The Pathological Associations of Hyperuricaemia in Sub-Clinical Gout, Cardiovascular and Cardiopulmonary Diseases
Bibliographic record
Abstract
- Introduction Gout is a common and treatable disease caused by the deposition of MSU crystals in articular and non-articular structures. Hyperuricaemia is the most important risk factor for the development of gout. Gout management is suboptimal worldwide resulting in significant socio-economic impact due to permanent disability. Gout is independently associated with increased morbidity and mortality due to CVD. Although the associations between hyperuricaemia and CVD are well described, it has not been definitively established whether uric acid is merely a marker for risk or a causative agent. At present ACR/EULAR 2015 gout classification criteria state that a patient must have at least one acute gout flare prior to a diagnosis being confirmed. This thesis firstly examines early clinical presentations of gout which do not fulfil the current diagnostic criteria, secondly, the effect of hyperuricaemia on surrogate markers of adverse CVD outcomes and thirdly, MCC950 as a selective inhibitor of the NLRP3 inflammasome and a potential new therapeutic agent for the treatment of gout. The impact of the COVID-19 pandemic on our research is also discussed. Methods. Patients with hyperuricaemia and healthy controls who met the study criteria were recruited. Baseline clinical and demographic information was recorded. Hyperuricaemic cases with foot pain underwent assessment with validated pain scores and US evaluation of the first MTP joint to examine for evidence of urate crystal deposition (DC sign, tophus and erosions). Cases were treated with ULT and assessments repeated after a period of six months. To investigate associations with CVD, patients underwent flow and nitroglyerin mediated dilatation studies of the brachial artery and assessment of pulmonary haemodynamics via pulmonary pulse wave transit. These examinations were repeated after 3 months of ULT. Synovial biopsies and PBMCs were isolated from patients during an acute gout flare. Levels of IL-6 and IL-1β were examined by ELISA and qPCR and compared to osteoarthritis (OA) control samples. Subsequently ,the effects of MCC950 on the secretion of IL-6 and IL-1β was assessed. Results. Results from this study indicate that hyperuricaemic cases with non-specific foot pain commonly have US features of uric acid crystal deposition. The presence of DC sign or tophus on MTP US predicted a significant improvement in pain score following ULT. Hyperuricaemic cases had impaired FMD, NMD and pPTT compared to normal healthy controls, these indices improved following 3 months of treatment with ULT. Knee samples taken from patients with acute gout had elevated IL-6 and IL-1β compared to OA patients and treatment with MCC950 reduced levels of IL-6 and IL-1β in a dose dependant manner. Conclusion. We describe an early clinical presentation of gout previously unrecognised which, through the use of US, can be diagnosed prior to the first acute flare. We propose that inclusion of highly sensitive and specific US indicators of early gout be included in diagnostic criteria so that diagnosis and earlier, effective treatment may commence prior to disease progression. Hyperuricaemia is associated with surrogate markers that predict future adverse CVD outcomes. MCC950 reduced pro-inflammatory mediators associated with gout and has potential to be further investigated as a novel therapeutic agent.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".