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Record W2039571133 · doi:10.2147/tcrm.s11987

Enzyme replacement therapy for Fabry disease: some answers but more questions

2011· article· en· W2039571133 on OpenAlexaff
Sandra Sirrs, Majid Alfadhel

Bibliographic record

VenueTherapeutics and Clinical Risk Management · 2011
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsVancouver Hospital and Health Sciences CentreUniversity of British ColumbiaVancouver Coastal Health
Fundersnot available
KeywordsEnzyme replacement therapyMedicineFabry diseaseDiseaseRenal functionProteinuriaInternal medicineStroke (engine)Quality of life (healthcare)Intensive care medicineKidney

Abstract

fetched live from OpenAlex

Fabry disease (FD) is a multisystem, X-linked disorder of glycosphingolipid metabolism caused by enzyme deficiency of α-galactosidase A. Affected patients have symptoms including acroparesthesias, angiokeratomas, and hypohidrosis. More serious manifestations include debilitating pain and gastrointestinal symptoms, proteinuria and gradual deterioration of renal function leading to end-stage renal disease, hypertrophic cardiomyopathy, and stroke. Heterozygous females may have symptoms as severe as males with the classic phenotype. Before 2001, treatment of patients with FD was supportive. The successful development of enzyme replacement therapy (ERT) has been a great advancement in the treatment of patients with FD and can stabilize renal function and cardiac size, as well as improve pain and quality of life of patients with FD. In this review, we have provided a critical appraisal of the literature on the effects of ERT for FD. This analysis shows that data available on the treatment of FD are often derived from studies which are not controlled, rely on surrogate markers, and are of insufficient power to detect differences on hard clinical endpoints. Further studies of higher quality are needed to answer the questions that remain concerning the efficacy of ERT for FD.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.803
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.098
GPT teacher head0.398
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations34
Published2011
Admission routes1
Has abstractyes

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