Higher Prevalence and Degree of Insulin Resistance in Patients With Rheumatoid Arthritis Than in Patients With Systemic Lupus Erythematosus
Bibliographic record
Abstract
Objective. Since insulin resistance (IR) is highly prevalent in patients with systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA), we aimed to determine whether differences in IR exist between the two conditions. Methods. We conducted a cross-sectional study comprising 413 subjects without diabetes (186 with SLE and 227 with RA). Glucose, insulin, and C-peptide serum levels, as well as IR by the homeostatic model assessment (HOMA2) were studied. A multivariable regression analysis was performed to evaluate the differences in IR indexes between patients with SLE and RA, as well as to determine if IR risk factors or disease-related characteristics are differentially associated with IR in both populations. Results. The insulin:C-peptide molar ratio was upregulated in patients with RA compared to patients with SLE (β 0.009, 95% CI 0.005–0.014, P < 0.001) after multivariable analysis. HOMA2 indexes related to insulin sensitivity (HOMA2-%S) were found to be lower (β –27, 95% CI –46 to –9, P = 0.004) and β cell function (HOMA2-%B) showed higher IR indexes (β 38, 95% CI 23–52, P < 0.001) in RA than in SLE patients after multivariable analysis. Patients with RA more often fulfilled the definition of IR than those with SLE (OR 2.15, 95% CI 1.25–3.69, P = 0.005). The size effect of IR factors on IR indexes was found to be equal in both diseases. Conclusion. IR sensitivity is lower and β cell function is higher in RA than in SLE patients. The fact that traditional IR factors have an equal effect on IR in both SLE and RA supports the contention that these differences are related to the diseases themselves.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".