The North American Immune Tolerance Registry: Practices, Outcomes, Outcome Predictors
Bibliographic record
Abstract
The North American Immune Tolerance Registry was initiated to study of immune tolerance (ITT) in Canada and the United States with respect to: 1) therapeutic regimens in use for haemophilia A (HA) and B (HB) inhibitor patients; 2) therapeutic outcomes; 3) potential predictors of successful outcome and 4) complications of therapy. Data on 188 ITT courses was collected by questionnaire from 60 haemophilia centers from 1993-99. Among the completed courses, the overall success rate was 70% (115/164) for all HA and 31% (5/16) for all HB. Outcome parameters noted to be predictive of ITT success for all HA were 1) pre-ITT induction (p = 0.003), 2) ITT peak (p = 0.007) and 3) historical pre ITT peak (p = 0.04) inhibitor titres. An inverse correlation between total daily dose (units/kg/day) and success: (80% with under 50; 71% with 50-99; 73% with 100-199; and 41% with > or = 200, p = 0.01) was found. Outcome predictors were not evaluable for HB, although adverse reactions to therapy, including nephrotic syndrome, and access complications were more common among failed courses. Infection most often complicated the use of access catheters. These results are discussed within the context of the international ITT registry and upcoming prospective ITT study.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".