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Record W2052945182 · doi:10.1186/ar4660

Significance of cerebrovascular reactivity in patients with systemic lupus erythematosus

2014· article· en· W2052945182 on OpenAlexfundno aff
Jason Lazar, Louis Salciciolli, Elina Malamed, Ellen M. Ginzler

Bibliographic record

VenueArthritis Research & Therapy · 2014
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health ResearchNational Institutes of HealthLupus Research AllianceCanadian Arthritis NetworkNational Institute of Arthritis and Musculoskeletal and Skin DiseasesArthritis SocietyCentral New York Community FoundationMerck KGaALupus Foundation of America
KeywordsRheumatologyMedicineInternal medicineSystemic lupusCardiologyDisease

Abstract

fetched live from OpenAlex

There is growing recognition and concern regarding cognitive dysfunction in patients with systemic lupus erythematosus (SLE). SLE patients have accelerated atherosclerosis, which is known to contribute to cognitive dysfunction in other disease states. Impaired cerebrovascular reactivity (CVR) is a vascular measure linked to cognitive dysfunction, but this has not been well studied in the setting of SLE. The objectives of this study are to determine whether CVR is impaired in patients with SLE and to determine the significance of CVR impairment. Right middle cerebral artery CVR was assessed by the breath holding index (BHI), which combines transcranial Doppler recording and passive breath holding. This technique evaluates changes in middle cerebral artery Doppler velocities upon permissive hypercapnea. We measured the BHI in nine female patients with SLE (age 38 ± 13 years) and 12 age-matched controls. Cognitive function was assessed using the color Stroop block time test (SBT) and the Stroop black/white test (SBWT). The augmentation index, a measure of arterial wave reflection, was assessed by applanation tonometry of the radial artery. Carotid intimal media thickness measurements were obtained with high-resolution ultrasound. Completion times for the SBT (38.4 ± 8.7 vs. 29.5 ± 6.6) and the SBWT (29.7 ± 5.4 vs. 22.9 ± 5.8) were significantly higher in SLE patients versus controls ( P = 0.005 and P = 0.004 respectively). On CVR testing, right middle cerebral artery BHI responses were significantly different between SLE and NLS (0.91 ± 1.10 vs. -0.99 ± 1.7, P = 0.001). There was a trend towards higher CIMT (0.634 ± 0.130 cm vs. 0.549 ± 0.116 cm, P = 0.10) and towards higher AI (27 ± 16% vs. 18 ± 9%, P = 0.10) in the SLE group. CVR was significantly correlated with AI (0.68, P = 0.003), and a trend with SBT ( r = 0.42, P = 0.07) and CIMT ( r = 0.45, P = 0.08). On multivariate analysis (with age and SLE), SLE was a significant predictor of BHI ( B = 1.84, P = 0.033). SLE is associated with impaired CVR. Impaired CVR appears related to higher wave reflection as measured by the AI. This ongoing study will help define the relations between CVR and other vascular parameters as well as potential relations with cognitive dysfunction in SLE patients.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.300
Teacher spread0.274 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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