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Record W2964409357 · doi:10.1097/njh.0000000000000585

Evaluating the Pharmacological Management of Terminal Delirium in Imminently Dying Patients With and Without the Comfort Measure Order Set

2019· article· en· W2964409357 on OpenAlexaff
M. Linda Sutherland, Kalli Stilos

Bibliographic record

VenueJournal of Hospice and Palliative Nursing · 2019
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsDeliriumSet (abstract data type)Terminal (telecommunication)MedicinePalliative careTerminal careTerminally illIntensive care medicineMedical emergencyNursingComputer science

Abstract

fetched live from OpenAlex

Terminal delirium is a distressing irreversible process that occurs frequently in the dying phase, often misdiagnosed and undertreated. A previous study in our organization revealed that terminal delirium was a poorly managed symptom at end of life. Pharmacological options are available in an existing order set to manage this symptom. The management plans of 41 patients identified as having terminal delirium were further evaluated. Elements extracted included medications prescribed to manage terminal delirium, whether medication changes occurred, and whether they were administered and effective. Patients with the order set were more comfortable as compared with the group without. Both groups had several changes made by the palliative care team. Nurses did not administer prescribed as-needed medication to more than one-third of patients. Modifications will be made to the existing order set, and additional education for staff will be organized.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.137
GPT teacher head0.462
Teacher spread0.325 · 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 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

Citations7
Published2019
Admission routes1
Has abstractyes

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