Successful treatment of paroxysmal tonic upgaze with low dose Gravol ®
Bibliographic record
Abstract
Background: We present a case of paroxysmal tonic upgaze (PTU) of infancy treated with a daily low dose of Gravol ® to improve symptoms. Method: Case report Results: A one year-old boy presented with episodes of sustained conjugate upgaze that persisted for 30 to 45 minutes, varied in severity, and occurred with increasing frequency over the past two months. The episodes were worse when fatigued and were relieved by sleep. Pregnancy, delivery, and development were normal. Neurological examination between episodes was normal, as were EEG, brain MRI, and blood analysis. CSF neurotransmitter analysis showed serotonin and dopamine metabolites at lower levels of normal. The patient was diagnosed with paroxysmal tonic upgaze of infancy and was treated with 12.5 mg of Gravol ® daily with complete cessation of episodes. Conclusions: Paroxysmal tonic upgaze (PTU) of infancy is a disorder seen in infants where the eyes are forcibly deviated upwards for minutes to hours at a time. PTU often resolves spontaneously over several months, however episodes are extremely debilitating. Currently, treatments with levodopa have been tried with some success. Via its anticholinergic effects, Gravol may be a novel therapeutic option for PTU, negating the need to use serotonergic medications.
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 | 0.000 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".