Life Expectancy of People with Fetal Alcohol Syndrome.
Bibliographic record
Abstract
OBJECTIVES: To estimate the life expectancy and specify the causes of death among people with fetal alcohol syndrome (FAS). METHODS: Included were all patients recorded in Alberta provincial databases of inpatients, outpatients, or practitioner claims from 2003 to 2012. People with FAS were identified by ICD-9 code 760.71 and ICD-10 codes Q86.0 and P04.3, and were linked to the Vital Statistics Death Registry to get information about mortality. Life expectancy was estimated by using the life table template developed in the United Kingdom, which is recommended for estimating life expectancy in small areas or populations. RESULTS: The life expectancy at birth of people with FAS was 34 years (95% confidence interval: 31 to 37 years), which was about 42% of that of the general population. The leading causes of death for people with FAS were "external causes" (44%), which include suicide (15%), accidents (14%), poisoning by illegal drugs or alcohol (7%), and other external causes (7%). Other common causes of death were diseases of the nervous and respiratory systems (8% each), diseases of the digestive system (7%), congenital malformations (7%), mental and behavioural disorders (4%), and diseases of the circulatory system (4%). CONCLUSION: The life expectancy of people with FAS is considerably lower than that of the general population. As the cause of FAS is known and preventable, more attention devoted to the prevention of FAS is urgently needed.
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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 | 0.002 |
| 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".