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Record W2021746707 · doi:10.1159/000168482

Agalsidase Alfa Slows the Decline in Renal Function in Patients with Fabry Disease

2008· review· en· W2021746707 on OpenAlexaff
Sandro Feriozzi, Andreas Schwarting, Gere Sunder–Plassmann, Michael L. West, Markus Cybulla

Bibliographic record

VenueAmerican Journal of Nephrology · 2008
Typereview
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsDalhousie University
Fundersnot available
KeywordsRenal functionMedicineFabry diseaseUrologyCreatinineNephropathyProteinuriaInternal medicineEndocrinologyKidney diseaseAngiotensin-converting enzymeEnzyme replacement therapyACE inhibitorHypertensive NephropathyKidneyDiabetic nephropathyDiabetes mellitusDiseaseBlood pressure

Abstract

fetched live from OpenAlex

The aim of this study was to determine the effects of enzyme replacement therapy with agalsidase alpha on renal function in patients with Fabry nephropathy. Serum creatinine data were collected from 165 adult patients during 3 years of treatment. Serum creatinine increased in all men whereas it was stable in women, except in stage II renal disease (Kidney Disease Outcomes Quality Initiative). The estimated glomerular filtration rate (eGFR) declined in males with stage I and II (from 115.0 +/- 22.2 to 98.3 +/- 27.3 and from 76.5 +/- 8.1 to 66.3 +/-21.6 ml/min/1.73 m(2), respectively; both p < 0.01), whereas eGFR was stable in stage III. In females, eGFR was stable in stages I and III, and decreased in stage II (from 72.5 +/- 8.3 to 67.3 +/- 13.6 ml/min/1.73 m(2); p = 0.01). The 24-hour proteinuria was <1 g in all patients, and most patients (96%) were treated with angiotensin receptor blockers (ARBs) or angiotensin-converting enzyme (ACE) inhibitors. Agalsidase alpha in combination with ACE inhibitors/ARB may be effective in slowing the deterioration in renal function in Fabry nephropathy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.020
GPT teacher head0.309
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations69
Published2008
Admission routes1
Has abstractyes

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Same venueAmerican Journal of NephrologySame topicLysosomal Storage Disorders ResearchFrench-language works237,207