive inaccuracy, and factors that reduced the likelihood for poor chair-stand outcome were strength (attenuated after adjusting for pain intensity or self-efficacy), self-efficacy, and aerobic exercise. Individuals who sustained high function and those who sustained low function over the 3 years were described. CONCLUSION: Factors placing individuals with knee OA at greater risk of a poor function outcome by at least 1 of the 2 function measures included the local factors laxity and proprioceptive inaccuracy, as well as age, BMI, and knee pain intensity. Factors protecting against a poor function outcome included strength, the psychosocial factors mental health, self-efficacy, and social support, and the activity level measured by the amount of aerobic exercise per week. The identification of these factors provides possible targets for rehabilitative and self-management strategies to prevent disability.
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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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
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 ».