Negative Association of Smoking History With Clinically Manifest Cardiac Sarcoidosis: A Case-Control Study
Bibliographic record
Abstract
Background The etiology of sarcoidosis is still unknown and is likely related to a genetic susceptibility to unidentified environmental trigger(s). Our group and others have extensively described a specific phenotype of primarily Caucasian patients who have clinically manifest cardiac sarcoidosis (CS). In this study, we sought to explore whether smoking is associated with this specific phenotype of sarcoidosis. Methods We performed a case-control study. Cases with clinically manifest CS were prospectively enrolled in the Cardiac Sarcoidosis Multi-Center Prospective Cohort Study (CHASM-CS registry; NCT01477359) and answered a standardized smoking history questionnaire. Cases were matched 10:1 with controls from the Ontario Health Study. Pretreatment positron emission tomography scans with 18 F-fluorodeoxyglucose were compared for smokers vs nonsmokers. Results Eighty-seven cases met the inclusion criteria. A total of 82 of 87 (94.3%) answered the questionnaire and were matched with 820 controls. A clear negative association of sarcoidosis and smoking was found, with 23 of 82 CS cases (28.0%) being current or ex-smokers, vs 392 of 820 controls (47.8%; P = 0.0006). CS patients with a smoking history had significantly less lifetime consumption (8.31 ± 9.20 pack-years) than the controls (15.34 ± 10.84 pack-years; P < 0.003). On 18 F-fluorodeoxyglucose-positron emission tomography scan, the mean standardized uptake value of the left ventricle was 4.2 ± 8.98 in lifetime nonsmokers vs 2.89 ± 2.07 in patients with a smoking history ( P < 0.0001). Conclusions We describe a strong negative association between smoking history and clinically manifest CS. Nonsmokers had more severe myocardial inflammation (greater mean standardized uptake value of the left ventricle) than did patients with a smoking history. Further research is needed to understand these associations and whether they have therapeutic potential.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".