SAT-250 Impact of Lipoprotein(a) on the Clinical Diagnosis of Familial Hypercholesterolaemia in Chinese
Bibliographic record
Abstract
Abstract Disclosure: C. Tang: None. T. Lui: None. C. Lee: None. H. Fong: None. Y. Wong: None. W. Shiu: None. K.C. Tan: None. Introduction: Elevated lipoprotein(a) [Lp(a)] has been shown to affect the diagnosis of familial hypercholesterolaemia (FH) in Caucasians. Since there are differences in Lp(a) levels by race and ethnicity and East Asians tend to have lower levels, we have investigated firstly whether Chinese FH patients have increased Lp(a) levels, and secondly whether the use of Lp(a)-corrected LDL-cholesterol (LDL-C) influences the clinical diagnosis of FH using the Dutch Lipid Clinic Network (DLCN) diagnostic criteria. Method: Adult patients with a clinical diagnosis of FH (defined as DLCN criteria score of ≥3) were recruited from a tertiary lipid clinic. Lp(a) levels were measured by an isoform-insensitive assay (Tina-quant Lipoprotein(a) Gen.2 assay, Roche Diagnostics). The Lp(a) distribution in FH patients was compared with that of the general population from the Hong Kong Cardiovascular Risk Factor Prevalence Study (CRISPS) using Kernel density estimation. LDL-C was adjusted for Lp(a)-cholesterol using the Rosenson-Marcovina formula [Lp(a)-cholesterol, mg/dL = Lp(a), nmol/L * 0.077]. Diagnostic reclassification rates were determined after the adjustments. Results: 151 FH patients were recruited, and genetic testing had been performed in 120 patients. The median Lp(a) level of the FH cohort was significantly higher than that of the CRISPS cohort [54.2 nmol/L (20.0-169.1) vs 31.4 nmol/L (18.8-56.5) respectively, p < 0.001]. Thirty-two percent of the FH subjects had Lp(a) levels ≥125 nmol/L. Using Lp(a)-corrected LDL-C led to a decrease in DLCN score in 15 patients (10%) but resulted in down-classification in only 5 patients (3.3%). Four patients had their DLCN score categories changed from probable FH to possible FH. Only 1 patient was re-classified from possible FH to unlikely FH. The number of patients who were down-classified in mutation-positive FH (n = 94) and mutation-negative FH patients (n = 26) were 1 (1.1%) and 2 (7.7%), respectively. No mutation-positive patient was re-classified to unlikely FH. Conclusion: The use of Lp(a)-corrected LDL-C influences the diagnosis of FH in Chinese using the DLCN criteria, albeit to a smaller degree than in Caucasian patients. This may be due to genetic polymorphisms in apolipoprotein(a), with Chinese individuals having lower Lp(a) concentrations compared to other ethnicities. Presentation: Saturday, July 12, 2025
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".