Exploring physiological determinants of ventilatory inefficiency in hypertrophic cardiomyopathy patients
Bibliographic record
Abstract
Abstract Background The role of cardiopulmonary exercise test (CPET) in hypertrophic cardiomyopathy (HCM) has been previously examined, revealing two prognostic parameters: peak Vo2 and the VE/VCO2 slope. Specifically, individuals with a VE/VCO2 value above 31 (ventilator inefficiency) demonstrate a poorer prognosis. Purpose This study aims to analyze the physiological factors contributing to ventilatory inefficiency in individuals with HCM. Methods In this retrospective study, 43 patients HCM patients underwent resting transthoracic echocardiography, CPET combined with echocardiography during physical exertion, and cardiac magnetic resonance imaging. Ventilatory inefficiency was defined as a VE/VCO2 slope exceeding 31, leading to the identification of two groups: Group A (those with ventilatory inefficiency) and Group B (those without ventilatory inefficiency). Results Nine patients exhibited ventilatory inefficiency, while 34 had a normal VE/VCO2 slope. No statistically significant differences were found between the two groups concerning clinical and therapeutic characteristics. Subjects with ventilatory inefficiency showed reduced oxygen pulse (8.3 ± 2.6 vs 11.7 ± 4, p 0.013) and peak VO2 values (13 ± 5 vs 19 ± 5, p 0.005), lower left ventricle global longitudinal strain (-15±3 vs -17± 2, p 0,012), the exertional TAPSE/SPAP ratio (0.46 [0.32-0.48] vs 0.58 [0.47-0.80], p 0.001), exertional TAPSE (23 ± 3 vs 28 ± 4, p 0.001), and indexed stroke volume of the left ventricle assessed by cardiac magnetic resonance imaging (38±8 vs 48±10, p 0.011) (Table 1). The right ventricular function under physical exertion (peak TAPSE and TAPSE/sPAP) and left ventricular functional parameters (index stroke volume and global longitudinal strain) predicted the presence of ventilatory inefficiency. Conclusions This study highlights the role of exertional parameters in the origin of ventilatory inefficiency.Correlation tableFigure with scatter plot
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".