Implementation of universal newborn bloodspot screening for sickle cell disease and other clinically significant haemoglobinopathies in England: screening results for 2005–7
Bibliographic record
Abstract
Early results from the National Health Service Sickle Cell and Thalassaemia Screening programme covering the whole of England are reported following the implementation of the national newborn blood-spot screening programme. Of the 13 laboratories performing screening, 10 chose high-performance liquid chromatography as the first screen, with isoelectric focusing as the second confirmatory test. Screening results for April 2005 to March 2007 are presented and include data from all the laboratories screening newborns in England, and almost 1.2 million infants. The screen-positive results show a national birth prevalence of almost 1 in 2000. The birth prevalence in London is five times that of most of the rest of the country. Over 17,000 carriers have been identified. Approximately seven per 1000 samples are reported as post-transfusion with wide ethnic category variation. Given the prevalence of the conditions, and coverage by ethnicity, 3-4 screen-positive cases could be missed each year. National implementation of newborn screening in England has increased the number of children identified with sickle cell disease, in many areas almost doubling the workload. Underascertainment of the condition has allowed a downplaying of the scale of need. It may also have contributed to infant mortality rates in urban areas as babies died without a diagnosis or treatment. The value of a co-ordinated national approach to policy development and implementation is emphasised by the English experience. The programme provides a model for Europe as well as other countries with significant minority populations, such as Canada. Potentially it also offers important lessons for Africa where the World Health Organization is supporting the introduction of newborn screening.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".