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Record W6959394500 · doi:10.7939/r3pk0768c

Oligoanalgesia in Adult Colles Fracture Patients Admitted to the Emergency Department

2015· dissertation· en· W6959394500 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Alberta Library · 2015
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicPasture and Agricultural Systems
Canadian institutionsnot available
Fundersnot available
KeywordsEmergency departmentColles' fractureIncidence (geometry)HomogeneousRetrospective cohort studyAge groups

Abstract

fetched live from OpenAlex

Pain is the most common reason that patients frequent the Emergency Department. Pain is a complex symptom to assess properly and according to research, it appears to be poorly managed in the Emergency Department. The majority of research has focused on the incidence of oligoanalgesia in large samples of patients with heterogeneous injuries. Pain management will differ depending on the type of injury a patient has sustained. The occurrence of oligoanalgesia in a homogeneous injury, such as Colles fracture, has yet to be explored. This is a pilot study using a retrospective chart review to determine the incidence of oligoanalgesia in adult Colles fracture patients admitted to two urban Emergency Departments in Western Canada. One hundred and fifty charts from site 1 and site 2 were analyzed from the last five years to determine the occurrence of oligoanalgesia. There was no statistical difference in age groups, who received analgesia, and females were more likely to receive analgesia, but this was not significant. Age and sex were not significantly associated with receipt of an opioid. Age and sex were significant predictors of pain assessment. Neither age nor sex were significant predictors of pain reassessment. Pain reassessment was only completed in 47% of patients who received an initial pain assessment, This was significant when compared to the best practice standard.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.516
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.006
GPT teacher head0.179
Teacher spread0.173 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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