The impact of different lifestyle factors on disability in multiple sclerosis at older ages: a monocentric retrospective study
Bibliographic record
Abstract
Background: Multiple sclerosis (MS) is a chronic immune-mediated disease of the central nervous system affecting approximately 2.8 million people worldwide. In addition to genetic and environmental factors, various lifestyle factors contribute to disease development and progression. Objectives: We performed a monocentric retrospective study and investigated the effect of lifestyle factors such as obesity, smoking, alcohol consumption, physical activity, and dietary habits on the degree of disability in a cohort of people with MS (pwMS) with an average onset of disease after the age of 55. Design: This late-onset MS (LOMS) study group ( n = 47) was characterized by a mean age of 60.9 years and a mean duration of disease of 5.0 years. The LOMS study group was compared with two control groups. The study participants in the “old control group” (Cold) were on average as old and in the “young control group” (Cyoung) as long suffering from MS as the pwMS in the LOMS group. Methods: Data from medical documentation and a questionnaire were analyzed using descriptive frequency analyses and testing for correlation between different variables also by generalized estimating equations. The Expanded Disabilty Status Scale (EDSS) score and the progression index were used as a measure of disability. Results: We found a significant association between smoking history and the current EDSS score in the Cyoung group, but not in the two older study groups. For physical activity, there was a significant negative correlation with EDSS score in the study group and the Cold group, alcoholic beverage consumption correlated with decreased EDSS in the Cold group. The intake of meat negatively correlated with the progression index in the LOMS group. Conclusion: In summary, different life-style factors correlated with disability depending on patient age and disease duration. These life-style factors may be considered in the future counseling of pwMS at older ages.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".