Diagnosis of Creutzfeldt-Jakob Disease in Canada: An Update on Cerebrospinal Fluid Testing from 2016 to 2024
Bibliographic record
Abstract
BACKGROUND: Canada's National Microbiology Laboratory offers diagnostic testing of Creutzfeldt-Jakob disease (CJD) and related prion diseases. Since 2016, the highly sensitive and specific end-point quaking-induced conversion assay (EP-QuIC) of CSF samples has been used for antemortem CJD diagnostic testing alongside tests for surrogate biomarkers 14-3-3 and hTau. To assess EP-QuIC's utility, we undertook a retrospective study of Canadian CJD diagnostic testing conducted between 2016 and 2024. METHODS: Using CJD CSF test results collected between 2016 and 2024, we analyzed the CJD incidence in Canada, estimated based on positive EP-QuIC tests. Multivariate regression models were used to further evaluate CJD CSF testing between CJD subtypes, genders, age groups and codon 129 genotypes. RESULTS: From 2016 to 2024, the CJD incidence across Canada was estimated at 1.51 cases per million population per year. CJD incidence did not vary significantly across provinces, although a slight increase in CJD incidence was detected in New Brunswick due to increased sampling rates. EP-QuIC offered higher test sensitivity than both surrogate biomarker tests. Analysis of biomarker abundances and test positivity rates across biochemical subtypes revealed significant differences. We also detected variation in CSF test positivity rates across age groups and a trend of increasing biomarker abundance with age within EP-QuIC-negative cases. No significant variation was detected between males and females. CONCLUSION: EP-QuIC exhibits exceptional specificity and sensitivity for antemortem diagnosis of CJD, providing a valuable tool for the diagnosis of human prion diseases and for improved surveillance.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".