MétaCan
Menu
Back to cohort
Record W2613180961 · doi:10.22374/cjgim.v12i1.205

Stop that Train! I Want to Get Off: Emergency Care for Patients with Advanced Dementia

2017· article· en· W2613180961 on OpenAlexvenueno aff
Kieran L. Quinn, Corita R. Grudzen, Alexander K. Smith, Allan S. Detsky

Bibliographic record

VenueCanadian Journal of General Internal Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDementiaEmergency departmentMedical emergencyIntensive care medicineNursingInternal medicineDisease

Abstract

fetched live from OpenAlex

The prevalence of advanced dementia (AD) is expected to increase dramatically over the next few decades. Patients with AD suffer from recurrent episodic illnesses that frequently result in transfers to acute care hospitals. The default pathway followed by some emergency physicians, internists and intensivists who see those patients is to prioritize disease-directed therapies over attention to the larger picture of AD. While this strategy is desired by many families, some families prefer a different approach. This essay examines the reason why there can be a failure to focus on the over-arching issue of AD and offers suggestions for improvement. Gaps in information and physician workload are important factors, but we argue that until physicians who see patients in emergency departments learn to pause first and ask “Why are we doing this?” they will revert to their comfort zone of ordering tests and therapies that may be unwanted. A separate emergency palliative care pathway may be one solution. Shifting the focus back to the larger picture of AD and away from the physiologic disturbance of the moment may alter the trajectory of care in ways that truly respect the wishes of some patients and their families.

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 score0.257
Threshold uncertainty score0.811

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.072
GPT teacher head0.384
Teacher spread0.312 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of General Internal MedicineSame topicPalliative Care and End-of-Life IssuesFrench-language works237,207