Deceived by the Fick principle: blood flow distribution in heart failure
Bibliographic record
Abstract
AIMS: The Fick principle states that oxygen uptake (V̇O2) is cardiac output (Qc) * arterial-venous O2 content difference [ΔC(a-v)O2]. Blood flow distribution is hidden in Fick principle, and its relevance during exercise in heart failure (HF) is undefined. To highlight the role of blood flow distribution, we evaluated peak exercise V̇O2, Qc, and ΔC(a-v)O2, before and after HF therapeutic interventions. METHODS AND RESULTS: Symptom-limited cardiopulmonary exercise tests with Qc measurement (inert gas rebreathing) was performed in 234 HF patients before and 6 months after successful exercise training, cardiac resynchronization therapy, or percutaneous edge-to-edge mitral valve repair. Considering all tests (n = 468), a direct correlation between peakV̇O2 and peakQc (R2 = 0.47) and workload (R2 = 0.70) was observed. Patients were grouped according to treatment efficacy in Group 1 (peakV̇O2 increase >10%, n = 93), Group 2 (peakV̇O2 change between 0 and 10%, n = 60), and Group 3 (reduction in peakV̇O2, n = 81). Post-treatment peakV̇O2 changes poorly correlated with peakQc and peakΔC(a-v)O2 changes. Differently, post-procedure peakQc vs. peakΔC(a-v)O2 changes showed a close negative correlation (R2 = 0.46), becoming stronger grouping patients according to peakV̇O2 improvement (R2 = 0.64, 0.79, and 0.58 in Groups 1, 2, and 3, respectively). In 76% of patients, peakQc and ΔC(a-v)O2 changes diverged regardless of treatment. CONCLUSION: The bulk of these data suggests that blood flow distribution plays a pivotal role on peakV̇O2 determination regardless of HF treatment strategies. Accordingly, for assessing HF treatment efficacy on exercise performance, the sole peakV̇O2 may be deceptive and the combination of V̇O2, Qc and ΔC(a-v)O2, must be considered.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".