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Record W4404726208 · doi:10.1016/j.cjco.2024.11.013

Factors Associated With Withdrawal of Life-Sustaining Therapy After Out-of-Hospital Cardiac Arrest

2024· article· en· W4404726208 on OpenAlexaffabout
Michael D. Elfassy, Mena Gewarges, Steve Fan, Bianca McLean, Dustin Tanaka, Amrita Bagga, S. Bennett, Isabella Janusonis, Clara Osei-Yeboah, Jeremy Rosh, Daniel T. Teitelbaum, Jaime C. Sklar, Manpreet Basuita, Damon C. Scales, Adriana Luk, Paul Dorian

Bibliographic record

VenueCJC Open · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsSunnybrook Health Science CentreUniversity Health NetworkUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineIntensive care medicine

Abstract

fetched live from OpenAlex

Background: Out-of-hospital cardiac arrest (OHCA) is a leading cause of global mortality. Most patients get hypoxic brain injury, which often leads to the withdrawal of life-sustaining therapy (WLST) because of concerns of poor neurologic prognosis. This study describes the rates and reasons for WLST and identifies factors associated with early WLST, defined as occurring within 72 hours of admission. Methods: We conducted a multicentered, retrospective cohort study of adult OHCA patients admitted to 3 large academic hospitals in Toronto from January 2012 to December 2019. Data were extracted from medical records and analyzed using descriptive statistics and cause-specific hazards regression models to identify factors associated with WLST and documented goals of care (GOC) discussions. Results: Among 264 patients (median age 66 years, 76.5% male), the in-hospital mortality rate was 62.1%. Of the nonsurvivors, 67.1% died following WLST (90% of cases because of concern of poor neurologic prognosis), with 50% of WLST occurring <72 hours from admission. Formal declaration of brain death only occurred 9.8% of the time. Older age significantly increased the risk of early WLST. GOC discussions were documented only 56.4% of the time in the overall cohort and significantly associated with WLST across all time periods. Conclusions: This study highlights the high incidence of WLST, and specifically early WLST, in OHCA patients. GOC discussions are routinely undocumented and is associated with a higher likelihood of WLST. These findings underscore heterogeneity of practice, and the influence of GOC discussions in education and shared decision making.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.351

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)0.0000.000

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 head0.021
GPT teacher head0.294
Teacher spread0.273 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2024
Admission routes2
Has abstractyes

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