Sudden Cardiac Arrest in the Paediatric Population
Bibliographic record
Abstract
Sudden cardiac arrest in the young is a rare event with a range of potential causes including cardiomyopathies, ion channelopathies, and autonomic nervous system dysfunction. Investigations into the cause involve a multidisciplinary team, including cardiologists, geneticists, and psychologists. In addition to a detailed medical history, family history and circumstances surrounding the event are important in determining the cause. Clinical investigations including an electrocardiogram are fundamental in diagnosis and should be interpreted cautiously because some children may have atypical presentations and an evolving phenotype. The potential for misdiagnosis exists that could lead to incorrect long-term management strategies. If an inherited condition is suspected, genetic testing of the patient and cascade screening of family members is recommended with genetic counselling and psychological support. Medical management is left to the treating physician acknowledging that a clear diagnosis cannot be made in approximately half of cases. Secondary prevention implantable defibrillators are widely deployed but can be associated with complications in young patients. A plan for safe return to activity is recommended along with a proper transition of care into adulthood. Broad screening of the general population for arrhythmia syndromes is not recommended; preventative measures include screening paediatric patients for risk factors by their primary care physician. Several milestone events or activities that take place in youth could be used as opportunities to promote safety. Further work into risk stratification of this paediatric population through patient registries and greater awareness of cardiopulmonary resuscitation and automated external defibrillator use in saving lives is warranted.
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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".