Positive Predictive Value of Anti-GAD65 ELISA Cut-Offs for Neurological Autoimmunity
Bibliographic record
Abstract
High anti-GAD65 levels associate with core manifestations of GAD65 neurological autoimmunity. ELISA cut-offs for high anti-GAD65 levels (>10,000 IU/ml in serum, >100 IU/ml in CSF) have been proposed that merit further evaluation. We reviewed patients who underwent anti-GAD65 ELISA for suspected autoimmune encephalitis and found values above these cut-offs to have a positive predictive value (PPV) for neurological autoimmunity of 88%. Anti-GAD65 values above proposed ELISA cut-offs have a reasonably high PPV for neurological autoimmunity in patients with suspected autoimmune encephalitis. Consideration of alternative diagnoses and corroboration with CSF can help flag potentially clinically irrelevant results and avoid patient misdiagnosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".