Geographical Variations in Sex Ratio Trends over Time in Multiple Sclerosis
Bibliographic record
Abstract
BACKGROUND: A female/male (F/M) ratio increase over time in multiple sclerosis (MS) patients was demonstrated in many countries around the world. So far, a direct comparison of sex ratio time-trends among MS populations from different geographical areas was not carried out. OBJECTIVE: In this paper we assessed and compared sex ratio trends, over a 60-year span, in MS populations belonging to different latitudinal areas. METHODS: Data of a cohort of 15,996 (F = 11,290; M = 4,706) definite MS with birth years ranging from 1930 to 1989 were extracted from the international MSBase registry and the New Zealand MS database. Gender ratios were calculated by six decades based on year of birth and were adjusted for the F/M born-alive ratio derived from the respective national registries of births. RESULTS: Adjusted sex ratios showed a significant increase from the first to the last decade in the whole MS sample (from 2.35 to 2.73; p = 0.03) and in the subgroups belonging to the areas between 83° N and 45° N (from 1.93 to 4.55; p<0.0001) and between 45° N to 35° N (from 1.46 to 2.30; p<0.05) latitude, while a sex ratio stability over time was found in the subgroup from areas between 12° S and 55° S latitude. The sex ratio increase mainly affected relapsing-remitting (RR) MS. CONCLUSIONS: Our results confirm a general sex ratio increase over time in RRMS and also demonstrate a latitudinal gradient of this increase. These findings add useful information for planning case-control studies aimed to explore sex-related factors responsible for MS development.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".