Sex ratio and age of onset in AQP4 antibody-associated NMOSD: a review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Aquaporin-4 (AQP4) antibody-associated neuromyelitis optica spectrum disorder (NMOSD) is an antibody-mediated inflammatory disease of the central nervous system. We have undertaken a systematic review and meta-analysis to ascertain the sex ratio and mean age of onset for AQP4 antibody associated NMOSD. We have also explored factors that impact on these demographic data. METHODS: A systematic search of databases was conducted according to the PRISMA guidelines. Articles reporting sex distribution and age of onset for AQP4 antibody-associated NMSOD were reviewed. An initially inclusive approach involving exploration with regression meta-analysis was followed by an analysis of just AQP4 antibody positive cases. RESULTS: A total of 528 articles were screened to yield 89 articles covering 19,415 individuals from 88 population samples. The female:male sex ratio was significantly influenced by the proportion of AQP4 antibody positive cases in the samples studied (p < 0.001). For AQP4 antibody-positive cases the overall estimate of the sex ratio was 8.89 (95% CI 7.78-10.15). For paediatric populations the estimate was 5.68 (95% CI 4.01-8.03) and for late-onset cases, it was 5.48 (95% CI 4.10-7.33). The mean age of onset was significantly associated with the mean life expectancy of the population sampled (p < 0.001). The mean age of onset for AQP4 antibody-positive cases in long-lived populations was 41.7 years versus 33.3 years in the remainder. CONCLUSIONS: The female:male sex ratio and the mean age of onset of AQP4 antibody-associated NMOSD are significantly higher than MS. The sex ratio increases with the proportion of cases that are positive for AQP4 antibodies and the mean age of onset increases with population life expectancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.032 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".