Consensus guideline for the diagnosis and treatment of tetrahydrobiopterin (BH4) deficiencies
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
Abstract Background Tetrahydrobiopterin (BH 4 ) deficiencies comprise a group of six rare neurometabolic disorders characterized by insufficient synthesis of the monoamine neurotransmitters dopamine and serotonin due to a disturbance of BH 4 biosynthesis or recycling. Hyperphenylalaninemia (HPA) is the first diagnostic hallmark for most BH 4 deficiencies, apart from autosomal dominant guanosine triphosphate cyclohydrolase I deficiency and sepiapterin reductase deficiency. Early supplementation of neurotransmitter precursors and where appropriate, treatment of HPA results in significant improvement of motor and cognitive function. Management approaches differ across the world and therefore these guidelines have been developed aiming to harmonize and optimize patient care. Representatives of the International Working Group on Neurotransmitter related Disorders (iNTD) developed the guidelines according to the SIGN (Scottish Intercollegiate Guidelines Network) methodology by evaluating all available evidence for the diagnosis and treatment of BH 4 deficiencies. Conclusion Although the total body of evidence in the literature was mainly rated as low or very low, these consensus guidelines will help to harmonize clinical practice and to standardize and improve care for BH 4 deficient patients.
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) | 0.001 | 0.001 |
| 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