Bibliographic record
Abstract
In future studies it could be interesting to know the same outcomes assessed by this article in patients with partial and idiopathic generalized epilepsy.Unfortunately the sample size in this study does not allow this comparative analysis.In the article the authors assessed some factors associated with the lack of response to LVT and basically the authors find the profile of patients with intractable epilepsy such as surgical candidates, patients on polytherapy, history of status epilepticus and the use of concomitant AEDS.This observation was expected and it is an interesting finding of the study because these characteristics represent the profile of patients that could not only fail to LVT but also to other medications.Regarding tolerability the study shows an adequate profile.Overall 23% of patients developed side effects and 16% and of those discontinued the drug.Side effects identified in the study were the most common, having been recognized in the international literature such as drowsiness and behavior changes.The results of this study confirm previous evidence supporting the efficacy and tolerability of LVT.There is no question that LVT is well positioned as a drug for patients with partial and generalized efficacy due to several commented advantages.
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 | 0.002 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".