Totally Implantable Ventricular Assist System that Can Increase Brain Blood Flow
Bibliographic record
Abstract
In the clinical usage of the ventricular assist device (VAD), multiple organ failure becomes an important problem. To improve the clinical record of the VAD, another organ function may be vitally important. For that reason, we have been developing a VAD system aiming at improving another organ's function. Development of the vibrating flow pump (VFP), which can generate a very unique flow pattern from 10 Hz to 50 Hz, was ongoing in our Institute. In order to evaluate brain blood flow and oxygen consumption, HbO2 was measured with a NIRO monitoring device in healthy adult goats. Four goats were anesthetized with halothane inhalation; then left thoracotomy was performed for the left heart bypass. HbO2 of the brain was measured by recording of the hemodynamic variables during left heart assistance with the VFP system. During left heart bypass with the VFP system, hemodynamic parameters stayed within normal range, and satisfactory pump output was easily obtained. Pump output stayed within 20-40% bypass to evaluate the effect of high frequency oscillated assist flow on brain blood flow during the same cardiac output. Interesting results were observed during the experiments. During 30 Hz drive of the VFP left heart assistance, HbO2 suggested that brain blood flow significantly increased compared with another drive frequency assistance during the same total cardiac output. These results suggest that we can control the brain blood flow with a totally implantable VAD system such as the VFP system.
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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 | 0.000 |
| 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 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".