The uptake and utility of genetic testing and genetic counseling for hypertrophic cardiomyopathy—A systematic review and meta‐analysis
Bibliographic record
Abstract
Genetic testing and genetic counseling are routinely indicated for patients with hypertrophic cardiomyopathy (HCM); however, the uptake and utility of these services is not entirely understood. This systematic review and meta-analysis summarizes the uptake and utility of genetic counseling and genetic testing for patients with HCM and their at-risk family members, as well as the impact of genetic counseling/testing on patient-reported outcomes (PROs). A systematic search was performed through March 12, 2021. Meta-analyses were performed whenever possible; other findings were qualitatively summarized. Forty-eight studies met inclusion criteria (47 observational, 1 randomized). Uptake of genetic testing in probands was 57% (95% confidence interval [CI]: 40, 73). Uptake of cascade screening for at-risk relatives were as follows: 61% for cascade genetic testing (95% CI: 45, 75), 58% for cardiac screening (e.g. echocardiography) (95% CI: 40, 73), and 69% for either/both approaches (95% CI: 43, 87). In addition, relatives of probands with a positive genetic test result were significantly more likely to undergo cascade screening compared to relatives of probands with a negative result (odds ratio = 3.17, 95% CI: 2.12, 4.76). Overall, uptake of genetic counseling in both probands and relatives ranged from 37% to 84%. Multiple studies found little difference in PROs between individuals receiving positive versus negative genetic test results; however, other studies found that individuals with positive genetic test results experienced worse psychological outcomes. Genetic testing may also inform life choices, particularly decisions related to reproduction and insurance. Genetic counseling was associated with high satisfaction, increased perceived personal control and empowerment, and decreased anxiety. Approximately half to three-quarters of patients with HCM and their relatives undergo genetic testing or cascade screening. PROs after genetic testing varied and genetic counseling was associated with high satisfaction and improved PROs.
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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 | 0.014 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.031 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".