Quality of Life, Cognition and Mood in Adults with Pediatric Multiple Sclerosis
Bibliographic record
Abstract
BACKGROUND: Pediatric onset multiple sclerosis (MS) negatively affects cognitive function, mood and health related quality of life (HRQOL). We aimed to explore the cognitive, psychological and HRQOL impacts of pediatric MS on young adults and to explore the relationships between disability, disease duration, cognition, mood and HRQOL in this hypotheses generating study. METHODS: Thirty-four young adults with pediatric onset MS at St. Michael's Hospital in Toronto were included in this cross-sectional study (mean age 21.3 years, 56% female). Participants completed assessments of physical disability (Expanded Disability Status Scale (EDSS)), cognitive function (Symbol Digit Modalities Test (SDMT)), mood (Beck Depression Inventory II (BDI-II)), and HRQOL (Short Form Health Survey (SF-36v2)). Findings were compared to age- and gender- matched normative data. RESULTS: Individuals with pediatric MS performed worse on the SDMT compared to normative data, with 53% demonstrating cognitive impairment. There was no difference in BDI-II scores from normative data, but 21% showed at least mild depression. There was a non-significant impairment in physical HRQOL compared to normative data. Decreased physical HRQOL was related to disability (EDSS), while mental HRQOL was related to depression (BDI-II). CONCLUSIONS: Young adults with pediatric MS have reduced cognitive function. Non-significant reductions in HRQOL may be partly attributed to physical disability and depression. These factors should be addressed in the care of adults with pediatric MS. Further studies including control groups and longitudinal design are needed to confirm these findings.
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 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".