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Record W2148639588 · doi:10.1177/1089253210379271

Vasopressin and Methylene Blue: Alternate Therapies in Vasodilatory Shock

2010· review· en· W2148639588 on OpenAlexaff
Dominique Lavigne

Bibliographic record

VenueSeminars in Cardiothoracic and Vascular Anesthesia · 2010
Typereview
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsMedicineVasopressinSeptic shockAnesthesiaHypoxemiaIntensive care unitShock (circulatory)Intensive care medicineCardiologySepsisInternal medicine

Abstract

fetched live from OpenAlex

Cardiac surgery with cardiopulmonary bypass (CPB) is frequently complicated by vasoplegic syndrome, a vasodilatory shock state. Traditional treatment based on fluid resuscitation and catecholamine drugs is ineffective in a number of patients. Clinical trials investigating both vasopressin and methylene blue as additional rescue or preventative therapy are reviewed. Vasopressin is suggested to retain its vasoconstrictive power in hypoxemia and acidosis, lower pulmonary hypertension, reduce supraventricular arrhythmias, and accelerate intensive care unit (ICU) recovery. Safety concerns include frequent thrombocytopenia and potentially altered mesenteric and renal perfusion. Methylene blue is suggested to facilitate CPB weaning, reduce renal, respiratory, arrhythmic, and septic complications, reduce mortality, and accelerate ICU and hospital recovery. Safety concerns include oximeter interference, pulmonary hypertension, neurotoxicity, arrhythmias, and potentially altered coronary, mesenteric, and renal perfusion. Research on both molecules is ongoing and has yet to confirm on a larger scale their efficacy and safety as treatments for post-CPB vasoplegic syndrome.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.018
GPT teacher head0.325
Teacher spread0.307 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations33
Published2010
Admission routes1
Has abstractyes

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