Assessment of intellectual impairment, health‐related quality of life, and behavioral phenotype in patients with neurotransmitter related disorders: Data from the <scp>iNTD</scp> registry
Bibliographic record
Abstract
Abstract Inherited disorders of neurotransmitter metabolism are a group of rare diseases, which are caused by impaired synthesis, transport, or degradation of neurotransmitters or cofactors and result in various degrees of delayed or impaired psychomotor development. To assess the effect of neurotransmitter deficiencies on intelligence, quality of life, and behavior, the data of 148 patients in the registry of the International Working Group on Neurotransmitter Related Disorders (iNTD) was evaluated using results from standardized age‐adjusted tests and questionnaires. Patients with a primary disorder of monoamine metabolism had lower IQ scores (mean IQ 58, range 40‐100) within the range of cognitive impairment (<70) compared to patients with a BH 4 deficiency (mean IQ 84, range 40‐129). Short attention span and distractibility were most frequently mentioned by parents, while patients reported most frequently anxiety and distractibility when asked for behavioral traits. In individuals with succinic semialdehyde dehydrogenase deficiency, self‐stimulatory behaviors were commonly reported by parents, whereas in patients with dopamine transporter deficiency, DNAJC12 deficiency, and monoamine oxidase A deficiency, self‐injurious or mutilating behaviors have commonly been observed. Phobic fears were increased in patients with 6‐pyruvoyltetrahydropterin synthase deficiency, while individuals with sepiapterin reductase deficiency frequently experienced communication and sleep difficulties. Patients with BH 4 deficiencies achieved significantly higher quality of life as compared to other groups. This analysis of the iNTD registry data highlights: (a) difference in IQ and subdomains of quality of life between BH 4 deficiencies and primary neurotransmitter‐related disorders and (b) previously underreported behavioral traits.
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 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 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".