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Record W2151193988 · doi:10.3899/jrheum.101054

Thrombovascular Events Affect Quality of Life in Patients with Systemic Lupus Erythematosus

2011· article· en· W2151193988 on OpenAlexafffundvenue
Amaris Balitsky, Valentina Peeva, Jiandong Su, Elaheh Aghdassi, Eric Yeo, Dafna D. Gladman, Murray B. Urowitz, Paul R. Fortin

Bibliographic record

VenueThe Journal of Rheumatology · 2011
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoArthritis SocietyLupus CanadaHospital for Special Surgery
KeywordsMedicineAffect (linguistics)Systemic diseaseQuality of life (healthcare)Connective tissue diseaseLupus erythematosusDermatologyIntensive care medicineSystemic lupus erythematosusImmunopathologyImmunologyInternal medicineAutoimmune diseaseDiseaseAntibody

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare health-related quality of life (HRQOL) of patients with antiphospholipid syndrome (APS) and systemic lupus erythematosus (SLE) with and without previous thrombovascular events (TE). METHODS: The Medical Outcomes Study Short-Form 36 (SF-36) was used to assess HRQOL in 5 patient groups: (1) primary APS (PAPS; n = 35); (2) APS associated to SLE (SAPS; n = 37); (3) SLE+TE without persistent positive antiphospholipid antibody (SLE+TE-aPL; n = 75); (4) SLE-TE+aPL (n = 71); and (5) SLE-TE-aPL (n = 608). RESULTS: The data on both mental component summary and physical component summary (PCS) scores showed an impaired quality of life in all patient groups. Patients in the SLE+TE-aPL group had a lower PCS score compared to patients in the SLE-TE+aPL group. CONCLUSION: The combination of SLE and TE has a more negative influence on reported HRQOL, compared to having SLE or APS alone.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.293
Teacher spread0.257 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2011
Admission routes3
Has abstractyes

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