Lipoprotein Glomerulopathy, First Case Report from Canada
Bibliographic record
Abstract
Abstract: Lipoprotein glomerulopathy (LPG) is caused by a mutation in the apolipoprotein E gene ( APOE ) gene and is characterized by lipoprotein thrombi in glomerular capillaries. Here, we describe a case of LPG, the first to be reported from Canada and the first case of LPG in North America to be associated with the APOE Tokyo/Maebashi mutation (p.Leu162_Lys164del, traditional nomenclature 142_144del). A 49-year-old man of Chinese descent with a previous diagnosis of dyslipidemia and a new diagnosis of hypertension was found to have proteinuria on routine urinalysis. Renal biopsy showed markedly dilated glomerular capillaries filled with pale staining mesh-like material that stained positive for Oil-Red-O, consistent with lipoprotein thrombi. APOE gene sequencing confirmed the diagnosis of LPG. The patient was treated with fenofibrate and perindopril. His lipid profile normalized and proteinuria dropped to minimal levels. Repeat renal biopsy 2 years after the first showed resolution of lipoprotein thrombi but with rare residual granular densities by electron microscopy consistent with lipoprotein in the subendothelial space, supporting the hypothesis that this subendothelial material contains precursors to lipoprotein thrombi. Keywords: apolipoprotein E, apoE Tokyo/Maebashi, proteinuria, dyslipidemia, fibrate, lipoprotein glomerulopathy
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".