P.003 CJD in the modern era: The value of clinical features and diagnostic tests
Bibliographic record
Abstract
Background: The advent of real-time quaking-induced conversion (RT-QuIC) assays has transformed the diagnostic approach to sporadic Creutzfeldt-Jakob disease (CJD) facilitating earlier recognition of affected patients. Recognizing this, we evaluated the performance of clinical features and diagnostic tests for CJD in the modern era. Methods: Clinical data were extracted from the electronic medical records of 115 patients with probable or definite CJD assessed at Mayo Clinic from 2014-2021. Clinical features and diagnostic tests were evaluated at presentation, and associations with diagnosis and prognosis determined. Results: Mean age-at-symptom onset was 64.8±9.4 years; 68 patients were female (59%). The sensitivity of clinical markers (myoclonus) and tests historically considered in patients with suspected CJD was poor (stereotyped EEG abnormalities, 16%; CSF 14-3-3, 60%). Conversely, RT-QuIC (93%), t-tau >1149 pg/mL (88%), and characteristic signal abnormalities on MRI (77%) identified most patients. Multivariable linear regression confirmed shorter days-to-death in patients with myoclonus (125.9, CI95% 23.3-15.5, p=0.026), visual/cerebellar signs (180.19, CI95% 282.2-78.2, p<0.001), positive 14-3-3 (193, CI95% 304.9-82.9; p<0.001), and elevated t-tau (9.0, CI95% 1.0-18.0, for every 1000 pg/ml elevation; p=0.041). Conclusions: CSF RT-QuIC and elevated t-tau, and stereotyped MRI abnormalities were consistently detected in CJD patients. Myoclonus, EEG findings, and CSF protein 14-3-3 were less useful in the modern era.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".