Bibliographic record
Abstract
PURPOSE OF REVIEW: The sustained decline in mortality following congenital heart surgery, while important, also has resulted in an emerging focus upon the use of processes and technological developments to reduce early postoperative morbidity. We summarize here recent efforts within the field of pediatric cardiac intensive care to optimize outcomes associated with the perioperative management of the child with congenital heart disease. RECENT FINDINGS: Goal-directed and protocol-driven therapy targeting optimization of oxygen delivery improves outcomes in the management of many populations of critically ill patients, and is now increasingly used following congenital heart surgery with a low associated incidence of organ failure and favorable early survival. Restrictive blood product transfusion practices following congenital heart surgery are showing promise in reducing donor exposures and transfusion-associated morbidities without a resulting increase in end organ dysfunction. Technological developments are affording noninvasive opportunities for earlier recognition and intervention in the deteriorating child, while also providing means for support of the failing myocardium, both in an acute setting during cardiopulmonary resuscitation, and among patients with end-stage heart failure requiring longer-term mechanical circulatory support. SUMMARY: Multi-institutional, prospective evaluation of perioperative management practices, along with patient-specific, integrated electronic health information, provides unique opportunities for investigators to identify and test both processes and technological tools in confronting the most challenging aspects of early postoperative management following congenital heart surgery.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.012 |
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".