Novel Extra Aortic Counterpulsation Device for Enhancing Cardiac Performance
Bibliographic record
Abstract
Heart failure is the fastest growing cardiovascular disorder. Incidence is rising at a rate of approximately 2% to 5% in people over 65 years of age, and 10% in people over 75 years of age [1]. Over 13 Million people suffer from heart failure in the USA, Europe, Canada and Australia, and heart failure is a leading cause of hospital admissions and re-admissions in Americans older than 65 years of age [2]. The secondary heart pump system is the expansion and recoil of the aorta which reduces heart load and drives left coronary artery blood flow. Increases in aortic stiffness are a result of elastin degradation due to ageing and/or cardiovascular diseases such as atherosclerosis [3–5], which increase heart load and pulse pressure [6–10]. Significantly higher aortic stiffness is found in hypertensive and heart failure suffers [6,7,9–11]. Specifically, healthy aged subjects have been found to have aortic stiffness 50% higher relative to subjects in a young and healthy group, while symptomatic hypertensive patients in heart failure have aortic stiffness further increased by approx. 77% relative to the age matched healthy cohort (i.e. by ∼88% relative to the young and healthy group) [11].
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".