Universal Newborn Screening for Hb H Disease in California
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Newborn screening is an accepted public health measure to ensure that appropriate health care is provided in a timely manner to infants with hereditary/metabolic disorders. Alpha-thalassemia is a common hemoglobin (Hb) disorder, and causes Hb H (beta4) disease, and usually fatal homozygous alpha(0)-thalassemia, also known as Hb Bart's (gamma4) hydrops fetalis syndrome. In 1996, the State of California began to investigate the feasibility of universal newborn screening for Hb H disease. Initial screening was done on blood samples obtained by heel pricks from newborns, and stored as dried blood spots on filter paper. Hb Bart's levels were measured as fast-moving Hb by automated high-performance liquid chromatography (HPLC) identical to that currently used in newborn screening for sickle cell disease. Subsequent confirmation of Hb H disease was done by DNA-based diagnostics for alpha-globin genotyping. A criterion of 25% or more Hb Bart's as determined by HPLC detects most, if not all cases of Hb H disease, and few cases of alpha-thalassemia trait. From January, 1998, through June, 2000, 89 newborns were found to have Hb H disease. The overall prevalence for Hb H disease among all newborns in California is approximately 1 per 15,000. Implementation of this program to existing newborn hemoglobinopathy screening in populations with significant proportions of southeast Asians is recommended. The correct diagnosis would allow affected infants to be properly cared for, and would also raise awareness for the prevention of homozygous alpha(0)-thalassemia or Hb Bart's hydrops fetalis syndrome.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it