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P157 Neurocognitive insights: functional magnetic resonance imaging of spatial working memory and sustained attention in people with systemic lupus erythematous

2024· article· en· W4395077504 on OpenAlexaff
Michelle Barraclough, Matt McCowen, Shane McKie, Alex Kafkas, Ben Parker, Juan Pablo Díaz-Martínez, Andrea Knight, Kathleen Bingham, Michael Li, Jiandong Su, Mahta Kakvan, Carolina Muñoz‐Grajales, Maria Carmela Tartaglia, Lesley Ruttan, Joan Wither, Dennisse Bonilla, Nicole D. Anderson, Daniela Montaldi, Rebecca Elliott, Patricia Katz, Dorcas Beaton, Robin Green, Ian N Bruce, Zahi Touma

Bibliographic record

VenueLara D. Veeken · 2024
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsToronto Rehabilitation InstituteUniversity Health NetworkUniversity of TorontoInstitute for Work & HealthToronto Western HospitalHospital for Sick Children
FundersSanofiGlaxoSmithKlineAstraZenecaEli Lilly and Company
KeywordsFunctional magnetic resonance imagingMedicineSystemic lupusNeurocognitiveMagnetic resonance imagingWorking memorySystemic lupus erythematosusNeuroscienceCognitionInternal medicinePsychiatryRadiologyPsychology

Abstract

fetched live from OpenAlex

Abstract Background/Aims Cognitive impairment (CI) is common in people with systemic lupus erythematosus (pwSLE). Treatment options are limited and the effects upon the brain is unclear. Differences in brain structure seen in SLE do not always associate with CI, however significant associations have been found with functional magnetic resonance imaging (fMRI). Using fMRI, this study aims to further explore potential compensatory brain mechanisms used in SLE that help with cognitive function. Methods Participants were recruited into one of two groups;pwSLE (meeting EULAR/ACR criteria) or healthy controls(HC). Demographic, clinical and psychiatric data and patient reported outcome measures were collected.Cognitive function was assessed using the ACR Neuropsychological Battery. Brain scans included two structural and two fMRI scans done during stage 1 and 2 of a cognitive task. Stage 1 of the task had an encoding, retention and working memory (WM) component. Stage 2 of the task examined long-term memory. Differences between task performances were examined using t-tests. The fMRI data was modelled using SPM12 to look for differences in blood-oxygen-level-dependent (BOLD) brain responses between the study groups during the different stages/components of the task. Results To-date 37 pwSLE and 10 HCs have been recruited. The median ages were 36 (HC) and 40 (pwSLE) years. From the pwSLE group the average disease duration was 15 years, the average SLEDAI-2K score was 5 and percentages of those on antimalarials, corticosteroids, and immunosuppressants and biologics were 66%, 32%, and 54%, respectively. There were no differences on task performance between the two groups. Greater BOLD responses were seen in the HC compared to the pwSLE group during stage 1 encoding and WM phases as well as during stage 2 (long-term memory). pwSLE had less attenuated BOLD signals during the stage 1 retention phase compared to HCs (Table 1). Conclusion We found altered brain responses to our cognitive task between pwSLE and HCs. Predominantly the HC group had greater BOLD responses in cognitive regions during the task compared to the pwSLE group. However, we did not find any difference between the two groups in regards to cognitive performance. This study is still ongoing and additional results are expected. Disclosure M. Barraclough: None. M. McCowen: None. S. McKie: None. A. Kafkas: None. B. Parker: None. J. Diaz-Martinez: None. A. Knight: None. K. Bingham: None. M. Li: None. J. Su: None. M. Kakvan: None. C. Munoz Grajales: None. M. Tartaglia: None. L. Ruttan: None. J. Wither: None. D. Bonilla: None. N. Anderson: None. D. Montaldi: None. R. Elliott: None. P. Katz: None. D. Beaton: None. R. Green: None. I. Bruce: None. Z. Touma: None.

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)0.001
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.243
Teacher spread0.231 · 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
Published2024
Admission routes1
Has abstractyes

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