Effectiveness of alternative strategies to define index case phenotypes to aid genetic diagnosis of familial hypercholesterolaemia
Bibliographic record
Abstract
OBJECTIVE: To determine the utility of secondary stratification measures to improve the ascertainment of index cases of familial hypercholesterolaemia (FH). DESIGN: A retrospective study of genotyped index patients with Simon Broome (SB) FH. SETTING: University teaching hospital. PATIENTS: 204 patients aged 55±14 years; 36% had tendon xanthoma (TX), 21% had coronary heart disease (CHD), low-density lipoprotein cholesterol (LDL-C) was 6.20±2.24 mmol/l and 55% had genetic FH. INTERVENTIONS: The effects of different staging systems (SB vs Dutch criteria), presence of TX, use of LDL-C level, personal history of CHD and imaging evidence of atheroma by carotid intima-media thickness or coronary artery calcium score to identify genetic FH was explored. OUTCOME MEASURES: Changes in C-statistic and net reclassification index (NRI). RESULTS: SB criteria gave a C-statistic of 0.64 comprising C=0.65 in TX(+) and C=0.5 in TX(-) patients. Genetic FH was present in 75% of TX(+) compared with 44% in TX(-) patients. The Dutch criteria gave C=0.72. Addition of imaging criteria to prior CHD raised C=0.64 to C=0.65 in all patients with a NRI of 19% (p=0.06). In TX(-) patients imaging raised C=0.50 to C=0.65 with a NRI of 0.38 (p=0.001) and a weighted comparison index of 0.28, implying the detection of 14 more FH cases per thousand. CONCLUSIONS: Patients with tendon xanthoma (definite FH) should be genotyped. In patients with possible FH, the presence of a personal history of CHD or imaging evidence of increased atheroma offers the best method of identifying index patients likely to have monogenic FH.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".