Epidemiology of congenital anomalies of the kidney and the urinary tract: a birth registry study
Bibliographic record
Abstract
Background Congenital anomalies of the kidney and the urinary tract (CAKUT) are common birth defects. The aims of our study were to estimate the prevalence and structure of CAKUT in Murmansk County during 2006-2011 and to explore their risk factors. Methods The Murmansk County Birth Registry was the primary source of information about cases and perinatal exposures. The study included 50936 singletons in the examination of prevalence and proportional distribution of CAKUT, while the multivariate analyses of risk factors included 39322 newborns. Results The prevalence of CAKUT was 4.0 per 1000 newborns [95%CI: 3.4-4.5]. There were six cases of isolated single kidney cyst (Q61.0), which is considered as a minor anomaly by the EUROCAT and, thus, the prevalence according to EUROCAT guidelines was 3.9 (95%CI = 3.3–4.4). Congenital hydronephrosis was predominant form in the structure of CAKUT (14.2% of all cases). Multiple urinary malformation was observed in 10% of cases. Moreover, a half of all malformations were diagnosed as “other congenital anomalies of kidney”. Based on the multivariate analysis, diabetes mellitus or gestational diabetes [OR = 4.77, 95%CI: 1.16-19.65], acute infections while pregnant [OR = 1.83, 95%CI: 1.14-2.94], the use of medication during pregnancy [OR = 2.03, 95%CI: 1.44-2.82], and conception during the summer [OR = 1.75, 95%CI 1.15-2.66] were significantly associated with higher risk of CAKUT. Conclusions The overall four-fold enhancement of the occurrence of urinary malformations in Murmansk County for the 2006-2011 period showed little annual dependence. During pregnancy, use of medications, infections, pre-existing diabetes mellitus or gestational diabetes were associated with increased risk of these anomalies, as was conception during summer. The findings have direct applications in improving prenatal care in Murmansk County and establishing targets for prenatal screening and women’s consultations. Key message: Use of medications during pregnancy, diabetes mellitus or gestational diabetes, infections during the pregnancy, and conception during summer are associated with increased risk of urinary anomalies
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".