Higher Prevalence of Metabolic Syndrome in Patients with Psoriatic Arthritis: A Comparison with a Control Group of Noninflammatory Rheumatologic Conditions
Bibliographic record
Abstract
To the Editor: In our recent report, we showed that metabolic syndrome (MetS) is highly prevalent in patients with psoriatic arthritis (PsA) and is independently associated with the severity of underlying PsA1. This finding suggested that the higher burden of musculoskeletal inflammation may play a major role in the development of MetS. We acknowledge that one of the limitations of our study was the lack of a control group. Herein, we have recruited an age-, sex-, and race/ethnicity-matched control group attending rheumatology clinics with noninflammatory rheumatologic conditions. Our objective was to compare the prevalence of MetS in this control group with our earlier published cohort of patients with PsA to further test the inflammation-cardiovascular disease (CVD) hypothesis. The control group consisted of 100 consecutive patients attending rheumatology clinics with noninflammatory conditions (osteoarthritis = 27, fibromyalgia = 36, regional musculoskeletal pain = 25, osteoporosis = 12). These patients were recruited from December 2014 through to March 2015. None of these patients had concomitant chronic inflammatory joint disease, and none of these patients … Address correspondence to Dr. M. Haroon, Consultant Rheumatologist, Division of Rheumatology, Department of Medicine, University Hospital Kerry, Tralee, Ireland. E-mail: mharoon301{at}hotmail.com
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".