Seasonality of fatigue in Parkinson’s disease in a high temperature location
Bibliographic record
Abstract
Background: Fatigue is one of the most common and disabling non-motor symptoms in Parkinson’s disease (PD), and its assessment is important to measure the quality of life of these patients. Simultaneously, rising temperatures due to global warming may aggravate conditions such as fatigue. The city of Teresina has a warming scenario that will only become a reality in some regions of the globe in the next decade, making it relevant to analyze the influence of temperature on neurological diseases in this city. Objective: To assess the severity of fatigue and quality of life in patients with Idiopathic Parkinson’s Disease (IPD) according to seasonal variations in a high temperature location. Methods: This is a longitudinal observational study. It included patients with IPD according to the UK Parkinson’s Disease Society Brain Bank and Movement Disorders Society criteria, followed at a movement disorder center in Teresina-PI. Assessments took place in the high temperature period (September to December) and the mild temperature period (January to April), using the Unified Parkinson’s Disease Rating Scale (UPDRS), Montreal Cognitive Assessment (MoCA), Parkinson’s Disease Questionnaire-39 (PDQ-39), and Fatigue Severity Scale (FSS). The R software (R Core Team) was used for statistical data analysis. The normality assumption of the data was verified by the Shapiro-Wilk test. The Wilcoxon test was used to compare the UPDRS scale values in the high and mild temperature periods. The paired t-test was used to compare the levodopa equivalent dose (LED) values and the FSS and PDQ-39 scales in the high temperature period (HTP) and mild temperature period (MTP). The criterion for a statistically significant difference was p-value <0.05. Results: A sample of 16 patients with a mean age of 65 years, 75% male, with a mean duration of symptoms of 9.06 years and a mean diagnosis time of 8.12 years, the mean MoCA score was 18.81. The mean UPDRS was 33.18 in HTP and 31.64 in MTP (p=0.9645). The average LED in HTP was 617.31, and in MTP was 667.37 (p=0.1730). The average FSS in HTP was 4.56, while in MTP was 4.53 (p=0.9227). The average PDQ-39 was 46.33 in HTP and 45.36 in MTP (p=0.6906). There were no statistically significant differences between the high and mild temperature periods. Conclusion: The severity of fatigue and quality of life in patients with Idiopathic PD did not differ between seasons in a high temperature location. The restricted sample became the current findings limited.
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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 | 0.000 | 0.001 |
| 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".