Echocardiographic Abnormalities in New-onset Polymyositis/dermatomyositis
Bibliographic record
Abstract
OBJECTIVE: To identify early echocardiographic abnormalities at the time of diagnosis of polymyositis (PM) and dermatomyositis (DM) and follow the echocardiographic findings during the first 3 months of therapy. METHODS: We included 30 PM/DM patients (23/7) with a mean age of 42.3 ± 1.6 years and without cardiovascular symptoms. Age-matched healthy patients served as controls. Clinical characteristics were recorded. Traditional echocardiography and tissue Doppler imaging (TDI) were performed to measure systolic [ejection fraction, right ventricular fractional area change (RV FAC), lateral and tricuspid annulus s velocities] and diastolic echocardiographic variables (mitral inflow velocities: E, A; deceleration time: DT; lateral and tricuspid annulus e', a' velocities, lateral E/e'). RESULTS: The left and right ventricular systolic dysfunction detected by TDI at the time of the PM/DM diagnosis improved, and characteristic values at the end of the followup period were comparable to those of the controls (lateral s: 10.6 ± 0.2, 8.7 ± 0.4, 9.6 ± 0.3, 11.3 ± 0.2 cm/s; RV FAC: 45.2 ± 2.3, 36.9 ± 1.5, 42.2 ± 1.3, 46.9 ± 1.2%; tricuspid s: 13.3 ± 0.2, 9.5 ± 0.4, 10.3 ± 0.3, 11.6 ± 0.5 cm/s; control, 0, 1, and 3 mos, respectively). Measurements indicated the development of diastolic dysfunction at 3 mos (E/A: 1.4 ± 0.1, 1.29 ± 0.05, 1.03 ± 0.05, 0.92 ± 0.05; DT: 148.6 ± 3.6, 157.3 ± 5.7, 168.3 ± 6.0, 184.3 ± 6.2 ms; lateral e': 12.8 ± 0.3, 12.1 ± 0.5, 10.2 ± 0.6, 10.8 ± 0.8 cm/s; E/e': 5.6 ± 0.1, 5.0 ± 0.22, 6.92 ± 0.46, 7.64 ± 0.47; control, 0, 1, and 3 mos, respectively). CONCLUSION: TDI is a useful method to detect early cardiac abnormalities complementing the conventional echocardiographic measurements. LV and RV systolic dysfunction found in the acute phase significantly improved during the first 3 months of therapy; however, deterioration of diastolic dysfunction was also observed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".