Clinical efficacy and changes in regional cerebral perfusion after nicergoline treatment in vascular dementia: a retrospective study in South Korea
Bibliographic record
Abstract
Background: Nicergoline is an ergoline derivative and vessel dilator that is used to treat cognitive deficits in cerebrovascular disease and various forms of dementia including vascular dementia (VaD).Although therapeutic effects of nicergoline have been established, little is known about its effects on cerebral perfusion in patients with VaD.We conducted this longitudinal study to evaluate the role of nicergoline in regional cerebral blood flow (rCBF) and cognitive function of VaD patients using technetium-99m ethyl cysteinate dimer single photon emission computed tomography (SPECT) and neuropsychological tests.Methods: Eleven VaD patients who received nicergoline therapy and 11 VaD patients who did not receive nicergoline therapy underwent SPECT and clinical neuropsychological tests at baseline and 6-month follow up visits.Patients treated with nicergoline received 30 mg twice per day.Clinical and cognitive functioning was assessed using the mini-mental state examination, clinical dementia rating with sum of boxes, Montreal cognitive assessment and neuropsychiatric inventory.Results: Nicergoline treatment showed improvement in the cognitive function via results of neuropsychological tests and neuropsychiatric symptoms, which were not statistically significant.In regard with change in rCBF, there also was no statistical significance between 2 groups.Conclusions: Although there is no significant improvement in cognitive function, numerical improvements were shown in cognitive tests other than rCBF.Larger, longitudinal studies are needed to further clarify the therapeutic effects of nicergoline and determine the utility of nicergoline for treatment of VaD.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".