Importance of shear in prosthetic valve closure dynamics.
Bibliographic record
Abstract
BACKGROUND AND AIM OF STUDY: The results of recent hematological studies have suggested that, under non-physiological flow conditions, circulating procoagulant proteins activate the coagulation cascade. In the present study, in-vitro estimates of flow transients at or near the time of valve closure, including regional backflow velocity (RBV, m/s), flow acceleration (m/s2), and rate of acceleration (jerk, m/s3), have shed new light on the blood-damage potential of prosthetic valves. METHODS: Several prosthetic valves were tested in a pulse duplicator under simulated cardiac conditions. A unique prototype subsystem (Leonardo(VSI)) was used to measure the projected dynamic valve areas (PDVAs) from backlit valves. The regional flow velocity was derived by dividing the time-dependent volumetric flow rate by the PDVA. The flow acceleration and jerk were subsequently obtained as time derivatives of the flow velocity. RESULTS: Current mechanical valves have overt flow transients at valve closure, relating to leaflet nonresponse to flow deceleration and residual PDVA. In contrast, tissue valves initiate closure during the flow deceleration phase, and seal when closed, thus preventing supra-physiological backflow transients. The estimated average RBV transients at or near closure ranged from 45 to 162 m/s for mechanical valves, and from 3 to 10 m/s (i.e., ca. 93% less) for tissue valves. The average derived flow acceleration and jerk transients ranged from +2,235 to -1,786xg and from +10.8 x 106 to -7.5 x 10(6) m/s3 for mechanical valves, respectively, and were substantially lower for tissue valves (ca. 90-99% less). CONCLUSION: The study results implicate that RBV transients at or near mechanical valve closure, and not the forward or closed flow phase, as being primary to the shear-induced activation of the coagulation cascade. Results obtained in vitro for an experimental trileaflet mechanical valve (Triflo) were tested only in the aortic site similar to those obtained with tissue valves.
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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) | 0.000 | 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".