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Record W2187467166 · doi:10.1016/j.joad.2015.07.004

Emergency care outcomes of acute chemical poisoning cases in Rawalpindi

2015· article· en· W2187467166 on OpenAlexafffund
Ibrar Rafique, Umbreen Akhtar, Umar Farooq, Mussadiq Khan, Junaid A. Bhatti

Bibliographic record

VenueJournal of Acute Disease · 2015
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsSunnybrook Health Science CentreHealth Sciences Centre
FundersMinistry of Health, British Columbia
KeywordsMedicineEmergency departmentEmergency medicineTertiary careLogistic regressionOccupational safety and healthMedical emergencyHarmInjury preventionHealth carePoison controlSuicide preventionOdds ratioFamily medicineEnvironmental healthNursingInternal medicine

Abstract

fetched live from OpenAlex

To assess the emergency care outcomes of acute chemical poisoning cases in tertiary care settings in Rawalpindi, Pakistan. The data were extracted from an injury surveillance study conducted in the emergency departments (ED) of three tertiary care hospitals of Rawalpindi city from July 2007 to June 2008. The World Health Organization standard reporting questionnaire (one page) was used for recording information. Associations of patients' characteristics with ED care outcomes, i.e., admitted vs. discharged were assessed using logistic regression models. Of 62 530 injury cases reported, chemical poisoning was identified in 434 (0.7%) cases. The most frequent patient characteristics were poisoning at home (61.9%), male gender (58.6%), involving self-harm (46.0%), and youth aged 20–29 years (43.3%). Over two-thirds of acute poisoning cases (69.0%) were admitted. Acute poisoning cases were more likely to be admitted if they were youth aged 10–19 years [odds ratio (OR) = 4.41], when the poisoning occurred at home (OR = 21.84), and was related to self-harm (OR = 18.73) or assault (OR = 7.56). Findings suggest that controlling access of poisonous substances in youth and at homes might reduce related ED care burden. Safety promotion agencies and emergency physicians can use these findings to develop safety messages.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.435

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.063
GPT teacher head0.443
Teacher spread0.381 · 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

Citations4
Published2015
Admission routes2
Has abstractyes

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