Clinical genetic testing in pediatric cardiomyopathy: Is bigger better?
Bibliographic record
Abstract
BACKGROUND: For clinical genetic testing of cardiomyopathy (CMP), current guidelines do not address which gene panels to use: targeted panels specific to a CMP phenotype or expanded (panCMP) panels that include genes associated with multiple phenotypic subtypes. AIM: Our objective was to assess the clinical utility of targeted versus panCMP panel testing in pediatric CMPs. METHODS: 151 pediatric patients with primary hypertrophic (n = 66), dilated (n = 64), restrictive (n = 8), or left-ventricular non-compaction (n = 13) CMP who underwent clinical genetic panel testing at a single centre were included. PanCMP (n = 47) and targeted panel testing (n = 104) were compared for yield of pathogenic variants and variants of unknown significance (VUS). RESULTS: Pathogenic variants were identified in 26% of patients, 42% had indeterminate results (only VUS detected), and 32% had negative results. Yield was lower (15%) in panCMP vs. targeted panel testing (32%) (P = .03) in all CMP subtypes. VUS detection was higher with panCMP (87%) than targeted panel testing (30%) (P <.0001). PanCMP panel testing only identified pathogenic variants in genes that overlapped targeted panels. CONCLUSION: PanCMP testing did not increase diagnostic yield compared to targeted panel testing. Until accuracy of variant interpretation with panCMP panels improves, targeted panels may be suitable for clinical testing in pediatric CMP.
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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 | 0.011 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".