Timing of birth and disease progression in multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: The timing of birth has recently been associated with the risk of developing multiple sclerosis (MS) in later life. Whether the timing of birth also influences the disease course of MS is unknown. OBJECTIVE: To investigate whether the season or month of birth influences the timing of secondary progression or the time to landmark disability outcomes in MS. METHODS: To allow confirmation of findings, all analyses were performed in duplicate in two large natural history cohorts from geographically distinct but seasonally similar locations in Europe and North America. Kaplan-Meier survival analyses were used to investigate the influence of month and season of birth on 1) the time to and age at the development of secondary progression in patients with a relapsing disease onset and 2) the time to reach an Expanded Disability Status Scale (EDSS) score of 6.0 in patients with primary progressive and relapsing MS. RESULTS: No association between the month or season of birth and disease progression could be found, which was reproducible in both natural history cohorts. A seasonal trend was observed for the time to and age at secondary progression in Groningen, with March babies exhibiting a shorter time to and younger age at secondary progression. The birth month affected time to EDSS 6 for those with relapsing MS in British Columbia, with January babies exhibiting a longer time to EDSS 6. Neither finding could be reciprocated in the other natural history cohort. CONCLUSION: The season or month of birth does not appear to influence disease progression of MS.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".