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Record W155586360

Radial head subluxation: how long do children wait in the emergency department before reduction?

2007· article· en· W155586360 on OpenAlexaff
Philippe Toupin, Martin H. Osmond, Rhonda Correll, Amy C. Plint

Bibliographic record

VenuePubMed · 2007
Typearticle
Languageen
FieldMedicine
TopicElbow and Forearm Trauma Treatment
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineEmergency departmentTriageSubluxationElbowPediatricsRetrospective cohort studyCohortEmergency medicineSurgeryInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the current emergency department (ED) wait times and treatment characteristics of children with radial head subluxation (RHS). METHODS: We performed a 2-year retrospective medical record review (April 1, 2004, to March 31, 2006) of all children who presented to our tertiary care pediatric ED with a discharge diagnosis of RHS, pulled elbow, dislocated elbow or nursemaid's elbow. RESULTS: We identified 501 cases of RHS in 427 children over a 2-year period. The mean age was 2.4 years (range 22 d-9.7 yr) and the injury was caused by a pull in 314 (62.8%) cases, a fall in 91 (18.2%) cases and a twist in 20 (4.0%) of the cases. The median time from triage to physician assessment was 1.3 hours, with 112 (23.5%) patients waiting > 2 hours and 33 (6.9%) waiting > 3 hours. The median time from triage to ED discharge was 1.7 hours, with 193 (41.2%) staying > 2 hours, 85 (18.1%) staying > 3 hours and 30 (6.4%) staying > 4 hours. Overall, 490 (99.2%) of these injuries were reduced in the ED: 98 (19.8%) were reduced prior to physician assessment and 309 (89.6%) were reduced on the first attempt. The technique used was pronation in 138 (52.7%), supination in 100 (38.2%), and pronation and supination in 24 (9.2%) cases. CONCLUSION: This large cohort indicates that children with RHS often have long ED waits before reduction and discharge. The majority of children with RHS are treated successfully with 1 reduction attempt. The data from this study will be used in planning a prospective study to shorten ED visits for patients with RHS.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

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

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 head0.022
GPT teacher head0.261
Teacher spread0.239 · 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

Citations13
Published2007
Admission routes1
Has abstractyes

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