Prevalence of Congenital Heart Defects and their Non-Inherited Risk Factors among Children through the Period 2019-2023: A Retrospective Comparative Study
Bibliographic record
Abstract
Background: Congenital heart defects (CHD) are the most common types of congenital disabilities. The frequency of CHD among their patient populations also remains the leading cause of their increased mortality, accounting for an estimated 50% of all causes of death from abnormalities. Objectives: The study aimed to identify the prevalence of non-inherited risk factors among children with cardiac defects and compare the prevalence of congenital heart defects among children in different governorates in Iraq related to non-inherited risk factors. Materials and Methods: A retrospective study design was used to study congenital heart defects in children in Babylon Centre for Catheterization and Cardiac Surgery in Al-Imam Sadiq Hospital Babylon province, Iraq, from 15/10/2023 to 13/6/2024. A nonprobability convenience sample of 542 patients aged 0-18 years with CHD was collected by administering a constructed tool for the study. The data were collected from all Iraqi governorates, including the north, center, and south, as well as east and west countries. Result: The study shows the mean age of children was 2.2 ±9.2 years. The majority of children included were within infant age groups, almost equal in their sexes, giving girl to boy, 1.04:1. The age at screening and diagnosis of Echo was more than half in the first month, and the type of defect was Ventricular-septal-defect (VSD) and Tetralogy of Fallot (TOF). The study findings show that there is a statistically significant relationship between risk factors related to maternal medication history, including Folic acid Supplements. Maternal diseases such as Rubella, with CHD, and the highest recorded governorates for congenital heart defects are Baghdad, Mosul, and Diyala. Conclusions: The study concludes that most children included were within infant age groups, almost equal in their sexes, and the highest recorded governorates for congenital heart defects are Baghdad, Mosul, and Diyala. Also, the most frequent CHD is VSD and TOF, the history of maternal medication use, including folic acid supplements, and maternal diseases such as Rubella were significant factors in assessing the risk or outcome.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".