Incidence of cardiovascular risk factors and exercise phenotyping in cardiomyopathies: One size does not fit all
Bibliographic record
Abstract
Background: Cardiovascular disease risk factors (CVDRF) are linked to increased morbidity in cardiomyopathies (CMP), but whether new onset CVDRF differ among CMPs is unknown. In addition, whether the acute exercise response during cardiopulmonary exercise testing (CPET) differs among CMPs remains unclear. Methods: This single-center, retrospective study analyzed patients with arrhythmogenic, hypertrophic, and dilated (DCM) cardiomyopathy without CVDRF at baseline. Resting echocardiography and CPET were performed, and exercise response was assessed depending on sex and CMP. After a median follow-up of 19.5 months, CPET and echocardiography were analyzed in relation to the development of new CVDRF. Results: A total of 104 CMPs were included (median age 53.0 years). New-onset CVDRF was rare (11.5 %) and driven by arterial hypertension (8.7 %) but did not differ among CMPs. DCM displayed significantly lower resting left ventricular ejection fraction (40.5 %, interquartile range, IQR, 11.5 %, p < 0.001), diastolic function (E/e' 9.3, IQR 5.5, p < 0.001), and had the lowest peak systolic blood pressure (170.0 mmHg, IQR 52.5 mmHg, p = 0.011), predicted peak oxygen consumption (82.0 %, IQR 39.8 %, p = 0.003), oxygen pulse (101.0 %, IQR 28.8 %, p = 0.030) as well as lower ventilatory (VP, 5.5 mmHg, IQR 1.4 mmHg, p = 0.033) and circulatory (CP, 4096.0 mL/kg/min x mmHg, IQR 2299.3 mL/kg/min x mmHg, p = 0.015) power compared to the other groups. Lower VP (5.0 mmHg, IQR 1.3 mmHg, p = 0.003) and CP (3660.0 mL/kg/min x mmHg, IQR 3298.0 mL/kg/min x mmHg, p = 0.004) were observed for females. Conclusions: Arterial hypertension was the most common CVDRF among CMPs, underscoring the importance of monitoring this outcome. Exercise limitations differ between CMPs and should be interpreted depending on sex.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".