The Effects of β <sub>1</sub> -Blockade on Oxidative Metabolism and the Metabolic Cost of Ventricular Work in Patients With Left Ventricular Dysfunction
Bibliographic record
Abstract
BACKGROUND: The mechanism for the beneficial effect of beta-blocker therapy in patients with left ventricular (LV) dysfunction is unclear, but it may relate to an energy-sparing effect that results in improved cardiac efficiency. C-11 acetate kinetics, measured using positron-emission tomography (PET), are a proven noninvasive marker of oxidative metabolism and myocardial oxygen consumption (MVO(2)). This approach can be used to measure the work-metabolic index, which is a noninvasive estimate of cardiac efficiency. METHODS AND RESULTS: The aim of this study was to determine the effect of metoprolol on oxidative metabolism and the work-metabolic index in patients with LV dysfunction. Forty patients (29 with ischemic and 11 with nonischemic heart disease; LV ejection fraction <40%) were randomized to receive metoprolol or placebo in a treatment protocol of titration plus 3 months of stable therapy. Seven patients were not included in analysis because of withdrawal from the study, incomplete follow-up, or nonanalyzable PET data. The rate of oxidative metabolism (k) was measured using C-11-acetate PET, and stoke volume index (SVI) was measured using echocardiography. The work-metabolic index was calculated as follows: (systolic blood pressure x SVI x heart rate)/k. No significant change in oxidative metabolism occurred with placebo (k=0.061+/-0.022 to 0.054+/-0.012 per minute). Metoprolol reduced oxidative metabolism (k=0.062+/-0. 024 to 0.045+/-0.015 per minute; P:=0.002). The work-metabolic index did not change with placebo (from 5.29+/-2.46 x 10(6) to 5.14+/-2. 06 x 10(6) mm Hg. mL/m(2)), but it increased with metoprolol (from 5. 31+/-2.15 x 10(6) to 7.08+/-2.36 x 10(6) mm Hg. mL/m(2); P:<0.001). CONCLUSIONS: Selective beta-blocker therapy with metoprolol leads to a reduction in oxidative metabolism and an improvement in cardiac efficiency in patients with LV dysfunction. It is likely that this energy-sparing effect contributes to the clinical benefits observed with beta-blocker therapy 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) | 0.001 | 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 | 0.001 |
| 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".