Bibliographic record
Abstract
Osteoarthritis (OA) is a multifactorial disease of the joints, common among older adults, which can lead to pain, impaired function and reduced quality of life. This thesis aims to investigate the associations and predictive value of various hormonal, inflammatory and imaging biomarkers with OA outcomes in population-based studies of people with and without prevalent OA. Two population samples were used in this thesis. The first group was a population-based sample of older adults aged 50-80 years (mean age: 62 years; 51% female). Followup measurements were conducted 2.7 (2.6-3.3) years later and again for questionnaire data 5.0 (5.3-6.8) years later. Magnetic resonance imaging (MRI) on the right knees was undertaken at baseline and first followup: knee cartilage volume, tibial bone area, cartilage defects and bone marrow lesions (BMLs) were measured or scored; cartilage mean T1 signal intensity and thickness were measured by semi-automated software. Baseline knee and hip x-rays were scored for joint space narrowing (JSN) and osteophytes. Serum leptin and cytokine levels were measured by immunoassay at baseline and first followup. Body morphometry was measured at baseline. Fat and lean mass measures were measured at baseline using dual-energy x-ray absorptiometry (DXA). Knee pain was assessed by questionnaires (WOMAC, Western Ontario and McMasters Osteoarthritis Index) at all timepoints. The second group was a population-based sample of younger adults aged 26-51 (mean age 41; 64% female). Anthropometric, x-ray and MRI-derived scores and measures were obtained as in the first group. Urinary C-terminal crosslinking telopeptide of type II collagen (U-CTX-II) was measured by measured by immunoassay. This thesis consists of 6 studies. In the first study, in older adults, circulating levels of both leptin and interleukin-6 (IL-6) were associated with hip JSN in both sexes and females respectively, independently of BMI. Adiposity was associated with hip JSN, but not after adjustment for leptin. In the second study, baseline levels of both IL-6 and tumor necrosis factor alpha (TNF-˜í¬±) were associated with medial tibiofemoral knee JSN. Baseline IL-6, change in IL-6 and change in TNF-˜í¬± were associated with cartilage volume loss. In the third study, in older adults, baseline or change over 2.9 years in circulating levels of high sensitivity C-reactive protein (hs-CRP), IL-6 and TNF-˜í¬± were associated with change over 5 years in sub-scale or total WOMAC knee pain. In the fourth study, higher leptin in older adults was significantly associated with lower femoral, tibial and patellar cartilage thickness. Fat measures were negatively associated with cartilage thickness, largely mediated by leptin. Baseline and change in leptin were associated with medial tibial cartilage thickness loss. In the fifth study, knee cartilage defects in older adults were found to be common, not likely to regress, and to predict cartilage volume loss and risk of knee replacement. In the final study, mean T1 MRI signal intensity of cartilage was negatively associated with BMI and same-region cartilage defects in younger and older adults; with U-CTX-II in younger adults; and with JSN and osteophytes in older adults at various sites. It predicted cartilage thickness loss over 2.7 years in older adults. In conclusion, inflammatory and metabolic factors may play important roles in aetiology of cartilage loss and/or symptoms in OA. Cartilage defects predict cartilage loss and risk of knee replacement, and mean T1 MRI signal intensity of cartilage predicts loss of cartilage thickness. All these are potential biomarkers for OA at risk of development or progression, and thus possible targets for intervention.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".