Estimation of Cardiac Output by C0(2) Rebreathing during Incremental Exercise in Patients with Coronary Artery Disease
Bibliographic record
Abstract
In 9 patients with stable coronary artery disease, measurements were made during a progressive incremental maximum exercise test of O(2) intake (VO(2)), CO(2) output (VCO(2)), mixed venous PCO(2) by an exponential rebreathing method, and end-tidal PCO(2) (PETCO(2)) to estimate arterial PCO(2) (PaCO(2)). By applying the Fick principle to CO2, these measurements were used to derive cardiac output at several incremental work loads. Each subject underwent two incremental exercise studies to establish the reproducibility of the technique, and also a steady state exercise study to compare steady state responses with unsteady state incremental exercise. The results were also compared to those previously obtained in healthy subjects. PvCO(2) showed a curvilinear increase with increasing VCO(2) with only a small intersubject variation. Cardiac output-oxygen uptake relationships (Q/VO(2)) were similar in the two incremental studies (intercepts 6.27 and 6.641/min; slopes 4.82 and 4.58 1/min), and also similar to that obtained previously in healthy subjects (intercept 6.441/min; slope 4.71 1/min). Low calculated values for cardiac output were obtained at high exercise levels during the incremental test in those subjects in whom PETCO(2) fell at the highest work loads. This effect could be corrected for by using a PETCO(2) obtained 1 min prior to rebreathing, suggesting that the low values of Q were an artifact due to a transient decrease in PaCO(2) secondary to hyperventilation. At any given VO(2) or VCO2, PvCO(2) and Q were the same in both steady state and unsteady state incremental exercise. The exponential CO(2) rebreathing method may be reliably applied to incremental exercise testing to evaluate the cardiac output responses to exercise in patients with cardiac disease.
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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) | 0.001 | 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 | 0.001 | 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".