Notice bibliographique
Résumé
Osteoarthritis (OA) is a multifactorial disease of the joints with a complex interplay between systemic factors, such as age, sex, genetic components, obesity and environmental factors (including smoking, diet, physical activity, joint injury and muscle function). Among those risk factors, genetic and modifiable factors (obesity) have been shown to have a crucial role in the development and progression of the disease on radiographs; however, how genetic factors and obesity influence the progression of early structures on magnetic resonance imaging (MRI) and its symptoms (pain) is not fully understood. This thesis aims to explore how these two factors separately or interactively are associated with important structural outcomes on MRI and pain. Data from two longitudinal studies were utilised (the Offspring and TASOAC study). In the offspring study, 372 individuals (186 offspring having at least one parent with a total knee replacement (TKR) for severe primary knee OA and 186 controls) aged 26‚Äö-61 years (mean age of 45 years) participated at baseline and were followed 2.3 and 10.2 years later. TASOAC study is a population-based study with 1099 older adults aged 50-80 years (mean age of 62 years) enrolled at baseline and followed approximately 2.6 and 5.1 years. Cartilage volume, cartilage defects, bone marrow lesions (BMLs), meniscal pathology and effusion were assessed by MRI.Radiographic OA was assessed by X-ray. Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) was used to assess knee pain. A self-reported questionnaire was used to assess pain at neck, back, hands, shoulders, hips, knees and feet. Fat mass was assessed using dual energy x-ray absorptiometry. Data from the Offspring study was used to describe the associations of family history of knee OA with worsening knee pain and knee structural changes over 10 years. We found that offspring had an increased risk of worsening knee pain as compared to controls with no family history of knee OA, and this association was independent of structural factors. Also, offspring had an increased risk of worsening multiple knee structural abnormalities including cartilage defects, meniscal extrusion and tears but not BMLs. The associations between weight and knee cartilage volume/defects over 10 years in offspring and in controls were also examined from the same population. Increasing body weight was deleteriously associated with medial tibiofemoral cartilage volume and presence of medial tibiofemoral cartilage defects in offspring. Similar associations were observed for lateral tibiofemoral cartilage volume and defects. However, there were no statistically significant associations between weight and cartilage volume or defects in controls. The fourth study utilised data from the TASOAC study to explore the associations of fat mass, fat mass index (FMI) and body mass index (BMI) with multi-site pain (MSP), finding that fat mass was associated with MSP and pain at the hands, knees, hips and feet. Results were similar for FMI and BMI. The final study, in the same population, found that the presence of MSP independently predicts knee cartilage volume loss. In conclusion, this series of studies suggest that both genetic and systemic factors (especially fat mass) may have an important role in early structural changes and pain in OA, and these two factors interact with each other to involve in the pathogenesis of OA.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».