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Record W3047077524 · doi:10.1002/art.41404

Prevalence, Incidence, and Years Lived With Disability Due to Gout and Its Attributable Risk Factors for 195 Countries and Territories 1990–2017: A Systematic Analysis of the Global Burden of Disease Study 2017

2020· article· en· W3047077524 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueArthritis & Rheumatology · 2020
Typearticle
Languageen
FieldMedicine
TopicGout, Hyperuricemia, Uric Acid
Canadian institutionsMcGill University
FundersShahid Beheshti University of Medical Sciences
KeywordsMedicineIncidence (geometry)Burden of diseaseDiseaseEnvironmental healthGoutDisease burdenDemographyGerontologyPopulationInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the levels and trends of point prevalence, annual incidence, and years lived with disability (YLD) for gout and its attributable risk factors in 195 countries and territories from 1990 to 2017 according to age, sex, and Sociodemographic Index (SDI; a composite of sociodemographic factors). METHODS: Data were extracted from the Global Burden of Disease (GBD) 2017 study. A comprehensive systematic review of databases and the disease-modeled analysis were performed by the GBD team at the Institute for Health Metrics and Evaluation, in collaboration with researchers and experts worldwide, to provide estimates at global, regional, and national levels during 1990 and 2017. Counts and age-standardized rates per 100,000 population, along with 95% uncertainty intervals (95% UIs), were reported for point prevalence, annual incidence, and YLD. RESULTS: Globally, there were ~41.2 million (95% UI 36.7 million, 46.1 million) prevalent cases of gout, with 7.4 million incident cases per year (95% UI 6.6 million, 8.5 million) and almost 1.3 million YLD (95% UI 0.87 million, 1.8 million) in 2017. The global age-standardized point prevalence estimates and annual incidence rates in 2017 were 510.6 (95% UI 455.6, 570.3) and 91.8 (95% UI 81.3, 104.1) cases per 100,000 population, respectively, an increase of 7.2% (95% UI 6.4%, 8.1%) and 5.5% (95% UI 4.8%, 6.3%) from 1990. The corresponding age-standardized YLD rate was 15.9 (95% UI 10.7, 21.8) cases per 100,000 persons, a 7.2% increase (95% UI 5.9%, 8.6%) from 1990. In 2017, the global point prevalence estimates for gout were higher in males, and higher prevalence was seen in older age groups and increased with age for both males and females. The burden of gout was generally highest in developed regions and countries. The 3 countries with the highest age-standardized point prevalence estimates of gout in 2017 were New Zealand (1,394.0 cases [95% UI 1,290.1, 1,500.9]), Australia (1,171.4 cases [95% UI 1,038.1, 1,322.9]), and the US (996.0 cases [95% UI 923.1, 1,076.8]). The countries with the highest increases in age-standardized point prevalence estimates of gout from 1990 to 2017 were the US (34.7% [95% UI 27.7%, 43.1%]), Canada (28.5% [95% UI 21.9%, 35.4%]), and Oman (28.0% [95% UI 21.5%, 34.8%]). Globally, high body mass index and impaired kidney function accounted for 32.4% (95% UI 18.7%, 49.2%) and 15.3% (95% UI 13.5%, 17.1%), respectively, of YLD due to gout in the 2017 estimates. The YLD attributable to these risk factors were higher in males. CONCLUSION: The burden of gout increased across the world from 1990 to 2017, with variations in point prevalence, annual incidence, and YLD between countries and territories. Besides improving the clinical management of disease, prevention and health promotion in communities to provide basic knowledge of the disease, risk factors, consequences, and effective treatment options (tailoring to high-risk groups such as the middle-aged male population) are crucial to avoid disease onset and hence to decrease the global disease burden.

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.

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)0.002
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 score0.009
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.014
GPT teacher head0.264
Teacher spread0.250 · 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