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Record W4206006306 · doi:10.1136/lupus-2021-000574

Herpes zoster in SLE: prevalence, incidence and risk factors

2022· article· en· W4206006306 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLupus Science & Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsUniversity Health NetworkWestern UniversityUniversity of Toronto
FundersDepartment of Medicine, University of TorontoUniversity of TorontoArthritis SocietyCanadian Rheumatology Association
KeywordsMedicineIncidence (geometry)Internal medicineDiseaseProportional hazards modelImmunology

Abstract

fetched live from OpenAlex

OBJECTIVES: This study aimed to evaluate the prevalence and incidence of herpes zoster (HZ) events and describe its associated factors in a study of patients with SLE. METHODS: 491 consecutive SLE participants were screened for HZ events using a patient-reported questionnaire to capture outcomes on pain and other characteristics associated with HZ events. Sociodemographic, clinical and laboratory measures were also analysed, and time-dependent Cox regression survival analyses were performed to investigate factors associated with HZ events. RESULTS: Prevalence of HZ was 30.5%, incidence was 14.3 cases per 1000 person-years. Lymphopenia and glucocorticoid dosing were significantly associated with HZ events. CONCLUSIONS: HZ is highly prevalent in SLE, which may be linked to disease-related and treatment-related effects on cellular immunity. Our results suggest that the presence of certain risk factors may be useful to allow identification of patients at risk of HZ and improve its management in patients with 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.

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)0.000
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 score0.050
Threshold uncertainty score0.814

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.016
GPT teacher head0.297
Teacher spread0.281 · 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