Incidence and Prevalence of Multiple Sclerosis in Newfoundland and Labrador
Bibliographic record
Abstract
ABSTRACT: Background: The incidence and prevalence of multiple sclerosis (MS) in Newfoundland and Labrador (NL) had been reported in 1984 and was considered to be relatively low at that time. This study revisits the incidence and prevalence of MS in NL for the year 2001. Methods: Case searches through patient files of neurologists in NL were conducted. A complete list of patients billed for MS in NL between 1996 and 2003 was obtained and all cases were confirmed via chart review. Results: There were 493 living MS patients yielding a prevalence of 94.4/100,000 which is significantly higher than previously reported. Of the living patients, 330 had relapsing remitting (RRMS), 94 had secondary progressive, 66 had primary progressive (PPMS) and three had unspecified MS. The total female to male ratio was 2.7:1. There was no difference between the female to male ratios for RRMS vs PPMS. Patients with PPMS had a later onset compared to RRMS (p<0.00001). Yearly incidences were relatively constant from 1994 to 2001 (5.6/100,000). Significant delays between first symptoms and final diagnosis were common and the delay time has not changed over the past 15 years. A prevalence of 88.9/100,000 was estimated from survival and incidence trends and was not significantly different than the measured prevalence (p=0.38). Conclusion: The increase in incidence and prevalence are accounted for through both better access to diagnostic facilities and more practicing neurologists. The revised prevalence and incidence are more in keeping with recently reported values throughout Canada. Conclusion: L’augmentation de l’incidence et de la prÉvalence se justifient par une plus grande accessibilitÉ aux moyens diagnostiques et par la prÉsence d’un plus grand nombre de neurologues. La prÉvalence et l’incidence que nous rapportons sont plus conformes à celles rapportÉes rÉcemment à travers le Canada.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".