FP114RENOPROTECTIVE EFFECT OF AGALSIDASE ALFA IN FABRY DISEASE IS INDEPENDENT OF TYPE OF MUTATION: RESULTS OF 12-YEAR FOLLOW-UP
Bibliographic record
Abstract
INTRODUCTION: We aimed to evaluate the impact of agalsidase alfa treatment on renal parameters in patients with Fabry disease in the Fabry Outcome Survey (FOS) registry. METHODS: We analyzed male patients aged >16 years at start of agalsidase alfa (baseline; BL), with a minimum treatment duration of 7 years, ≥3 available eGFR measurements, available BL proteinuria data, no history of dialysis/transplantation, and eGFR at BL ≥45 ml/min/1.73m². eGFR was calculated using the CKD-EPI formula. Patients with mutations associated with a classical phenotype (“classical”) were compared to “other” (including late-onset and variants of unknown significance). RESULTS: A total of 138 patients were analyzed; including 50 classical, 31 other, and 57 with no genetic data available. The most frequent among classical mutations were A143P (14%), M284T (6%), and R220X (6%). FP114 Table CONCLUSIONS: Use of agalsidase alfa may be associated with potential renoprotective effects in patients with mutations associated with a classical phenotype, as well as other mutations, leading to stabilization of renal function relative to expected decline in patients with Fabry disease. The impact of proteinuria merits further evaluation.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; 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".