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Improved Outcomes with Negative Pressure Ventilation (NPV) during Normothermic Ex Vivo Lung Perfusion

2017· article· en· W2614149722 on OpenAlexaff
Nader S. Aboelnazar, Sayed Himmat, Sanaz Hatami, Christopher W. White, Darren H. Freed, Jayan Nagendran

Bibliographic record

VenueTransplantation · 2017
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsCanadian VIGOUR CentreUniversity of Alberta
Fundersnot available
KeywordsMedicineBronchopleural fistulaVentilation (architecture)Ex vivoLung transplantationLungAnesthesiaPerfusionMechanical ventilationIn vivoInternal medicineBiologyPneumonectomy

Abstract

fetched live from OpenAlex

Introduction: Normothermic Ex Vivo Lung Perfusion (EVLP) has increased the rate of donor organ utilization, and increased volumes of lung transplantation at centers that have adopted the technology. Current ventilation methodology for EVLP uses Positive Pressure Ventilation (PPV) with all clinically available devices. We developed a novel ventilation system that replicates in vivo lung ventilation wherein a negative pressure is applied to the pleural surface of the lung (NPV). We hypothesize that NPV would be superior to PPV during EVLP. Methods: A fully automated NPV EVLP platform was developed and compared to conventional (PPV) EVLP. Pig and human lungs were perfused for 12 hours and physiologic parameters, cytokine profile, bronchopleural fistula (BPF) and edema formation were analyzed. A total of 24 pigs were perfused, divided equally into 4 groups based on ventilation strategy and perfusate composition: Acellular-NPV vs. Acellular-PPV, and, Cellular-NPV vs. Cellular-PPV (Acellular: STEEN solution™ & Cellular: packed Red Blood Cells + STEEN solution™). Preliminary unutilized human lungs compared Cellular-NPV (N = 2) and Cellular-PPV (N = 2). Results: Using ANOVA pairwise comparison (mean ± SE), pig and human lungs showed stable trends in lung oxygenation (>400 mmHg) and physiological parameters. Cytokine analysis of the pig lungs showed significantly lower TNFa, IL-6, and IL-8 production with an NPV strategy regardless of perfusate (p < 0.05). Moreover, there was a 38% lower incidence of BPF with a NPV vs. PPV strategy (p = 0.02). Edema after 12 hours of EVLP for pRBCs using NPV and PPV were 15.4 ± 2.0% and 40.6 ± 9.0% (p < 0.05); while with acellular using NPV and PPV it was 33.2 ± 6.4% and 88.1 ± 11.0% (p < 0.05) (Figure 1), respectively. Interestingly, with human lung perfusion we found edema at 12 hours for pRBCs using NPV and PPV were −10.8 ± 9.0% and 37.1 ± 9.0% (p < 0.05) (Figure 2), respectively. Conclusions: Negative pressure ventilation (NPV) is potentially more beneficial compared to traditional positive pressure ventilation (PPV), with significantly less inflammation, bullae, and edema formation during extended EVLP for both perfusate groups. The value of a NPV strategy may lead to further improvements to currently available clinical EVLP platforms. CIHR. CNTRP. UHF.FIGURE 1: Edema comparison between Negative Pressure Ventilation (NPV) EVL and Positive Pressure (PPV) EVLPand their perspective perspective perfusate groups.FIGURE 2: Negative edema formation with negative pressure ventilation (NPV) compared to positive pressure ventilation (PPV).

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.269
Teacher spread0.258 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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