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Record W4312193425 · doi:10.1016/j.tpr.2022.100125

Thoracic organ donation after circulatory determination of death

2022· article· en· W4312193425 on OpenAlexaff
Sanaz Hatami, Jennifer Conway, Darren H. Freed, Simon Urschel

Bibliographic record

VenueTransplantation Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsAlberta Biodiversity Monitoring InstituteUniversity of Alberta
Fundersnot available
KeywordsOrgan donationCirculatory systemMedicineDonationCardiologyComputer scienceInternal medicineTransplantationLawPolitical science

Abstract

fetched live from OpenAlex

The availability of thoracic organ transplantation as the treatment of choice for end-stage cardiac or pulmonary diseases is limited by the insufficient number of donor organs from brain dead donors, especially for organs where live-donation is not an option. Patients, who have not progressed to brain death, but have exhausted therapeutic options and life sustaining therapies are withdrawn can become donors with circulatory determination of death (DCD) when they meet criteria for the definition of this state. This approach can fulfill the wish of a patient to become an organ donor and also help to increase the number of donor organs. The DCD process exposes organs to prolonged warm ischemia that increases the possibility of primary graft dysfunction and failure. However, new technologies help in protecting the organs from cold preservation-related ischemia and facilitate resuscitation and monitoring of viability after the occurrence of the DCD-related ischemic insult. Herein, we review the opportunities and challenges in DCD thoracic organ transplantation, emerging techniques in preservation and monitoring of these organs and the potential effect of DCD thoracic organ transplantation on expanding the donor pool.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.293
Teacher spread0.279 · 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 teacher head, not a consensus.

Study designObservational
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".

Quick stats

Citations7
Published2022
Admission routes1
Has abstractyes

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