Observational studyArthritis care & research2021
Trajectories of Structural Disease Progression in Knee Osteoarthritis.
Observational study in Arthritis care & research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 34 citations in OpenAlex.
- Studying the Natural History of the Knee Joint.Journal of the American Academy of Orthopaedic Surgeons. Global research & reviews · 2026Review
- Association of baseline MRI-defined structural features with knee symptom trajectories over nine years: Data from the osteoarthritis initiative (OAI).Osteoarthritis imaging · 2026Article
- Borderline acceleration in blood epigenetic age of unclear biological importance in knee osteoarthritis progression: Specimens and data from the Osteoarthritis Initiative and Johnston County Osteoarthritis Project.Osteoarthritis and cartilage · 2026Article
- Longitudinal associations between bilateral versus unilateral knee osteoarthritis and physical performance measures.Osteoarthritis and cartilage open · 2025Article
- Common intra-articular knee injections demonstrate a similar recovery trajectory over 60 months: A systematic review and meta-analysis of 15,418 participants.Journal of experimental orthopaedics · 2025Review
- MonitOring the health trajectory of patients with kNee osteoarthritis referred for orthopaedic opinion: Protocol for the MOTION parallel cohort-implementation study.Osteoarthritis and cartilage open · 2025Article
- Are Changes in Physical Activity, Pain, and Quality of Life in Patients with Knee Osteoarthritis After Exercise Therapy and Education Beyond Normal Fluctuations? A Comparative Study.Journal of clinical medicine · 2025Article
- Commentary: Musculoskeletal adverse events in dogs receiving bedinvetmab (Librela).Frontiers in veterinary science · 2025Article
- Article
- Evaluation of Dynamic Effects of Depressive Symptoms on Physical Function in Knee Osteoarthritis.Arthritis care & research · 2024Article
- Gaussian Aquila optimizer based dual convolutional neural networks for identification and grading of osteoarthritis using knee joint images.Scientific reports · 2024Article
- A Comprehensive Review of Current Management Trends in Medial Compartment Arthritis of the Knee Joint.Cureus · 2024Review
- Exploring relationships among multi-disciplinary assessments for knee joint health in service members with traumatic unilateral lower limb loss: a two-year longitudinal investigation.Scientific reports · 2023Article
- Researchers in rheumatology should avoid categorization of continuous predictor variables.BMC medical research methodology · 2023Article
- Anatomical Imaging Study on Uneven Settlement of the Proximal Tibia.Orthopaedic surgery · 2023Article
- Peripheral Blood DNA Methylation-Based Machine Learning Models for Prediction of Knee Osteoarthritis Progression: Biologic Specimens and Data From the Osteoarthritis Initiative and Johnston County Osteoarthritis Project.Arthritis & rheumatology (Hoboken, N.J.) · 2023Article
- Identifying trajectories of radiographic spinal disease in ankylosing spondylitis: a 15-year follow-up study of the PSOAS cohort.Rheumatology (Oxford, England) · 2022Observational
- Discovering Knee Osteoarthritis Imaging Features for Diagnosis and Prognosis: Review of Manual Imaging Grading and Machine Learning Approaches.Journal of healthcare engineering · 2022Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveKnee osteoarthritis (OA) is a heterogeneous disease, with most patients experiencing slow disease progression and some with rapid deterioration. We aimed to identify groups of patients with symptomatic knee OA experiencing rapid structural progression.
methodsWe selected participants from the Osteoarthritis Initiative with baseline Kellgren/Lawrence (K/L) grades 1-3 and knee pain, and with joint space width (JSW) on fixed-flexion knee radiographs assessed at baseline and with ≥1 follow-up over 8 years. We used latent class growth analysis to identify subgroups of JSW progression, jointly modeling time to knee replacement (KR) to account for potential informative dropouts. After identifying trajectories, we used logistic regression to assess the association between baseline characteristics and the JSW trajectory group.
resultsWe used data from 1,578 participants. Baseline radiographic severity was K/L grade 1 in 17%, K/L grade 2 in 50%, and K/L grade 3 in 33%. We identified 3 distinct JSW trajectories: 86% stable, 6% with stable JSW followed by late progression, and 8% with early progression. Incorporating information about KR resulted in 47% of KRs initially classified as stable being reclassified to 1 of the progressing trajectories. Prior knee surgery was associated with being in the late-progressing versus the stable trajectory, while obesity was associated with being in the early-progressing versus stable trajectory.
conclusionIn addition to a subgroup of individuals experiencing early structural progression, 8-year longitudinal data allowed the identification of a late-progressing trajectory. Incorporating information about KR was important to properly identify longitudinal structural trajectories in knee OA.
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