ANALYZING THE RELATIONSHIP AMONG CLINICAL SYMPTOMS, X-RAY RESULTS, AND CARTILAGE WEAR PATTERNS IN KNEE OSTEOARTHRITIS USING T2 MAPPING MRI
Notice bibliographique
Résumé
Objectives: Osteoarthritis (OA) is a condition that causes joint pain, varying degrees of functional limitations, and a decrease in overall quality of life. The purpose of this study was to examine the progression of cartilage degeneration in knees affected by symptomatic OA and determine its relationship with X-ray and T2 map MRI findings. Methods: This study was conducted at a Tertiary Care Teaching Institute in India and involved 40 patients. It was an observational type of study. For our assessment, we utilized the Western Ontario and McMaster University (WOMAC) osteoarthrosis index to evaluate function, quality of life, and joint pain. Medical imaging technique A standing AP view of the affected knee joint was taken using plain radiographs. Once the X-rays were obtained, they were graded using the Kellgren–Lawrence Classification, which ranges from 0 to 4 grades. Results: Out of the total patients, 6.0% were <40 years old, 21.2% were between 41 and 50 years old, 27.2% were between 51 and 60 years old, 39.3% were between 61 and 70 years old, and 6.0% were above 70 years old. In this study, there were 21 females (63.6%) and 12 males (36.4%). In this study, the researchers found that there was no distinction between the sides of the limb affected. Both the left and right sides were involved in 13 cases each, accounting for 39.39% of the total cases. In addition, 7 cases, or 21.21%, reported experiencing bilateral knee pain. Merchant grade reported that out of the knees examined, 17.5% had Grade 0, 45% had Grade 1, 27.5% had Grade 2, 10% had Grade 3, and none had Grade 4. Conclusion: The findings of this study suggest that T2 map MRI has the ability to accurately measure abnormal cartilage changes in conditions that affect the mechanical properties of the knee joint. It is crucial to have non-invasive methods that can assess early cartilage matrix changes. These methods are important for initiating early treatment, monitoring disease progression, planning operative procedures, and following up on operative cartilage repair.
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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 | 0,012 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,003 |
| 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 ».