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Record W2088927845 · doi:10.1159/000081044

Epidemiological Study of Creutzfeldt-Jakob Disease Death Certificates in Canada, 1979–2001

2004· article· en· W2088927845 on OpenAlexaffabout
Susie ElSaadany, R Semenciw, Maura Ricketts, Yang Mao, Antonio Giulivi

Bibliographic record

VenueNeuroepidemiology · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsHealth Canada
Fundersnot available
KeywordsMedicineEpidemiologyAutopsyDemographyCause of deathDeath certificateMortality rateIncidence (geometry)DiseasePediatricsGerontologyPathologySurgery

Abstract

fetched live from OpenAlex

INTRODUCTION: A descriptive epidemiological analysis to update trends of Creutzfeldt-Jakob disease (CJD) deaths, from 1979-2001, was undertaken. METHODS: Cases with CJD as underlying cause were extracted. Age-adjusted death rates by age, sex, and province were calculated. Information on birthplace, autopsy indications and type of work were examined for death certificates from 1979 to 1997. RESULTS: 462 cases were identified between 1979 and 1997. The average annual age-standardized mortality rate was 0.93 deaths per million persons during this period and 1.03 for 1998-2001. Persons 60 years or older demonstrated the highest average annual mortality rate. Rates were slightly higher among males and increased with age. Persons born in Canada accounted for 72% of deaths. Cause of death was verified by autopsy for 9.1% of patients while 21% of deaths indicated that additional information relating to underlying cause was expected. The service industry occupation represented the largest mortality (Quebec does not capture these data). CONCLUSIONS: Canadian rates are consistent with those of the United States and slightly higher than those of certain European countries. Approximately 44% of CJD cases had an autopsy record, though many were incomplete. We are unable to determine a relation with occupation. We recommend annual analysis of CJD death registrations for updated surveillance of trends, as mortality data are an efficient tool for monitoring incidence.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.053
GPT teacher head0.301
Teacher spread0.248 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2004
Admission routes2
Has abstractyes

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