Bibliographic record
Abstract
PURPOSE OF REVIEW: To give an overview over the substantial advances in the diagnosis and management of Long-QT syndrome since its first description 60 years ago. RECENT FINDINGS: LQT syndrome remains the most common inherited arrhythmia and is a leading cause for sudden unexplained death accounting for up to 20-25% of cases. Rapid progress of genetic technology over the past 2 decades has significantly improved our understanding of molecular and genetic mechanisms of LQT. Despite all those novel insights, phenotype assessment and appropriate risk stratification in LQT remains challenging - even for the expert. SUMMARY: This review outlines our current understanding and approach to the clinical diagnosis and management of LQT as well as recent insights into genotype-phenotype correlations. Genetic testing has evolved beyond a pure diagnostic tool and is in addition increasingly integrated as complementary prognostic marker. With regard to the management of LQT, there is now evidence that the protective effect of beta-blockers is rather substance-specific than a class effect. Novel approaches - in conjunction with standard beta-blockers - are emerging including gene-specific treatment for certain subtypes of LQT. A specialized inherited arrhythmia clinic is the preferred resource for the complex risk stratification and individualized management of individuals with LQT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".