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Living with osteoarthritis: patient expenditures, health status, and social impact

2001· article· en· W2078314652 on OpenAlexaboutno aff
Helen Lapsley, Lyn March, Kate Tribe, Marita Cross, Peter Brooks

Bibliographic record

VenueArthritis & Rheumatism · 2001
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsnot available
FundersNational Health and Medical Research Council
KeywordsMedicineWOMACOsteoarthritisPhysical therapyCohortProspective cohort studyDiseaseGerontologyHealth careCohort studySocial supportAlternative medicineInternal medicinePsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine "out-of-pocket" expenditures related to osteoarthritis (OA) and to explore whether demographic details, health status scores (Medical Outcomes Study 36-item Short Form [SF-36] and Western Ontario and McMaster Universities Osteoarthritis Index [WOMAC]), or perception of social effect were expenditure determinants. METHODS: A prospective cohort study of community-dwelling subjects with OA completed 4 consecutive 3-month cost diaries. In addition, subjects completed the SF-36 and WOMAC at baseline and at 12 months. Social impact at baseline was collected. Four groups categorized by age and sex were compared. Patients undergoing joint replacement were excluded. RESULTS: Differences in health status were defined more by age than by sex, especially for physical function. The costs to the patients were high, particularly for women, who spent more on medications and special equipment. Women also reported receiving more assistance from family and friends. Higher disease-related expenditures were associated with greater pain levels, poorer social function and mental health, and longer duration of disease. Significant independent predictors of total patient expenditures related to OA were being female and having joint stiffness. CONCLUSION: Despite having heavily subsidized health care and access to the Pharmaceutical Benefits Scheme, out-of-pocket costs for patients with OA in Australia are considerable. Higher expenditures for patients with OA are related to more advanced disease, especially for women.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.262
Teacher spread0.252 · 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.

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

Citations75
Published2001
Admission routes1
Has abstractyes

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