MétaCan
Menu
Back to cohort
Record W2146247094 · doi:10.1093/ndt/gfm233

Stability of lipids on peritoneal dialysis in a patient with familial LCAT deficiency

2007· article· en· W2146247094 on OpenAlexaff
Carolina Weber, J. Frohlich, Jian Wang, Robert A. Hegele, Clifford Chan-Yan

Bibliographic record

VenueNephrology Dialysis Transplantation · 2007
Typearticle
Languageen
FieldMedicine
TopicCholesterol and Lipid Metabolism
Canadian institutionsUniversity of British ColumbiaSt. Paul's HospitalWestern University
Fundersnot available
KeywordsMedicineProteinuriaPeritoneal dialysisInternal medicineEndocrinologyNephrotic syndromeMissense mutationRenal functionCreatinineGastroenterologyKidneyMutationBiochemistryBiology

Abstract

fetched live from OpenAlex

A 37-year-old man of northern European descent with familial lecithin:cholesterol acyltransferase (LCAT) deficiency started peritoneal dialysis (PD) one year ago, for end-stage renal failure. Proteinuria and an abnormal lipid profile were first noted in his early 20s. At the age of 29, he suffered an alkali burn to his right eye. When assessed by an ophthalmologist, diffuse lipid deposition in the corneas with accentuated arcus and preservation of his visual acuity were noted. At the age of 30 (in 1999), the following clinical findings were observed at nephrology and lipid specialist appointments: blood pressure 140/80, weight 112 kg (BMI 33), and marked arcus cornealis bilaterally. He was anaemic (haemoglobin 11.4g/dl), but had preserved renal function. Urinalysis revealed proteinuria and microhaematuria. A 24-h urine collection showed nephrotic range proteinuria at 6 g/day. His total cholesterol (TC) was 270 mg/dl (6.99 mmol/l), triglycerides (TG) 946 mg/dl (10.68 mmol/l) and HDL-C 15 mg/dl (0.38 mmol/l).

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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 designCase report
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

Citations18
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueNephrology Dialysis TransplantationSame topicCholesterol and Lipid MetabolismFrench-language works237,207