Fatigue and Physical Activity in Adult Cerebral Palsy‐ Pilot Case Series Study
Bibliographic record
Abstract
D. Berbrayer, No Disclosures: I Have Nothing To Disclose. To determine prevalence of fatigue among adults with Cerebral Palsy (CP) and relationship physical activity levels This study examined the effect of a condition (fatigue) on outcomes (physical activity) in a select population of Adult (>18) CP University Setting- Tertiary Academic Hospital Adults with CP (>18 years) Exclusion: severe intellectual disabilities Demographic information collected included gender, age, education level, living situation and income source. Current and past mobility levels were assessed using the Gross Motor Function Classification System (GMFCS). Physical fatigue was assessed using two questionnaires- Fatigue Questionnaire and Fatigue Severity Scale (FSS). Physical Activity was assessed by Physical Activity Scale for Individuals with Physical Disabilities (PASIPD). The PASIPD described the respondents acitivites and all activities were either walking or wheeling. Physiotherapy exercises were done on own. Fatigue was assessed with 2 scales:Fatigue Questionnaire and Fatigue Severity Scale (FSS). 13 CP average age 35 years (21- 62 years). There were 7 males, 6 females. 50% completed high school and 50% completed college. 50% live with parents, while 42% live independently with a partner or alone. 67% rely on disability benefits, while 1/3 have paid work. 50% CP reported motor impairment in all four limbs. 85% had one other symptom with bowel or bladder being the most common. 8 CP classified as GMFCS 1-2 and 5 CP GMFCS 3-4. 5 Female and 2 Male had fatigue. Fatigue was present in 5 CP GMFCS 1-2 and 2 CP GMFCS 3-5. Linear regression analysis between fatigue severity (FSS) and physical activity levels (PASIPD) showed no correlation (p>.05). Ambulatory patients experience more fatigue. 63% with mild motor impairment (GMFCS Class 1-2) experiencing severe fatigue compared 40% with severe motor impairment (GMFCS Class 3-5).
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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 | 0.000 | 0.000 |
| 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".