Increased Prevalence of Moderate to Severe Mitral and Aortic Valve Dysfunction in Systemic Sclerosis: A Case-control Study
Bibliographic record
Abstract
Objective To investigate the prevalence, severity, and associated clinical factors of mitral and aortic valvular involvement in patients with systemic sclerosis (SSc). Methods Our case-control study included 172 patients with SSc and 172 non-SSc adults without known cardiac disease matched by age, sex, and prevalence of cardiovascular (CV) risk factors. The screening of mitral and aortic valvular involvement was performed by transthoracic Doppler echocardiogram. The prevalence of aortic stenosis (AS) was also compared with that reported in a population-based study performed in our community during the same period. Results Patients with SSc showed an almost 5-fold increased prevalence of moderate to severe mitroaortic valve dysfunction compared to non-SSc controls (OR 4.60, 95% CI 1.51–13.98; P = 0.003). The most common lesion was mitral regurgitation (MR), which was observed in 5.2% of patients, followed by AS in 3.5%, and aortic regurgitation (AR) in 1.7%. Analyzing the different types of valvular lesion separately, we observed a significantly higher frequency of MR compared to controls (OR 4.69, 95% CI 1.12–22.04; P = 0.032), as well as a higher frequency of AS in the 65–75 (OR 7.51, 95% CI 1.22–46.23, P = 0.01) and 76–85 age groups (OR 3.53, 95% CI 1.03–12.22, P = 0.043) when compared to the general population in our community. Conclusion We found an increased prevalence of moderate to severe MR and AS in SSc compared to age-matched non-SSc controls with similar CV comorbidities. While results from this study do not allow for establishing a direct causal relationship, they strongly support the contribution of SSc-specific factors in the development of these complications.
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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".