Third‐generation Blood Pumps With Mechanical Noncontact Magnetic Bearings
Bibliographic record
Abstract
This article reviews third-generation blood pumps, focusing on the magnetic-levitation (maglev) system. The maglev system can be categorized into three types: (i) external motor-driven system, (ii) direct-drive motor-driven system, and (iii) self-bearing or bearingless motor system. In the external motor-driven system, Terumo (Ann Arbor, MI, U.S.A.) DuraHeart is an example where the impeller is levitated in the axial or z-direction. The disadvantage of this system is the mechanical wear in the mechanical bearings of the external motor. In the second system, the impeller is made into the rotor of the motor, and the magnetic flux, through the external stator, rotates the impeller, while the impeller levitation is maintained through another electromagnetic system. The Berlin Heart (Berlin, Germany) INCOR is the best example of this principle where one-axis control combination with hydrodynamic force achieves high performance. In the third system, the stator core is shared by the levitation and drive coil to make it as if the bearing does not exist. Levitronix CentriMag (Zürich, Switzerland), which appeared recently, employs this concept to achieve stable and safe operation of the extracorporeal system that can last for a duration of 14 days. Experimental systems including HeartMate III (Thoratec, Woburn, MA, U.S.A.), HeartQuest (WorldHeart, Ottawa, ON, Canada), MagneVAD (Gold Medical Technologies, Valhalla, NY, U.S.A.), MiTiHeart (MiTi Heart, Albany, NY, U.S.A.), Ibaraki University's Heart (Hitachi, Japan) and Tokyo Medical and Dental University/Tokyo Institute of Technology's disposable and implantable maglev blood pumps are also reviewed. In reference to second-generation blood pumps, such as the Jarvik 2000 (Jarvik Heart, New York, NY, U.S.A.), which is showing remarkable achievement, a question is raised whether a complicated system such as the maglev system is really needed. We should pay careful attention to future clinical outcomes of the ongoing clinical trials of the second-generation devices before making any further remarks. What is best for patients is the best for everyone. We should not waste any efforts unless they are actually needed to improve the quality of life of heart-failure patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".