Epidemiology and early predictors of Fabry nephropathy: evaluation of long-term outcomes from a national Fabry centre
Bibliographic record
Abstract
BACKGROUND: Fabry disease is a rare genetic lysosomal storage disorder, whereby the accumulation of sphingolipids consequently leads to kidney structural damage and dysfunction. We explored the epidemiology of chronic kidney disease (CKD) among patients with Fabry disease at a major UK referral centre in Greater Manchester serving over 7 million people, to inform early predictors of kidney disease and possible treatment planning. METHODS: Data were sourced from the electronic records of registered participants from November 2020 to February 2022 of adults diagnosed with Fabry disease, with at least 1 year of follow-up. Four hundred and five participants (female = 223, male = 182) met the initial eligibility criteria. Our study focused on identifying factors linked to incident CKD, with 395 evaluable individuals undergoing outcome analysis over a median of 6.4 years. RESULTS: Findings concluded that 60.5% of participants received disease-modifying treatments, 29.7% experienced non-fatal cardiovascular events, 3.3% developed end-stage kidney disease (ESKD), and 7.3% died. Men had higher use of disease modifying therapy, progression to ESKD requiring kidney replacement therapy, cardiovascular events, and mortality compared to women. Subgroup analysis over 9 years revealed that older age, cardiovascular history, renin-angiotensin-aldosterone system inhibitor use, and higher urine albumin-to-creatinine ratio (uACR) were predictors of faster estimated glomerular filtration rate (eGFR) decline and increased mortality. At baseline, 47.8% of 249 patients with uACR data had CKD, and 25.4% of the remaining individuals developed CKD during follow-up, associated with higher uACR and lower, albeit normal eGFR levels. CONCLUSION: Over 60% of Fabry disease patients are at lifetime risk of developing CKD, with a substantial risk of mortality, even with initially normal uACR and eGFR values.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".