A New Dawn for Brazilian Pediatric Cardiac Surgery Is on the Way — Issues Around and Outside the Operating Room
Bibliographic record
Abstract
In some developing countries, congenital heart disease still stands out among the leading causes of death in the first year of life. Therefore, there is a great need to develop programs designed to improve outcomes in the diagnosis and surgical treatment of congenital heart disease in these nations, where children have always been and still are severely underserved. The Brazilian Public Health Care System demands universal access to treatment as a constitutional right. Therefore, an underfunded Pediatric Cardiac Surgery program is unacceptable since it will cost lives and increase the infant mortality rate. Additionally, poor funding decreases providers' interest, impedes technological advances and multidisciplinary engagement, and reduces access to comprehensive care. Unfortunately, in most developing countries, Pediatric Cardiac Surgery progress is still the result of isolated personal efforts, dedication, and individual resilience. This article aims to present the current state of Brazilian pediatric cardiac surgery and discuss the structural and human limitations in developing a quality care system for children with congenital heart disease. Considering such constraints, quality improvement programs via International collaboration with centers of excellence, based on proper data collection and outcomes analysis, have been introduced in the country. Such initiatives should bring a new dawn to Brazilian Pediatric Cardiac 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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".