Impaired Myocardial Flow Reserve on <sup>82</sup> Rubidium Positron Emission Tomography/Computed Tomography in Patients With Systemic Sclerosis
Bibliographic record
Abstract
Objective. To investigate the association between Raynaud phenomenon (RP) and coronary microvascular dysfunction, we measured myocardial flow reserve (MFR) using positron emission tomography/computed tomography (PET/CT) in patients with primary and secondary RP and controls. Methods. Patients with RP, patient controls, and healthy participants who underwent dynamic rest-stress 82-rubidium PET/CT were studied. Differences in heart rate–blood pressure product-corrected MFR and clinical predictors of reduced MFR (< 2.0) were determined. Results. Forty-nine patients with RP (80% female; aged 65 ± 11 yrs; 11 with primary RP, 18 with systemic sclerosis [SSc], and 20 with other autoimmune rheumatic diseases [AIRDs] including 6 with systemic lupus erythematosus, 6 with rheumatoid arthritis, 4 with overlap syndrome, 2 with Sjögren syndrome, and 2 with inflammatory arthritis), 49 matched patients without RP or AIRD (78% female; 64 ± 13 yrs), and 14 healthy participants (50% female; 35 ± 5 yrs) were studied. Patients with primary RP, matched patient controls, and healthy participants had comparable MFR. Patients with SSc-RP had significantly reduced MFR (1.62 ± 0.32) compared to matched patient controls ( P = 0.03, 2.06 ± 0.61) and to healthy participants ( P = 0.01, 2.22 ± 0.44). In multivariable logistic regression, SSc was an independent predictor of reduced MFR. We identified a correlation between time since AIRD diagnosis and MFR (r = –0.30, 95% CI –0.63 to –0.02, P = 0.04). Conclusion. Our findings suggest that only secondary, not primary, RP is associated with reduced MFR, and that patients with SSc-RP have reduced MFR compared to those with primary RP and patients with other AIRDs. Larger prospective studies are warranted to fully elucidate the prognostic value of MFR in patients with secondary RP.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".