An evaluation of hard-shell venous reservoir integrated pressure relief valve pressure mitigation performance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Vacuum assisted venous drainage (VAVD) requires the sealing of the hard-shell venous reservoir, thereby creating circumstances where reservoir pressurization may occur. Manufacturers utilize integrated pressure relief valves (IPRV) to mitigate pressurization risk; however, accidents have been reported even with these devices. We have undertaken a performance evaluation of IPRV's in a large number of hard-shell venous reservoirs. METHODS: Reservoirs were sealed and gas insufflated while measuring reservoir internal pressure. Linear regression models were developed to depict the association between internal pressure and gas inflow rate. External secondary one-way valves (ESOV) were assessed for pressure mitigation performance. An assisted venous drainage survey was circulated to Canadian Clinical Perfusionists. RESULTS: < 0.001) in internal reservoir pressures (range: 0.04-161.41 mmHg) was observed across the titrated gas inflow rate (0.5-10.0 l/min). The regression models demonstrate excellent predictive performance (SE: 0.008-0.309). ESOV's reduce the reservoir pressure below that of the IPRV; however, they cannot eliminate reservoir pressurization. The survey showed a majority (91%) of respondents use VAVD, and reservoir pressurization events occur regularly (18%). CONCLUSIONS: Significant variability among reservoir's IPRV to mitigate reservoir pressurization exists. The predictive models are extremely accurate at estimating the internal pressure. ESOV performance limitations moderate their utility as a backup pressure mitigation technique. A significant number of reservoir pressurization events are occurring with the use of VAVD. As a result, standardized communication from manufacturers on the purpose and performance of IPRV is recommended in order to delineate the limitations of these devices.
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.
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 | 0.001 | 0.001 |
| 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 it