Brain Injury and Neurodevelopmental Outcome in Congenital Heart Disease: A Systematic Review
Bibliographic record
Abstract
CONTEXT: Brain injury during prenatal and preoperative postnatal life might play a major role in neurodevelopmental impairment in infants with congenital heart disease (CHD) who require corrective or palliative surgery during infancy. A systematic review of cerebral findings during this period in relation to neurodevelopmental outcome (NDO), however, is lacking. OBJECTIVE: To assess the association between prenatal and postnatal preoperative cerebral findings and NDO in infants with CHD who require corrective or palliative surgery during infancy. DATA SOURCES: PubMed, Embase, reference lists. STUDY SELECTION: We conducted 3 different searches for English literature between 2000 and 2016; 1 for prenatal cerebral findings, 1 for postnatal preoperative cerebral findings, and 1 for the association between brain injury and NDO. DATA EXTRACTION: Two reviewers independently screened sources and extracted data on cerebral findings and neurodevelopmental outcome. Quality of studies was assessed using the Newcastle-Ottawa Quality Assessment Scale. RESULTS: Abnormal cerebral findings are common during the prenatal and postnatal preoperative periods. Prenatally, a delay of cerebral development was most common; postnatally, white matter injury, periventricular leukomalacia, and stroke were frequently observed. Abnormal Doppler measurements, brain immaturity, cerebral oxygenation, and abnormal EEG or amplitude-integrated EEG were all associated with NDO. LIMITATIONS: Observational studies, different types of CHD with different pathophysiological effects, and different reference values. CONCLUSIONS: Prenatal and postnatal preoperative abnormal cerebral findings might play an important role in neurodevelopmental impairment in infants with CHD. Increased awareness of the vulnerability of the young developing brain of an infant with CHD among caregivers is essential.
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 | 0.005 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".