Fatigue in Post‐poliomyelitis Syndrome: Association With Disease‐Related, Behavioral, and Psychosocial Factors
Bibliographic record
Abstract
OBJECTIVE: To determine the biopsychosocial correlates of general, physical, and mental fatigue in patients with postpoliomyelitis syndrome (PPS) by assessing the additional contribution of potentially modifiable factors after accounting for important nonmodifiable disease-related factors. It was hypothesized that disease-related, behavioral, and psychosocial factors would contribute in different ways to general, physical, and mental fatigue in PPS and that a portion of fatigue would be determined by potentially modifiable factors. DESIGN: Cross-sectional study. SETTING: A tertiary university-affiliated hospital post-polio clinic. PATIENTS: Fifty-two ambulatory patients with PPS who were not severely depressed were included. ASSESSMENT OF RISK FACTORS: Potential correlates for fatigue included disease-related factors (acute polio weakness, time since acute polio, PPS duration, muscle strength, pain, forced vital capacity, maximum inspiratory pressure, maximum expiratory pressure, body mass index, disability, fibromyalgia), behavioral factors (physical activity, sleep quality), and psychosocial factors (depression, stress, self-efficacy). MAIN OUTCOME MEASUREMENTS: Fatigue was assessed with the Multidimensional Fatigue Inventory (MFI; assesses fatigue on 5 subscales) and the Fatigue Severity Scale (FSS). RESULTS: Multivariate models were computed for MFI General, Physical, and Mental Fatigue. Age-adjusted multivariate models with nonmodifiable factors included the following predictors of (1) MFI General Fatigue: maximum inspiratory pressure, fibromyalgia, muscle strength; (2) MFI Physical Fatigue: maximum expiratory pressure, muscle strength, age, time since acute polio; and (3) MFI Mental Fatigue: none. The following potentially modifiable predictors made an additional contribution to the models: (1) MFI General Fatigue: stress, depression; (2) MFI Physical Fatigue: physical activity, pain; and (3) MFI Mental Fatigue: stress. CONCLUSIONS: PPS fatigue is multidimensional. Different types of fatigue are determined by different variables. Potentially modifiable factors account for a portion of fatigue in PPS.
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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".