Potential protective role of ACE-inhibitors and AT1 receptor blockers against levodopa-induced dyskinesias: a retrospective case-control study
Bibliographic record
Abstract
Growing evidence has highlighted that angiotensin-converting enzyme (ACE)-inhibitors (ACEi)/AT1 receptor blockers (ARBs) may influence the complex interplay between dopamine and the renin-angiotensin system in the nigrostriatal pathway, thus affecting the development of levodopa-induced dyskinesia in Parkinson's disease (PD). In the present study, we analyzed whether the use of this class of medication was associated with a reduced occurrence of levodopa-induced dyskinesia, using electronically-stored information of idiopathic PD patients enrolled at Novara University Hospital "Maggiore della Carità". We conducted a retrospective case-control study identifying PD patients with dyskinesias (PwD; n = 47) as cases. For each PwD we selected a non-dyskinetic control (NoD), nearly perfectly matched according to sex, Unified Parkinson's Disease Rating Scale (UPDRS) part III score, and duration of antiparkinsonian treatment. Binary logistic regression was used to evaluate whether dyskinesias were associated with ACEi/ARBs use. Ninety-four PD patients were included, aged 72.18 ± 9 years, with an average disease duration of 10.20 ± 4.8 years and 9.04 ± 4.9 years of antiparkinsonian treatment. The mean UPDRS part III score was 18.87 ± 7.6 and the median HY stage was 2. In the NoD group, 25 (53.2%) were users and 22 (46.8%) non-users of ACEi/ARBs. Conversely, in the PwD group, 11 (23.4%) were users and 36 non-users (76.6%) of this drug class (Pearson chi-square = 8.824, P = 0.003). Concerning general medication, there were no other statistically significant differences between groups. After controlling for tremor dominant phenotype, levodopa equivalent daily dose, HY 3-4, and disease duration, ACEi/ARBs use was a significant predictor of a lower occurrence of dyskinesia (OR = 0.226, 95% CI: 0.080-0.636, P = 0.005). Therefore, our study suggests that ACEi/ARBs may reduce levodopa-induced dyskinesia occurrence and, thanks to good tolerability and easy management, represent a feasible choice when dealing with the treatment of hypertension in PD patients. The study was approved by the Ethics Committee of Novara University Hospital "Maggiore della Carità" (CE 65/16) on July 27, 2016.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".