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Record W2793198972 · doi:10.1089/ther.2017.0052

Use of Cold Fluids in Postcardiac Arrest Therapeutic Hypothermia: A Safety Analysis

2018· article· en· W2793198972 on OpenAlexaffabout
Julien Duranceau, Michaël Mayette

Bibliographic record

VenueTherapeutic Hypothermia and Temperature Management · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsMedicineHypothermiaOdds ratioConfidence intervalAnesthesiaProspective cohort studyPopulationTargeted temperature managementRetrospective cohort studySurgeryInternal medicineResuscitationReturn of spontaneous circulationCardiopulmonary resuscitation

Abstract

fetched live from OpenAlex

Therapeutic hypothermia (TH) has been part of the standard care of postresuscitation patients for more than a decade. Multiple cooling methods are available, including the administration of cold intravenous (IV) fluids. Although this method is widely used, the safety of administration of large volumes of cold IV fluids has not been clearly demonstrated in the literature, and recent evidence points to potential deleterious effects associated with administration of large IV fluid volumes. We conducted a retrospective cohort study among patients who have been treated with TH after cardiac arrest between November 2011 and November 2013 at a tertiary care hospital in Sherbrooke, Quebec, Canada. The primary outcome was the effect of IV fluid quantity on the 28-day survival rate. We reviewed 29 cases, with a total 28-day surviving rate of 51.7%. After adjusting for confounding variables, 28-day surviving rate was not significantly associated with the amount of fluids administrated (odds ratio = 1.034; confidence interval 95% [0.741-1.464]; p = 0.85). The amount of fluids did not influence the variation of the pulmonary component of the sequential organ failure assessment score between days 1 and 3 (ρ = -0.2, p = 0.34). Despite a small sample of patients, cold IV fluids in TH appear safe in the postcardiac arrest population. These findings should be reproduced in a larger, prospective study.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.017
GPT teacher head0.258
Teacher spread0.241 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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