Effects of systolic heart failure on cerebral oxygen delivery-to-utilization matching in COPD
Bibliographic record
Abstract
Maintenance of blood oxygenation is paramount to preserve cerebral O 2 delivery during exercise. In fact, we previously found substantial impairments in cerebral oxygenation and exercise tolerance in COPD patients showing oxy-hemoglobin desaturation (Oliveira MF et al. Clin Physiol Funct Imaging 2012; 32:52).It remains unclear, however, whether this would also be the case when O 2 delivery is likely to be impaired by convective mechanisms (cerebral blood flow), e.g., in COPD plus heart failure with reduced left ventricular ejection fraction (HFrEF). Sixteen patients with COPD+HFrEF, 16 with COPD and 15 with HFrEF underwent a progressive cardiopulmonary exercise test on a cycle ergometer. Changes (Δ) in cardiac output (Q T ) by trans-thoracic cardioimpedance and mean arterial pressure (MAP) were measured. Pre-frontal oxygenation (HbO 2 ) and a blood flow index (BFI) were obtained by near infrared spectroscopy. COPD+HFrEF patients had blunted Δ Q T and Δ MAP responses compared to their counterparts. Δ BFI and Δ HbO 2 increased to a similar extent in COPD and controls; in contrast, they failed to increase in both groups with HFrEF – particularly in COPD+HFrEF (median interquartile range)Δ BFI/Δ oxygen uptake= 0.9 (15.7) vs. -10.3 (14.3) mMol.s -1 .L.min -1 f for COPD and COPD+HFrEF, respectively; p<0.05). Impairments in ΔHbO 2 in COPD+HFrEF were related to ΔBFI (r= 0.81; p<0.01) but not to arterialized O 2 content. In conclusion, HFrEF impairs cerebral blood flow and oxygenation during exercise in patients with COPD. The clinical relevance of these abnormalities (e.g., exercise limitation, cognition, cerebrovascular disease, respiratory sensation) remains to be elucidated in this patient population.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 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".