P.045 Aquaporin-4 and Myelin Oligodendrocyte Glycoprotein Antibody Testing in Calgary: A Quality Improvement Review
Bibliographic record
Abstract
Background: Despite the availability of cell-based assays for aquaporin-4 (AQP4) and myelin oligodendrocyte glycoprotein (MOG) antibodies provincially, outside confirmatory testing is often performed (typically Mayo Clinic Laboratories, USA) when results deviate from expected. It is unknown how often this costly undertaking (upwards of $1,200 CAN) alters diagnosis and management. Methods: We undertook a quality improvement project evaluating the concordance/discordance rate with select chart review in all patients who had cell-based AQP4 or MOG IgG antibody testing at Mitogen Diagnostics (MitogenDx; Calgary, Alberta) and subsequent testing at Mayo Clinic Laboratories from as early as 2010 to July 2020. Results: Preliminary review of data from January 2016 to July 2020 retrieved 145 paired tests; 10 of which were discordant (concordance rate: 93.1%). Chart review confirmed 9 truly discordant cases, often associated with AQP4 or MOG weak-positive results (7/9 cases) or presumed false negative AQP4 results in prototypical neuromyelitis optica spectrum disorder (2/9 cases). Conclusions: Discordant results were rare when comparing MitogenDx local AQP4/MOG antibody test results to those referred out to Mayo Clinic Laboratories, impacting diagnosis and treatment in only 3 patients out of the total. Our results suggest costly outside confirmatory testing of AQP4/MOG antibodies could be reduced.
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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 | 0.015 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".