The Birth Prevalence of PKU in Populations of European, South Asian and Sub‐Saharan African Ancestry Living in South East England
Bibliographic record
Abstract
Phenylketonuria (PKU) is an autosomal recessive inborn error of metabolism (OMIM 261600). Treatment with a low-phenylalanine diet following early ascertainment by newborn screening prevents impaired cognitive development, the major disease phenotype in PKU. The overall birth prevalence of PKU in European, Chinese and Korean populations is approximately 1/10,000. Since the human PAH locus contains PKU-causing alleles and polymorphic core haplotypes that describe and corroborate an out-of-Africa range expansion in modern human populations, it is of interest to know the prevalence of PKU in different ethnic groups with diverse geographical origin. We estimated PKU prevalence in South East England, where a sizeable proportion of the population are of Sub-Saharan African or South Asian ancestry. Over the period 1994 to 2004 167 children were diagnosed with PKU. Using birth registration and census data to derive denominators, PKU birth prevalence per 10,000 live births (95% Bayesian credible intervals) was estimated to be 1.14 (0.96-1.33) among white, 0.11 (0.02-0.37) among black, and 0.29 (0.10-0.63) among Asian ethnic groups. This suggests that PKU is up to an order of magnitude less prevalent in populations with Sub-Saharan African and South Asian ancestry that have migrated to the UK.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".