Subclinical Cardiac Dysfunction in Polymyositis and Dermatomyositis: A Speckle-tracking Case-control Study
Bibliographic record
Abstract
OBJECTIVE: Subclinical heart disease occurs in up to 50% of patients with idiopathic inflammatory myopathies (IIM) and is difficult to detect through conventional imaging. We investigated the usefulness of global longitudinal strain (GLS) measurement to detect a subclinical systolic ventricular dysfunction in patients with IIM. METHODS: We enrolled 28 patients with IIM and 28 matched controls in a 1:1 fashion. Standard variables for the left ventricle (LV) and right ventricle (RV) systolic and diastolic function were measured and compared between cases and controls, along with speckle-tracking GLS of the LV and RV. A possible correlation between GLS and muscle strength, disease activity, cardiovascular risk factors, and other organ systems involvement was searched. RESULTS: Standard variables of systolic and diastolic dysfunction were similar between patients and controls. GLS was significantly lower in patients when compared with controls for both LV (-18.7 ± 4.2% vs -21.2 ± 2.1%, p = 0.006) and RV (-19.3 ± 6.3% vs -22.5 ± 3.8%, p = 0.033). Patients with IIM had a 4.9-fold increased risk for impaired left GLS [relative risk (RR) 4.9, 95% CI 1.5-15.8, p = 0.006], which involved usually basal and mid-segments of the anterior, anterior-septal, and lateral wall. Patients with IIM had a 3.4-fold increased risk for impaired right GLS (RR 3.4, 95% CI 1.1-11.7, p = 0.04) with the basal segment of the free RV wall most frequently involved. Muscle strength, disease activity, damage and duration, other organ system involvement, and previous treatment were not associated with reduced GLS. CONCLUSION: Subclinical systolic impairment is common in patients with IIM without overt LV dysfunction. In this context, GLS is a potentially useful variable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".