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Record W2086500231 · doi:10.1097/mnh.0000000000000113

Risk factors for progression in ADPKD

2015· review· en· W2086500231 on OpenAlexaff
Ahsan Alam

Bibliographic record

VenueCurrent Opinion in Nephrology & Hypertension · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and Kidney Cyst Diseases
Canadian institutionsRoyal Victoria HospitalMcGill University Health CentreRoyal Victoria Regional Health Centre
Fundersnot available
KeywordsAutosomal dominant polycystic kidney diseaseDiseaseMedicineRenal functionPolycystic kidney diseaseKidney diseaseClinical trialCystInternal medicineKidneyBioinformaticsIntensive care medicinePathologyBiology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Autosomal dominant polycystic kidney disease (ADPKD) is the most common hereditary kidney disease. This article will describe the factors associated with both functional and structural evidence of disease progression. It will also review the results of recent clinical trials that have shown an impact on markers of disease progression. RECENT FINDINGS: A variety of prognostic factors have been described that relate to a decline in glomerular filtration rate or an increase in total cyst or kidney volumes. We now have clinical trials that show that glomerular filtration rate decline and kidney volume growth can be slowed in those with ADPKD. SUMMARY: With the emergence of potential disease-modifying therapies, factors that can accurately identify those who are most at risk for renal progression or ADPKD-related complications need to be identified and validated.

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: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.391
Teacher spread0.293 · 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

Citations7
Published2015
Admission routes1
Has abstractyes

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