P.042 Could Live Cell-Based Assay increase the acetylcholine receptor autoantibodies seropositivity in patients with clinical suspicion of myasthenia gravis?
Bibliographic record
Abstract
Background: AChR antibodies (Abs) in Myasthnia Gravis (MG) are detected in approximately 50% of ocular and 85% of generalized MG by the current gold standard radioimmunoprecipitation assay (RIPA). Recently, fixed and lived Cell-Based assays (L-CBA) are developed. We clinically validated our in-house L-CBA in detecting AChR Ab in clinically suspected MG patients. Methods: Between January 2020 and April 2022, we assayed 10167 sera for AChR Ab by RIPA. We also assayed 4349 of AChR Ab seronegative sera of the above suspected MG samples for anti-MuSK Ab by RIPA. Then 1228 sera of double seronegative and/or borderline AChR Ab was assessed by L-CBA for AChR Ab. For clinical validation, we obtained clinical information on 36 seropositive cases for AChR Ab by L-CBA. Results: We found additional eighty-four cases seropositive for AChR Ab by L-CBA. The clinical information was obtained for 36 cases and based on their final diagnosis, twenty had generalized MG, thirteen had ocular MG, 2 not yet diagnosed and 1 case was of not-MG. Conclusions: The L- CBA has demonstrated improved sensitivity and higher diagnostics performance than RIPA. The L-CBA allowed improved clinical diagnosis and increased seropositivity (by 7%) in clinically suspected MG patients who were earlier seronegative/borderline for AChR Ab by RIPA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".