Essential Hypertension Worsens Left Ventricular Contractility in Systemic Sclerosis
Bibliographic record
Abstract
OBJECTIVE: Primary cardiac involvement in systemic sclerosis (SSc) is prevalent and morbid; however, the influence of traditional cardiovascular (CV) risk factors, such as essential hypertension (HTN), are unclear. In the present study, we sought to understand the effects of HTN on left ventricular (LV) contractility in patients with SSc using echocardiographic speckle-derived global longitudinal strain (GLS). METHODS: Fifty-six SSc patients with HTN (SSc+HTN+) and 82 SSc patients without HTN (SSc+ HTN-) were compared with 40 non-SSc controls with HTN (SSc-HTN+) and 40 non-SSc controls without HTN (SSc-HTN-), matched by age and sex. All HTN patients were on stable antihypertensive therapies. Echocardiographic measures included LV (LV) ejection fraction (LVEF), left atrial volume index (LAVI), and LV diastolic function. LV contractility was assessed by GLS, averaged across the 18 LV segments. RESULTS: 0.05), as well as the largest reduction in GLS compared to SSc+HTN- and both control groups. CONCLUSION: Speckle-derived strain revealed diminished LV contractility in patients with SSc, despite normal LVEF. SSc+HTN+ had more prominent reductions in GLS associated with evidence of LV remodeling and worsened diastolic function. Our findings demonstrate the presence of subclinical LV contractile dysfunction in SSc that is further exacerbated by concomitant HTN, thereby identifying HTN as an important modifiable CV risk factor that should be managed aggressively in this at-risk population.
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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 | 0.000 | 0.001 |
| 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".