PO.1.14 Evaluation of cognitive impairment in SLE – a comparison of two assessment tools
Bibliographic record
Abstract
Background, aims Cognitive impairment is estimated to occur in 10–30% of systemic lupus erythematosus (SLE) patients. Its screening and early recognition is not well established in routine clinical care. Assessment tools for common types of dementia are insufficient to detect early signs of cognitive dysfunction, furthermore, few tests have been studied specifically in SLE patients to screen and follow cognitive functions. The aim of this study was to evaluate the efficacy of Quick mild cognitive impairment screen (Qmci) and the Montreal Cognitive Assessment (MoCA) to find a brief screening tool for the everyday practice. Furthermore, our aim was to analyse which cognitive functions are mostly affected in SLE patients compared to healthy controls to detect mild cognitive impairment early, before it progresses to dementia. Methods We enrolled consecutive SLE patients aged < 65 years who met the Systemic Lupus International Collaborating Clinics (SLICC) 2012 classification criteria. Disease activity was measured by SLEDAI-2K. We evaluated the patients’ cognitive function with the MoCA and Qmci tests. We recorded the patients’ demographic, clinical, immunoserological parameters and data about education, social and health habits. We also used this study to validate the Hungarian translation of the Qmci test in SLE patients. Results Eighty-seven patients (mean age: 44.97/range: 20–64/), of whom 75 were women (86.2%) and 12 were men (13.8%) were studied. 32 patients (36.8%) had < 12 years of education, 32 patients had grammar school or college educational level (36.8%) and 23 had university degree. Regarding MoCA, the participants’ test score was in the range between 17 and 30 points (maximum score in the MoCA test is 30), with mean score of 26.28 (SD = 3.08), which is considered as normal cognition with the 24 cut-off score of the MoCa test. Patients scored a mean of 3.64 point (SD = 1.32) from the maximal 5 points on the delayed recall scale. The Qmci scores were in the range between 49 and 94 points (mean: 80.68/SD = 10.10/), which is classified as normal cognition using the 62 cut-off score (potential maximum for Qmci is 100). Highest deviations from the maximum were observed in the delayed recall domain (13,79, SD = 5.58) and the verbal fluency task (mean 11.78, SD = 2.96 out of the maximal 20 points). With MoCA we detected 16 patients (18,4%) with cognitive impairment, whereas Qmci classified 4 participants (4,6%) with this. Conclusions Cognitive impairment is present in a considerable proportion of SLE patients under 65 years of age, but the rate is dependent on the tool used. MoCA was a more sensitive test in this cohort, it therefore seems more useful for screening. Although Qmci has a less stringent numerical range to detect mild cognitive impairment, furthermore, it is a quick instrument, it classified less patients with cognitive impairment in our cohort. Analysis of subsets of cognitive function in the tests could help to better delineate the character of cognitive impairment developing in SLE. Further research is required in larger clinical and healthy sample to examine the diagnostic and follow-up value of the tests.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".