Human transmissible spongiform encephalopathies in eleven countries: diagnostic pattern across time, 1993–2002
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to describe the diagnostic panorama of human transmissible spongiform encephalopathies across 11 countries. METHODS: From data collected for surveillance purposes, we describe annual proportions of deaths due to different human transmissible spongiform encephalopathies in eleven EUROCJD-consortium countries over the period 1993-2002, as well as variations in the use of diagnostic tests. Using logistic models we quantified international differences and changes across time. RESULTS: In general, pre-mortem use of diagnostic investigations increased with time. International differences in pathological confirmation of sporadic Creutzfeldt-Jakob disease, stable over time, were evident. Compared to their counterparts, some countries displayed remarkable patterns, such as: 1) the high proportion, increasing with time, of variant Creutzfeldt-Jakob disease in the United Kingdom, (OR 607.99 95% CI 84.72-4363.40), and France (OR 18.35, 95% CI 2.20-152.83); 2) high, decreasing proportions of iatrogenic Creutzfeldt-Jakob disease in France, (OR 5.81 95% CI 4.09-8.24), and the United Kingdom, (OR 1.54 95% CI 1.03-2.30); and, 3) high and stable ratios of genetic forms in Slovakia (OR 21.82 95% CI 12.42-38.33) and Italy (OR 2.12 95% CI 1.69-2.68). CONCLUSION: Considerable international variation in aetiological subtypes of human transmissible spongiform encephalopathies was evident over the observation period. With the exception of variant Creutzfeldt-Jakob disease and iatrogenic Creutzfeldt-Jakob disease in France and the United Kingdom, these differences persisted across time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".