Sex Differences in Mortality in Children Undergoing Congenital Heart Disease Surgery
Bibliographic record
Abstract
BACKGROUND: The changing demographics of the adult congenital heart disease (CHD) population requires an understanding of the factors that impact patient survival to adulthood. We sought to investigate sex differences in CHD surgical mortality in children. METHODS AND RESULTS: Children <18 years old hospitalized for CHD surgery were identified using the Kids' Inpatient Database in 2000, 2003, and 2006. Demographic, diagnostic, and procedural variables were grouped according to RACHS-1 (Risk Adjustment for Congenital Heart Surgery) method. Logistic regression was used to determine the odds ratio of death in females versus males adjusting for RACHS-1 risk category, age, prematurity, major noncardiac anomalies, and multiple procedures. Analyses were stratified by RACHS-1 risk categories and age. Of 33 848 hospitalizations for CHD surgery, 54.7% were in males. Males were more likely than females to have CHD surgery in infancy, high-risk CHD surgery, and multiple CHD procedures. Females had more major noncardiac structural anomalies and more low-risk procedures. However, the adjusted risk of in-hospital death was higher in females (odds ratio, 1.21; 95% confidence interval, 1.08 to 1.36) on account of the subgroup with high-risk surgeries who were <1 year of age (odds ratio, 1.39; 95% confidence interval, 1.16 to 1.67). CONCLUSIONS: In this large US population study, more male children underwent CHD surgery and had high-risk procedures. Female infants who had high-risk procedures were at higher risk for death, but this accounted for a small proportion of females and is therefore unlikely to have a major impact on the changing demographics in adults in CHD.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".