Heart Rate–corrected QT Interval Duration in Rheumatoid Arthritis and Its Reduction with Treatment with the Interleukin 6 Inhibitor Tocilizumab
Bibliographic record
Abstract
OBJECTIVE: Individuals with rheumatoid arthritis (RA) are at a heightened risk of sudden cardiac death, an outcome increased in those with prolongation of the corrected electrocardiographic QT interval (QTc). We compared QTc between patients with RA and demographically matched controls and studied the change in QTc after treatment with the interleukin 6 inhibitor tocilizumab (TCZ). METHODS: Standard 12-lead electrocardiograms were obtained and QTc was measured in patients with RA at baseline and after 24 weeks of TCZ treatment, then compared with non-RA controls who were frequency-matched on age and sex. Indicators of the baseline QTc and predictors of change in QTc were studied using multivariable linear regression. RESULTS: A total of 94 RA and 42 non-RA controls were studied. The average baseline QTc was 10 ms longer in the RA group vs controls (422 vs 412 ms, respectively; p < 0.001) and decreased to an average of 406 ms with treatment (p < 0.001). Baseline QTc was significantly and independently higher among those with anticyclic citrullinated peptide antibodies seropositivity, higher swollen joint counts, and higher levels of C-reactive protein (CRP) and matrix metalloproteinase 3. Each log unit decrease in CRP with treatment was associated with an average reduction in QTc of 2.9 ms (p = 0.002) after adjusting for age and baseline QTc. Clinical response measures were not associated with the change in QTc. CONCLUSION: The marked normalization of QTc observed with TCZ treatment, and its close parallel with CRP reduction, support the premise that systemic inflammation contributes to cardiac repolarization abnormalities in RA that may be amenable to treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".