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Record W3034615126 · doi:10.35248/2684-1266.20.6.121

Do the Canadian Triage Guidelines Identify the Urgency of Oncological Emergencies

2020· article· en· W3034615126 on OpenAlexaboutno aff
Anas Alsharawneh, Joy Maddigan

Bibliographic record

VenueThe Journal of Cancer Research · 2020
Typearticle
Languageen
FieldMedicine
TopicNeutropenia and Cancer Infections
Canadian institutionsnot available
Fundersnot available
KeywordsTriageMedicineMedical emergencyEmergency departmentIntensive care medicineNursing

Abstract

fetched live from OpenAlex

Background: Triage in an emergency department (ED) plays a pivotal role as the volume of ED visitors is unpredictable. All ED patients are triaged to make sure that patients with urgent or life-threatening conditions are seen immediately while others with more stable conditions are safe to wait. Purpose: To examine the Canadian Triage and Acuity Scale (CTAS) guidelines to determine if the urgency of oncological emergencies can be prioritized appropriately using the CTAS guidelines. Methods: We used the Complaint Oriented Triage (COT 2012), which is an interactive computerized CTAS tool, to triage select oncological emergencies; superior vena cava syndrome, cardiac tamponade, tumor lysis syndrome, and febrile neutropenia. Results: Patients with cancer have a higher acuity compared to many other ED patients. However, most of the oncological emergencies can be subtle and nonspecific. The CTAS guidelines need to be strengthened to better represent the urgency of these life-threatening conditions. Conclusion: Although revisions have been implemented and the reliability of the CTAS tool has improved, the guidelines are designed to be generic and cannot address every health situation. Febrile neutropenia is an excellent example of the additional supports needed at triage to accurately determine the patient’s health status. Knowledge of the signs and symptoms of these emergencies will enable triage nurses to accurately differentiate the urgency of the different presenting complaints. Formalized education that prepares triage nurses to better understand the complexity of the symptom presentation and the needed care for patients with different oncological emergencies is essential.

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)0.003
metaresearch head score (Gemma)0.046
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.770
Threshold uncertainty score0.463

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.046
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.509
GPT teacher head0.571
Teacher spread0.062 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueThe Journal of Cancer ResearchSame topicNeutropenia and Cancer InfectionsFrench-language works237,207