Pericardial pressure in experimental chronic heart failure.
Bibliographic record
Abstract
BACKGROUND: In the normal heart, pericardial pressure is greater than previously believed. OBJECTIVES: To explore the contribution of pericardial constraint to the elevated left ventricular (LV) end-diastolic pressure in chronic heart failure (CHF). ANIMALS AND METHODS: Pericardial pressure was measured directly in 11 dogs with CHF. Seven dogs were instrumented with LV and right ventricular micromanometers and epicardial pacing leads, and paced at 240 to 260 beats/min for four to seven weeks. After the development of CHF, a left thoracotomy was performed and a flat pericardial balloon was positioned over the LV free wall through a slit in the pericardium. RESULTS: LV end-diastolic pressure was 31+/-9 mmHg, and pericardial pressure only 7+/-2 mmHg. Nitroglycerin in six dogs decreased LV end-diastolic pressure from 33+/-8 to 28+/-7 and pericardial pressure from 7+/-2 to 6+/-3 mmHg (both P<0.05). Calculated transmural LV end-diastolic pressure also decreased (26+/-8 to 22+/-7 mmHg, P<0.05). Volume loading in five dogs increased LV end-diastolic pressure from 29+/-8 to 42+/-10 mmHg (P<0.05), pericardial pressure from 6+/-3 to 12+/-6 mmHg (not significant) and transmural LV end-diastolic pressure from 23+/-7 to 30+/-7 mmHg (not significant). When the pericardium was opened in three dogs, the LV end-diastolic pressure decreased by 5 mmHg. Four previously uninstrumented dogs were studied to exclude the effects of epicardial scarring; LV end-diastolic pressure was 42+/-6 mmHg and pericardial pressure was 10+/-6 mmHg. CONCLUSION: Pericardial constraint, a prerequisite for pericardially mediated ventricular interaction, was not present to the same extent in this model of CHF as in acute models, probably reflecting the importance of pericardial remodelling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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 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".