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Record W2151986880 · doi:10.1093/rheumatology/kem373

SLE patients with renal damage incur higher health care costs

2007· article· en· W2151986880 on OpenAlexaffabout
AE Clarke, Peter Panopalis, Michelle Petri, S Manzi, David Isenberg, Caroline Gordon, Jean‐Luc Senécal, L. Joseph, Y. St. Pierre, Tianjing Li

Bibliographic record

VenueLara D. Veeken · 2007
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesNational Center for Research ResourcesU.S. Public Health ServiceWellcome TrustUniversity of Pittsburgh
KeywordsMedicineQuality of life (healthcare)Intensive care medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

OBJECTIVES: To compare costs and quality of life (QoL) between SLE patients with and without renal damage. METHODS: Seven hundred and fifteen patients were surveyed semi-annually over 4 yrs on health care use and productivity loss and annually on QoL. Cumulative direct and indirect costs (2006 Canadian dollars) and QoL (average annual change in SF-36) were compared between patients with and without renal damage [Systemic Lupus International Collaborating Clinics/ACR Damage Index (SLICC/ACR DI)] using simultaneous regressions. RESULTS: At study conclusion, for patients with the renal subscale of the SLICC/ACR DI = 0 (n = 634), 1 (n = 54), 2 (n = 15) and 3 (n = 12), mean 4-yr cumulative direct costs per patient (95% CI) were $20,337 ($18,815, $21,858), $27,869 ($19,230, $36,509), $51,191 ($23,463, $78,919) and $99,544 ($57,102, $141,987), respectively. In a regression where the renal subscale of the SLICC/ACR DI was a single indicator variable, on average (95% CI), each unit increase in renal damage was associated with a 24% (15%, 33%) increase in direct costs. In a regression where each level in the renal subscale was an indicator variable, patients with end-stage renal disease incurred 103% (65%, 141%) higher direct costs than those without renal damage. Cumulative indirect costs and annual change in the SF-36 summary scores did not differ between patients. CONCLUSIONS: SLE patients with renal damage incurred higher direct costs, but did not experience a poorer QoL. QoL may be more influenced by concurrent renal activity than accumulated renal damage, which can occur at any time and patients may gradually habituate to their compromised health state.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.308
Teacher spread0.292 · 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

Citations86
Published2007
Admission routes2
Has abstractyes

Explore more

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