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Predictors Of 24-Hour Mortality After Transfer To The Acute Palliative Care Unit (APCU)

2017· other· en· W6908551164 on OpenAlexaboutno aff

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2017
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPalliative careDeliriumMedical recordIntensive care unitDistressMalignancyRetrospective cohort study

Abstract

fetched live from OpenAlex

Abstract:Context: Although patients are assessed by the palliative care consultation team before admission to the acute palliative care unit (APCU), patients may die within 24 hours of admission, causing distress to clinicians and the patientu2019s family. Objectives: To assess the risk factors associated with sudden death.Methods: A retrospective study of medical records of patients transferred to the APCU from October 1, 2013 to October 1, 2017 was performed to identify those who died within 24 hours after transfer. Characteristics of these patients were compared to a control group composed of a random sample of patients that were alive 24 hours after transfer to the APCU. Results: Seventy-nine patients died within 24 hours after transfer to the APCU. Compared to the control group, the patients that died within 24 hours were more likely to have a higher Memorial Delirium Assessment Scale (MDAS) score (P = 0.0001), a hematologic malignancy (P = 0.0002), to be transferred during weekdays (P = 0.0002), to be unresponsive (P = 0.0023), to be on oxygen therapy (P = 0.0395), and to have a higher Eastern Cooperative Oncology Group (ECOG) performance status (P = 0.0275). There was no significant difference in Edmonton Symptom Assessment System (ESAS) scores between groups.Conclusions: Patients with delirium, oxygen requirements, hematologic malignancies, low performance status, and unresponsiveness at the time of transfer are more likely to die within 24 hours of APCU transfer. A more thorough pre-transfer evaluation of these patients is required to minimize distress to patients, families, and staff.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Bibliometrics, Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.094
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0180.019
Science and technology studies0.0010.003
Scholarly communication0.0050.012
Open science0.0220.012
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0260.008

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 head0.124
GPT teacher head0.388
Teacher spread0.264 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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