Birth prevalence of cryptorchidism and hypospadias in northern England, 1993-2000
Bibliographic record
Abstract
AIM: There is much debate as to whether the prevalence rates of cryptorchidism and hypospadias are increasing. To address this issue we investigated the birth prevalence of cryptorchidism and hypospadias in the northern region of England during the period 1993-2000. METHODS: Cases of cryptorchidism and hypospadias were identified from northern region hospital episodes statistics (HES). Trends in birth prevalence, based on the number of male live births, were assessed using linear regression. RESULTS: Prevalence was 7.6 per 1000 male live births for cryptorchidism and 3.1 per 1000 male live births for hypospadias. The orchidopexy rates for 0-4 year olds and 5-14 year olds were 1.8 and 0.8 per 1000 male population, respectively. The rates for hypospadias repair for 0-4 year olds and 5-14 year olds were 0.6 and 0.1 per 1000 male population, respectively. There was a statistically significant decreasing temporal trend for the corrective procedure in cryptorchidism of 0.1 per 1000 male population aged under 5 years per annum (95% confidence interval: -0.01 to -0.05, p<0.001), but no temporal change for the corrective procedure in hypospadias (p = 0.60). CONCLUSION: HES data were of high quality for the study period. There was no significant change in the prevalence of surgically corrected hypospadias. However, there was an apparent decline in the prevalence of surgically corrected cryptorchidism that may reflect a decrease in the prevalence of the condition or may be due to a decrease in the rate of surgical intervention.
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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".