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Record W1967710189 · doi:10.1002/art.24086

The cost of systemic sclerosis

2008· article· en· W1967710189 on OpenAlexaffabout
Sasha Bernatsky, Marie Hudson, Pantelis Panopalis, Ann E. Clarke, Janet Pope, Sharon LeClercq, Yvan St. Pierre, Murray Baron

Bibliographic record

VenueArthritis Care & Research · 2008
Typearticle
Languageen
FieldMedicine
TopicSystemic Sclerosis and Related Diseases
Canadian institutionsWestern UniversityMcGill UniversityUniversity of CalgaryMcGill University Health Centre
Fundersnot available
KeywordsMedicineIndirect costsConfidence intervalProductivityTotal costHealth careDemographyEnvironmental healthGerontologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess costs related to systemic sclerosis (SSc) and their determinants. METHODS: The Canadian Scleroderma Research Group is comprised of 15 centers contributing to a registry of adult patients with SSc. Available cross-sectional data included clinical variables and standardized measures of health resource use and time loss. Annualized averages of direct medical costs were calculated by multiplying health service utilization levels by the appropriate unit prices, determined from government fee schedules, professional associations, and other sources. Indirect costs were calculated from the subjects' self-reported time loss related to illness and to seeking health care, as well as caregiver time losses. Costs were represented in 2007 Canadian dollars. RESULTS: In the sample of 457 patients with SSc, the average direct cost per patient was $5,038 per year (95% confidence interval [95% CI] $4,400, $5,676). Regarding indirect costs, the value of potential productivity loss related to paid labor was estimated at an average of $5,345 per patient per year (95% CI $4,598, $6,092), and the cost of lost productivity related to unpaid labor contributed another $8,070 per patient annually. The average total annual cost was estimated at $18,453 (95% CI $16,598, $20,308) per patient. Total annual costs were strongly associated with younger age, greater disease severity, and poorer health status. CONCLUSION: Costs related to SSc are considerable, and there is a high impact of disease severity and health status on economic 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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.117
GPT teacher head0.349
Teacher spread0.232 · 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 designOther design
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

Citations73
Published2008
Admission routes2
Has abstractyes

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