Hypoplastic Left Heart Syndrome: Diagnosis, Care and Management From Fetal Life and Beyond
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hypoplastic left heart syndrome (HLHS) accounts for 2% to 3% of all congenital heart disease but is responsible for 25% to 40% of all neonatal cardiac deaths. Although the exact genetic origins of HLHS have not been clearly defined, various genetic and chromosomal associations have been identified. Advancements in fetal echocardiography have resulted in accurate diagnosis of congenital heart disease. On the basis of physical examination findings, fetuses may be candidates for prenatal intervention. In general, after prenatal diagnosis of HLHS, parents are faced with 2 choices: termination or continuation of pregnancy. If pregnancy is continued to delivery, patients may choose comfort care, surgical palliation with the Fontan procedure, or transplantation. A once lethal congenital anomaly, HLHS has undergone a marked evolution in management and prognosis during the last several decades. With advancements in prenatal diagnosis, neonatal management, and surgical palliation, patient survival has drastically improved: at an experienced center, current survival rates are very high after the Norwood procedure, with high rates of overall freedom from death or transplantation through 20 years. With survival becoming more promising, the issues that now take precedence are neurodevelopmental outcomes, Fontan procedure complications, and quality of life. Although much progress has been made in caring for this patient population, HLHS remains a high-risk condition that requires lifelong medical follow-up and has significant long-term morbidity, affecting overall quality of life for patients and their families.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it