Non-Ergot Dopamine Agonists and the Risk of Heart Failure and Other Adverse Cardiovascular Reactions in Parkinson’s Disease
Bibliographic record
Abstract
Reports suggest possible risks of adverse cardiovascular reactions, including heart failure, associated with non-ergot dopamine agonist (DA) use in Parkinson's disease (PD). The objectives of our review were to evaluate the risk of heart failure and other adverse cardiovascular reactions in PD patients who received a non-ergot DA compared with other anti-PD pharmacological interventions, placebo, or no intervention. Studies were identified via searches of six bibliographic databases. Randomized controlled trials (RCTs) and non-randomized studies (NRS) were eligible for study inclusion. Random-effect meta-analyses were performed to estimate adverse cardiovascular reaction risks. Quality of evidence was assessed using GRADE. In total, forty-four studies (thirty-six RCTs and eight NRS) satisfied our inclusion criteria. A single RCT found no significant difference in the risk of heart failure with ropinirole compared with bromocriptine (odds ratio (OR) 0.39, 95% confidence interval (CI) 0.07 to 2.04; low certainty). Conversely, three case-control studies reported a risk of heart failure with non-ergot DA treatment. The quality of evidence for the risk of heart failure was judged as low or very low. Findings suggest that non-ergot DA use may be associated with adverse cardiovascular outcomes, including heart failure. Studies are needed to better understand cardiovascular risks associated with PD treatment.
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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".