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Record W2520345115 · doi:10.1136/lupus-2016-000179.115

CE-36 Clinical measures and indices of disease activity and damage as predictors of morbidity and mortality in systemic lupus erythematosus (SLE): a systematic review of the literature

2016· review· en· W2520345115 on OpenAlexaffabout
Stephanie Keeling, Jorge E. Chaparro Medina, Tatiana Nevskaya, Janet Pope, Zainab Alabdurubalnabi, Asvina Bissonauth, Zahi Touma

Bibliographic record

Venuenot available
Typereview
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsUniversity of British ColumbiaWestern UniversityUniversity of TorontoUniversity of Alberta
Fundersnot available
KeywordsMedicineObservational studyDiseaseSystematic reviewSystemic lupus erythematosusInternal medicineGrading (engineering)MEDLINEPhysical therapy

Abstract

fetched live from OpenAlex

Background Despite validated clinical measures and indices of disease activity and damage, utilisation of these indices in clinical practice varies, as evidenced by a recent practice pattern survey of Canadian rheumatologists. In this review, we aimed to identify the impact of disease activity and damage on outcomes of mortality and damage to inform upcoming Canadian SLE recommendations utilising the GRADE (Grading of Recommendations Assessment, Development and Evaluation) method. Materials and methods Following GRADE methodology to fill in evidence-to-decision tables to create recommendations for “minimal investigations needed to monitor SLE patients at baseline and subsequent visits”, a systematic review of the literature including all relevant articles from 1946 to November 2014 was performed searching Medline and Embase. The impact of disease activity and damage measured by commonly utilised indices of disease activity [eg SLEDAI-2K (SLE Disease Activity Index-2000), BILAG (British Isles Lupus Assessment Group), SLAM (SLE Activity Measure), ECLAM (European Consensus Lupus Activity Measurement)], Mexican SLEDAI, and damage [SDI [SLICC/ACR (Systemic Lupus International Collaborating Clinics/ACR Damage Index)] on mortality, damage, and disease flares was evaluated with meta- analyses performed when available. Study quality was assessed by the Newcastle Ottawa scale for observational studies. Results A title screen of 2797 articles identified 771 papers for full paper review, 106 meeting inclusion criteria and 88 with extractable data. Fifty-five articles describing outcomes with disease activity indices (including BILAG, ECLAM, Mexican SLEDAI, SLEDAI-2K/SELENA-SLEDAI and SLAM) and twenty-four articles describing outcomes with damage based on SDI were identified. Mortality was associated with higher SLEDAI-2K in 6 observational studies [HR 1.14 (95% CI: 1.06,1.22)] and in 5 observational studies with higher SDI scores at baseline and/or immediately prior to death [HR 1.53 (95% CI: 1.28, 1.83)]. Higher SLAM scores were associated with increased risk of damage (SDI > 0) in 3 observational studies [OR 1.06 (95% CI:?1.04, 1.08]. Mean total BILAG was associated with mortality in one observational study with HR of 1.15. Conclusions Active lupus disease activity and presence of damage as represented by multiple clinical indices are associated with greater mortality and morbidity in lupus patients. Given the complexity of clinical assessments in SLE patients, the utilisation of validated measures for disease activity and damage is important and will serve to inform upcoming Canadian recommendations for the diagnosis and monitoring of SLE. Acknowledgements This systematic literature review is being used by the Canadian SLE Working Group to inform future recommendations for the diagnosis and monitoring of SLE.

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)0.012
metaresearch head score (Gemma)0.042
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.015
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.042
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.012
Bibliometrics0.0150.016
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.056
GPT teacher head0.390
Teacher spread0.334 · 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 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".

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Citations0
Published2016
Admission routes2
Has abstractyes

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