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Record W2996418870 · doi:10.1213/xaa.0000000000001153

Lund University Cardiac Assist System Induced Liver Laceration and Anterior Cord Infarction After Cardiac Arrest: A Case Report

2019· article· en· W2996418870 on OpenAlexaff
Thomas Drew, Adam Blackstock, Jonathan Aron

Bibliographic record

VenueA&A Practice · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsMedicineCardiopulmonary resuscitationResuscitationMyocardial infarctionEtiologyArteryAnesthesiaCardiologyInternal medicine

Abstract

fetched live from OpenAlex

We describe a hepatic laceration and subsequent anterior spinal artery syndrome in a 21-year-old man, secondary to prolonged cardiopulmonary resuscitation with a Lund University Cardiac Assist System (LUCAS2) mechanical cardiac compression device. We briefly review the current literature pertaining to hepatic injury from trauma due to cardiopulmonary resuscitation. The etiology of the anterior spinal artery syndrome in this patient is discussed. This case highlights that intra-abdominal causes of hypotension should be considered in patients after a prolonged resuscitation attempt. Extending focused cardiac ultrasound to exclude intra-abdominal free fluid should be routinely considered in these patients.

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)0.000
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 score0.008
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.002
Science and technology studies0.0040.002
Scholarly communication0.0030.003
Open science0.0020.003
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.0030.002

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 head0.010
GPT teacher head0.263
Teacher spread0.253 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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