Pain, depression, and quality of life in adults with MOG‐antibody–associated disease
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Myelin oligodendrocyte glycoprotein-antibody-associated disease (MOGAD) is an inflammatory autoimmune condition of the central nervous system. However, data on pain and depression have remained scarce. The aim of this study was to assess features of chronic pain and depression as well as their impact on health-related quality of life (hr-QoL) in MOGAD. METHODS: Patients with MOGAD were identified in the Neuromyelitis Optica Study Group registry. Data were acquired by a questionnaire, including clinical, demographic, pain (PainDetect, Brief Pain Inventory-Short Form, McGill Pain Questionnaire-Short Form), depression (Beck Depression Inventory-II), and hr-QoL (Short Form-36 Health Survey) items. RESULTS: Twenty-two of 43 patients suffered from MOGAD-related pain (11 nociceptive, eight definite neuropathic, three possible neuropathic) and 18 from depression. Patients with neuropathic pain had the highest pain intensity and most profound activities of daily living (ADL) impairment. Fifteen patients reported spasticity-associated pain, including four with short-lasting painful tonic spasms. Later disease onset, profound physical impairment, and depression were associated with chronic pain. Physical QoL was more affected in pain sufferers (p < 0.001) than in pain-free patients, being most severely reduced by neuropathic pain (p = 0.016). Pain severity, visual impairment, and gait impairment independently predicted lower physical QoL. Depression was the only factor reducing mental QoL. Twelve patients still suffering from moderate pain (pain severity 4.6 ± 2.3) received pain medication. Only four out of 10 patients with moderate to severe depression took antidepressants. CONCLUSIONS: Being highly prevalent, pain and depression strongly affect QoL and ADL in MOGAD. Both conditions remain insufficiently controlled in real-life clinical practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".