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Record W2063703798 · doi:10.1136/emj.2006.045583

Use of blood alcohol concentration in resuscitation room patients

2007· article· en· W2063703798 on OpenAlexaff
Emese Csipke, Robin Touquet, Trupti Patel, Jason Franklin, Amy Brown, Paul Holloway, Nicola Batrick, Mike Crawford

Bibliographic record

VenueEmergency Medicine Journal · 2007
Typearticle
Languageen
FieldMedicine
TopicAlcohol Consumption and Health Effects
Canadian institutionsSt Mary's Hospital
Fundersnot available
KeywordsMedicineResuscitationBlood alcoholAlcoholEmergency medicineMedical emergencyIntensive care medicineAnesthesiaPoison controlInjury prevention

Abstract

fetched live from OpenAlex

OBJECTIVE: To clarify the use of blood alcohol concentration (BAC) in the emergency department resuscitation room, by comparing it with a subsequent alcohol questionnaire and by surveying patients' attitudes to BAC testing. DESIGN: Observational study. PARTICIPANTS: 273 resuscitation room patients at St Mary's Hospital, Paddington between August 2005 and February 2006. MAIN OUTCOME MEASURES: BAC comparison to questionnaire results, and attitudes to BAC testing. RESULTS: The level of agreement between positive screening by questionnaire and a BAC of >80 mg/100 ml was low (kappa = 0.29, 95% confidence interval 0.12 to 0.46) because each test measures different aspects of drinking. Patients accepted the use of BAC tests in detecting alcohol use, though a small minority reported concerns over confidentiality. CONCLUSION: Use of BAC testing complements later questionnaire screening to identify alcohol misuse in patients initially brought to the emergency department resuscitation room, providing results are fed back to the patient. Potential ethical, judicial and insurance concerns should not prevent the use of BAC when judged to be in the patient's best interest.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0040.000

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 head0.160
GPT teacher head0.420
Teacher spread0.261 · 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 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

Citations20
Published2007
Admission routes1
Has abstractyes

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