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Record W2834818621 · doi:10.1213/xaa.0000000000000802

In Situ Cold Perfusion of the Liver on Cardiopulmonary Bypass: Coagulopathy and Its Correction: A Case Report

2018· article· en· W2834818621 on OpenAlexaff
Mohammed Emdadul Haque, Adriaan Van Rensburg, Stuart A. McCluskey, Massimiliano Meineri, Matteo Parotto

Bibliographic record

VenueA&A Practice · 2018
Typearticle
Languageen
FieldMedicine
TopicTrauma, Hemostasis, Coagulopathy, Resuscitation
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsCoagulopathyCardiopulmonary bypassMedicinePerfusionLiver perfusionCardiac surgeryCardiologyAnesthesiaIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

We report a case of profound coagulopathy after the dual insult of cold in-situ perfusion of the liver and cardiopulmonary bypass in a patient undergoing complex hepatobiliary and cardiovascular surgery. Management of this coagulopathy with conventional blood products was hindered by elevated venous pressures, thought to contribute to persistent bleeding and risked liver and right ventricular dysfunction, necessitating a change in strategy. Anesthesiologists should consider fluid-restrictive strategies to correct coagulopathy in combined liver and cardiac surgery.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0040.003
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0090.008
Insufficient payload (model declined to judge)0.0020.001

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 head0.025
GPT teacher head0.307
Teacher spread0.282 · 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 designCase report
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

Citations0
Published2018
Admission routes1
Has abstractyes

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