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Record W2412212310 · doi:10.3899/jrheum.151432

Trends in Emergency Department Visits and Charges for Gout in the United States between 2006 and 2012

2016· article· en· W2412212310 on OpenAlexvenueno aff
Sadao Jinno, Kohei Hasegawa, Tuhina Neogi, Tadahiro Goto, Maureen Dubreuil

Bibliographic record

VenueThe Journal of Rheumatology · 2016
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsMedicineEmergency departmentGoutEmergency medicineInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine temporal trends in the rate of gout emergency department (ED) visits and charges in the United States between 2006 and 2012. METHODS: A serial cross-sectional analysis of the Nationwide Emergency Department Sample. RESULTS: The rate of ED visits for gout in adults overall increased from 75.0 to 85.4 per 100,000 persons over the study period (14% increase, p < 0.001), and increased 29% for those aged 45-54 years. Nationwide ED charges increased from $156 million to $281 million (80% increase, p < 0.001). CONCLUSION: Between 2006 and 2012, the rate of gout ED visits increased among US adults, most notably in those aged 45-54 years.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.021
GPT teacher head0.297
Teacher spread0.276 · 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

Citations26
Published2016
Admission routes1
Has abstractyes

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