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Evaluation of Drug-related Emergency Department Admissions in a Tertiary Care Hospital

2020· article· en· W3046631227 on OpenAlexaboutno aff
Nusrat Shafiq, Cvn Harish, Samir Malhotra

Bibliographic record

VenueJournal of Postgraduate Medicine Education and Research · 2020
Typearticle
Languageen
FieldMedicine
TopicPharmaceutical Practices and Patient Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsEmergency departmentMedicineTertiary careMedical emergencyEmergency medicineDrugNursingPharmacology

Abstract

fetched live from OpenAlex

To estimate the incidence, severity, preventability, and cost of medication-related problems. To classify patients admitted with medicationrelated illnesses based on causative factors. Study design: Single-center, cross-sectional, observational study. Materials and methods: Patient details were collected within 24 hours of admission into emergency. The causality assessment for adverse drug reaction (ADR) was assessed using the Naranjo scale. The modified Canadian emergency department triage and the acuity scale was used for assessment of severity of the ADR and the likely outcome. Results: We screened approximately 6,050 admissions; of them, 180 (2.97%) were related to medication-related problems. About 59 (32.8%) were classified as definitely preventable, 92 (51.1%) possibly preventable, and remaining 29 (16.1%) were not preventable. A total of 103 (57.2%) were categorized as severe, 76 (42.2%) as moderate, and 1 as mild. Average number of drugs received prior to admission was 1.29 (1.15), which increased to 6.93 (2.34) at the time of analysis. The median (range) cost of medications was $11.70 ($0.32-253.6) per patient per day.

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)0.003
metaresearch head score (Gemma)0.005
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 score0.146
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
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 integrity0.0000.001
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 head0.217
GPT teacher head0.536
Teacher spread0.319 · 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".

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Citations1
Published2020
Admission routes1
Has abstractyes

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