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Record W2615497066 · doi:10.1097/bor.0000000000000416

Socioeconomic consequences of systemic lupus erythematosus

2017· review· en· W2615497066 on OpenAlexafffund
Megan R.W. Barber, Ann E. Clarke

Bibliographic record

VenueCurrent Opinion in Rheumatology · 2017
Typereview
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of Calgary
FundersNational Institute on Minority Health and Health DisparitiesArthritis Society
KeywordsMedicineSocioeconomic statusDisadvantagedIndirect costsPovertyQuality of life (healthcare)PopulationDiseaseEnvironmental healthGerontologyImmunologyEconomic growthInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The present review addresses recent literature investigating the socioeconomic consequences of systemic lupus erythematosus (SLE). We highlight the latest updates on health disparities affecting the SLE population, the direct and indirect economic costs of the disease, and less quantifiable costs such as reduced health-related quality of life (HRQoL). RECENT FINDINGS: Health disparities continue to exist among socially disadvantaged populations, including African Americans, Hispanics, and patients with decreased educational attainment and in poverty. Direct and indirect costs are substantial. Recent work provides updated cost estimates for patients with SLE outside of North America, including those in developing countries. Previous research has largely focused on costs of the general SLE population and those with renal manifestations or active SLE, whereas recent research addresses special populations such as hospitalized and pregnant patients and glucocorticoid users. Patients with SLE and their caregivers experience a substantially reduced HRQoL. SUMMARY: SLE is a costly disease that disproportionately affects disadvantaged populations. Future economic studies should measure not only direct costs, but also incorporate indirect costs and the HRQoL of both patients with SLE and their caregivers. All these components are essential to provide a comprehensive assessment of the socioeconomic consequences of SLE and an appreciation of the potential impact of novel therapies.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.186
GPT teacher head0.450
Teacher spread0.264 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations42
Published2017
Admission routes2
Has abstractyes

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