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
OBJECTIVES: The aim of this study was to review our "real-world" experience with the vesicular monoamine transporter 2 (VMAT2) inhibitors tetrabenazine (TBZ), deutetrabenazine (DTBZ), and valbenazine (VBZ) for treatment of hyperkinetic movement disorders. Access and adherence to VMAT2 inhibitors may be limited by insurance and regulatory issues, inexperience with their use by the prescribing physician, lack of efficacy, or side effects. METHODS: We performed a retrospective chart review, supplemented with a questionnaire, of all our patients treated with a VMAT2 inhibitor between January 1, 2017, and August 30, 2018. RESULTS: We identified 135 patients (57.8% male) and 178 prescriptions for VMAT2 inhibitors (TBZ, n = 45 [25.3%]; DTBZ, n = 104 [58.4%]; VBZ, n = 29 [16.3%]). Tourette syndrome/tics was the most common diagnosis (n = 67 [49.6%]) for which VMAT2 inhibitors were prescribed. The VMAT2 inhibitor mean treatment durations (range; SD) and daily dosages (range; SD) were as follows: TBZ (n = 31), 5.1 months (1-19; 3.9) at 48.8 mg (12.5-112.5; 29.6); DTBZ (n = 51), 8.0 months (0.25-16.5; 4.4) at 34.4 mg (6-96; 20.7); and VBZ (n = 20), 6.0 months (0.1-16; 5.6) at 64 mg (40-160; 35.3). The VMAT2 inhibitors effectively controlled hyperkinetic movement disorders as measured by a 1- to 4-point Likert scale (1 = normal or mildly ill, 4 = severely ill) comparing illness severity before starting and while on treatment (score of 1 in 13.0%-26.7% vs 60.9%-71.9% of patients). Side effects were mild and improved or resolved following dose reduction, drug cessation, or addition of adjunctive medications. CONCLUSIONS: The VMAT2 inhibitors are effective and safe in a range of hyperkinetic movement disorders but are not readily accessible by patients in the United States for indications not approved by the Food and Drug Administration.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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