MétaCan
Menu
Back to cohort
Record W1542272803 · doi:10.5811/westjem.2012.10.13864

Letter to the Editor and Reply: Sedation-assisted Orthopedic Reduction in Emergency Medicine: The Safety and Success of a One Physician/ One Nurse Model

2013· letter· en· W1542272803 on OpenAlexaffabout
Samuel Campbell, Patrick Froese

Bibliographic record

VenueWestern Journal of Emergency Medicine · 2013
Typeletter
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsQueen Elizabeth II Health Sciences Centre
Fundersnot available
KeywordsMedicineSedationEmergency departmentPhysician assistantsPatient carePatient safetyMedical emergencyNova scotiaNurse practitionersNursingHealth careAnesthesia

Abstract

fetched live from OpenAlex

To the Editor: We applaud Vinson and Hoehn for eloquently demonstrating that the performance of sedation assisted procedures in the emergency department (ED) does not necessarily require a 2 physician team. From a Canadian perspective, where single physician coverage in smaller EDs is common, this has important implications in terms of efficiency of patient care, reduction in the need for patient transfer and decreasing the time to definitive treatment for ED patients. We would like to draw attention to a model of care practiced in Halifax, Nova Scotia for over 15 years, using a team consisting of an advanced care paramedic (ACP) and a single physician, the former to conduct the sedation, and the latter to do the procedure.1 The skills of ACPs complement specific supplementary training in Procedural Sedation and Analgesia (PSA) to produce, in our opinion, expert ED sedationists, and our database of over 4000 safely conducted PSAs attest to this. Although performing PSA is primary role of ACPs in our ED, success with this has expanded our use of paramedics to a number of other ED tasks, freeing up other staff to perform what they do best.2

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.494
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.038
GPT teacher head0.315
Teacher spread0.277 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueWestern Journal of Emergency MedicineSame topicCardiac, Anesthesia and Surgical OutcomesFrench-language works237,207