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Record W2035331892 · doi:10.1081/jas-100000037

Predicting Emergency Department Utilization in Adults with Asthma: A Cohort Study

2001· article· en· W2035331892 on OpenAlexaff
Margot Underwood, Shirley G. Revitt, Stephen K. Field

Bibliographic record

VenueJournal of Asthma · 2001
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAsthmaMedicineEmergency departmentCohortProspective cohort studyCohort studyAsthma managementEmergency medicinePhysical therapyPediatricsInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

A consecutive sample of 378 adults with asthma were assessed at a university asthma program and then interviewed 1 year later regarding their need for emergency department (E.D.) asthma treatment. The purpose of this prospective cohort study was to determine whether any of their initial features could predict their subsequent need for E.D. asthma treatment. At one year, a total of 73 of the subjects had attended emergency departments for asthma. On entry, the 73 subjects had demonstrated more self-reported lifestyle restriction from asthma and more hospital admissions E.D. visits for asthma as well as poorer asthma control or than had the 305 subjects who had not required E.D. asthma treatment since entry to the cohort. This study suggests that special attention should be paid to subjects with asthma that interferes with their lifestyle and to those who have needed hospital admission for asthma.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.017
GPT teacher head0.295
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), 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

Citations48
Published2001
Admission routes1
Has abstractyes

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