Calcium Homeostasis and Skeletal Integrity in Individuals with Familial Hypercholesterolemia and Aortic Calcification
Bibliographic record
Abstract
BACKGROUND: Familial hypercholesterolemia (FH) due to mutations in the low-density lipoprotein receptor (LDLR) gene exhibit severe, premature aortic calcification in a gene-dosage, age-dependent fashion. We sought to determine potential associations with mineral and skeletal indices. METHODS: We obtained computed tomography (CT) scan aortic calcium scores (AoCSs) in 19 (age 49 [SD 14] years) FH patients heterozygous for the 15-kb deletion at the LDLR gene and examined associations with various indices of mineral and skeletal homeostasis. RESULTS: We found that mean bone mineral density (BMD) at the femoral neck in these patients did not differ from age-, sex-, and province-matched mean BMD, and we observed no association of AoCS with any marker of bone resorption. However, there were negative correlations between AoCS and serum concentrations of osteocalcin, a marker of bone formation (r = -0.64, P = 0.0034), urinary calcium (r = -0.59, P = 0.0085), and estimated glomerular filtration rate (r = -0.67, P = 0.0019). CONCLUSIONS: We found that LDLR-deficient FH was not associated with obvious bone loss or a major disturbance in calcium homeostasis. The lack of LDLR, however, may modify osteoblast function or extracellular calcium distribution, manifesting as lower bone formation, and reduced calcium excretion, resulting in increased deposition in calcifying vascular tissue.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".