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Record W1868015383

Revisiting arthritis prevalence projections--it's more than just the aging of the population.

2006· article· en· W1868015383 on OpenAlexaffabout
Anthony V. Perruccio, J. Denise Power, Elizabeth M. Badley

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineDemographyPopulationPrevalenceEpidemiologyGerontologyArthritisEnvironmental healthInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: Data for successive population surveys show there is a sustained increase in the prevalence of arthritis, surpassing projected estimates. We examined whether the often-made assumption of stability in age/sex-specific arthritis point-prevalence estimates when estimating future burden is upheld; we used nearly a decade of survey data, and computed new projections for arthritis prevalence in Canada, taking into account past changes in age/sex-specific prevalence estimates and anticipated changes in the age/sex structure of the population. The prevalence from 1994 to 2003, overall and by age and sex, was documented. METHODS: Analyses were based on persons aged 15+ years from 3 cycles of the National Population Health Survey (1994-99; n > 14,000) and 2 cycles of the Canadian Community Health Survey (2000-03; n > 130,000). Two projection scenarios were adopted to estimate future burden. RESULTS: Stability in age/sex point-prevalence estimates was not observed. From 1994 to 2003, absolute and relative increases were greatest in the older age groups (55+ yrs) and younger age groups (25-54 yrs), respectively. By 2021, we anticipate the prevalence of arthritis in Canada will have increased to between 21% and 26%. Overall, the prevalence increased from 13.4% to 17.6% from 1994 to 2003, an increase of nearly 50% in the number of Canadians reporting arthritis. CONCLUSION: The assumption of stable age/sex prevalence estimates over time does not hold in Canada. Past projections have underestimated future burden; past trends need to be considered.

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)0.001
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 score0.270
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.022
GPT teacher head0.266
Teacher spread0.244 · 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

Citations104
Published2006
Admission routes2
Has abstractyes

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