Cognitive impairment in the immune-mediated inflammatory diseases compared with age-matched controls: Systematic review and meta-regression
Bibliographic record
Abstract
OBJECTIVES: To compare the magnitude of cognitive impairment against age-expected levels across the immune mediated inflammatory diseases (IMIDs: systemic lupus erythematosus [SLE], rheumatoid arthritis [RA], axial spondyloarthritis [axSpA], psoriatic arthritis [PsA], psoriasis [PsO]). METHODS: A pre-defined search strategy was implemented in Medline, Embase and Psychinfo on 29/05/2021. Inclusion criteria were: (i) observational studies of an IMID, (ii) healthy control comparison, (iii) measuring cognitive ability (overall, memory, complex attention/executive function, language/verbal fluency), and (iv) sufficient data for meta-analysis. Standardised mean differences (SMD) in cognitive assessments between IMIDs and controls were pooled using random-effects meta-analysis. IMIDs were compared using meta-regression. RESULTS: In total, 65 IMID groups were included (SLE: 39, RA: 19, axSpA: 1, PsA: 2 PsO: 4), comprising 3141 people with IMIDs and 9333 controls. People with IMIDs had impairments in overall cognition (SMD: -0.57 [95% CI -0.70, -0.43]), complex attention/executive function (SMD -0.57 [95% CI -0.69, -0.44]), memory (SMD -0.55 [95% CI -0.68, -0.43]) and language/verbal fluency (SMD -0.51 [95% CI -0.68, -0.34]). People with RA and people with SLE had similar magnitudes of cognitive impairment in relation to age-expected levels. People with neuropsychiatric SLE had larger impairment in overall cognition compared with RA. CONCLUSIONS: People with IMIDs have moderate impairments across a range of cognitive domains. People with RA and SLE have similar magnitudes of impairment against their respective age-expected levels, calling for greater recognition of cognitive impairment in both conditions. To further understand cognition in the IMIDs, more large-scale, longitudinal studies are needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.034 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.039 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".