Fetal Alcohol Syndrome Effect of Alcohol on Heart: Case Presentation of Two Alcoholic Patients with Alcoholic Cardiomyopathy
Bibliographic record
Abstract
Background: About 40 thousand newborns are delivered annually with fetal alcohol syndrome (FAS). It induces serious CNS complications. Methods: In a review of, the word “ fetal alcohol syndrome” was searched in PubMed and Google Scholar and the retrieved articles were summarized. Results: Many studies showed that alcohol can cause more defects in fetus than heroin, cocaine and marijuana. The possible defects caused by alcohol include physical, mental and behavioral retardation, learning deficits, growth restriction, and some social problems. FAS is more common than Down syndrome (1%). In Germany, 2200 newborns are delivered with FAS annually. According to the 2007 US National Survey on Drug Use and Health, pregnant women aged 15 to 44 reported alcohol use at a rate of 11.6%, with 3.7% reported binge drinking and 0.7% reported heavy drinking in the month before the survey. However, these rates were considerably higher in non- pregnant women with same age (53%, 24.1%, and 5.5% respectively). Alcohol use during pregnancy is a significant clinical concern. In South Africa, it is counted as 70-80 in 1000 live births. Alcoholic fathers may also induce some defects in their children. Conclusion: FAS is nonhereditary cause of mental retardation and neurologic deficit in the Western world. The prevalence is high. It is preventive completely but has no treatment. In Iran we have no exact prevalence of FAS due to cultural problems. The day September 9th has been named for the FAS as the sign of 9 months of intrauterine life. Many countries such as Germany, USA, England, New Zealand, Scotland, Switzerland, Canada, Australia and Austria have paid lot of atte ntion to prevention of FAS.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".