Bibliographic record
Abstract
Heart failure (HF) in children is a complex syndrome with multiple diverse etiologies and both acute and chronic presentations. Chronic presentations can persist throughout childhood and adolescence, and require diligent management with ongoing reassessment to maximize survival and quality of life. Stages of HF are key to recognize as they guide both management and inform prognosis. In more severe cases, children can present with signs of low cardiac output and circulatory collapse with potential to transition either to a chronic HF stage or progress to a need for advanced HF therapies. Morbidity and mortality are high. Managing HF requires a multi-disciplinary approach that can adapt to the needs of the different phases of childhood and adolescence. Treatment can include medications, nutritional support, activity modifications, and potentially surgical intervention, pacemaker, respiratory or mechanical support, or even heart transplantation. Limited evidence exists for almost all medical therapies used in the management of HF in children and approaches are predominantly extrapolated from extensive adult experience. There are multiple maladaptive pathways in the failing heart; medications that modify these maladaptive pathways promote "reverse remodelling" of the myocardium and are key to the management, forming the basis for "guideline directed medical therapy". The purpose of this review is to summarize the current state of the art management of systolic HF in children.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".