Prevalence of birth defects in an Arctic Russian setting from 1973 to 2011: a register-based study
Bibliographic record
Abstract
BACKGROUND: Birth defects (BD) constitute an important public health issue as they are the main cause of infant death. Their prevalence in Europe for 2008-2012 was 25.6 per 1000 newborns. To date, there are no population-based studies for the Russian Federation. The aim of the present study is to estimate the prevalence of BD, its forms, and changes over time in the Russian Arctic city of Monchegorsk (Murmansk County) for the period 1973-2011. METHODS: The Murmansk County Birth Register and the Kola Birth Register were the primary sources of information, covering 30448 pregnancy outcomes in Monchegorsk (Murmansk County, Russia) during the study period. RESULTS: The total perinatal prevalence of BD was 36.1/1000 live births (LB) and stillborn (SB) (95% CI = 34.0-38.2). After exclusions of minor malformations according to the European Surveillance of Congenital Anomalies guidelines, it decreased to 26.5/1000 LB plus SB (95% CI = 24.6-28.3). The perinatal prevalence of BD that are obligatory to report in Russia was 7.3/1000 LB plus SB (95% CI = 6.4-8.3). There was a significant positive time-trend in total perinatal prevalence of birth defects across the study period (p < 0.001 for trend). Prevalence of all BD increased from 23.5/1000 to 46.3/1000 (LB plus SB), while that excluding minor defects rose from 17.7/1000 to 35.7/1000 (LB plus SB). The most prevalent group of defects was malformations of the musculoskeletal system, which represented 35.4% of all BD. The most prominent increase was observed for the urinary system, rising from 0.2/1000 to 19.1/1000 (LB plus SB). CONCLUSIONS: The observed perinatal prevalence of BD in Monchegorsk increased two-fold during the 38-year study period. Further investigations to identify the underlying bases for the observed progressive growth in BD are recommended.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".