P159 Development of digital neuropsychological battery: a use case in Indian SLE patients
Bibliographic record
Abstract
Abstract Background/Aims While cognitive dysfunction and mood disorders are frequently reported as adverse effects of SLE, there is a scarcity of neuropsychological (NP) data for Asian SLE patients. Existing English-centric NP tests are inadequate for the linguistic and culturally diverse population. This study examines SLE's effects on mood and cognitive functions using an indigenously developed language-neutral digital NP test battery and validated anxiety, stress, depression and quality of life instruments. Methods We recruited SLE patients fulfilling 2012 SLE classification criteria as cases and caregivers (CG) and college students (CS) as controls aged above 18 years and at least 10th standard education. All participants provided written informed consent. Institutional ethics committees approved the study. The NP battery comprised five cognitive tasks: Montreal Cognitive Assessment (MoCA) and modified versions of attention network test (ANT), sustained attention to response task (SART), picture naming and N-back, and five psychological tests (PHQ-9, GAD-7, STAI-T, PSS-4 and WHOQOL-BREF). Mann-Whitney test with conditional Bonferroni's corrections was used to compare cases with CG and CS. Results Total of 142 volunteers (age: median = 25.0, IQR = 9.0, cases [n = 82], CG [n = 40] and CS [n = 20]) participated in the study. Cases exhibited delayed response latencies in N-back, SART, and picture naming tasks compared to controls. They demonstrated reduced accuracy in all N-back conditions, with significant differences observed in hit rate, miss rate, false alarms, and d-prime scores compared to CS with effect size ranging from 0.298 to 0.736 (Table 1). However, the difference was only significant in the 2-back condition compared to CG. Cases displayed lower accuracy in SART Go trials (higher omission errors) than controls but better inhibition in SART No-Go trials (lower commission errors). No differences were observed in alerting, orienting and executive control functions. Cases showed significantly lower scores in MOCA than controls. Cases reported poorer psychological health through increased anxiety and stress levels and reduced WHO-quality of life scores compared to CG. Conclusion Contrary to earlier research that often relied on isolated cognitive assessments, our pioneering approach introduces a tailored test battery to establish cognitive baselines for Indian SLE patients. Disclosure P. Singhal: None. P. Srivastava: None. L. Rajasekhar: None. N. Samhitha: None.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".