Content and impact of pharmacy services for patients with Parkinson's disease
Bibliographic record
Abstract
BACKGROUND: Medicines optimisation is important for the management of Parkinson's disease (PD). As many patients with PD have other long-term conditions, treatment is complex and risk of adverse events for these patients is high. OBJECTIVE: To explore the role of pharmacists and impact of pharmacy interventions for PD patients. METHODS: We comprehensively searched PubMed, Embase, the Cochrane Library and Chinese databases Sinomed, China National Knowledge Infrastructure to identify studies reporting pharmacist interventions and pharmacy services for PD patients using a predefined search strategy. The search period was from inception to March 2019. We also manually searched the reference list of included studies and ClinicalTrials.gov. We conducted meta-analyses to synthesize the evidence quantitatively. RESULTS: A total of 1607 studies were identified by applying the search criteria. After screening, 19 cross-sectional and case-controlled studies with 1458 PD patients from 9 countries were included. Pharmacist interventions for PD patients most commonly related to adverse drug reactions (ADRs) (13 studies), adherence assessment (12 studies), medication review (12 studies), identification of drug interactions (11 studies), monitoring response to medication therapy (11 studies), identification of inappropriate medication (11 studies), and patient education (10 studies). Most pharmacy services were provided in outpatient settings (13 studies). Reported impact measures included adherence (8 studies), quality of life (7 studies), and identification of drug-related problems (6 studies) such as ADRs (393 times out of 1760 times, 22.33%, 6 studies), inappropriate drug choice (349 times, 19.83%, 6 studies), inappropriate dosage (335 times, 19.03%, 6 studies), inappropriate drug use (257 times, 14.60%, 3 studies) and drug-drug interactions (146 times, 8.3%, 4 studies). Pooled results from 3 studies indicated no statistically significant impact of pharmacy services on all subscales of PD Questionnaire-39. CONCLUSION: ADRs were the most widely reported drug-related problems for PD patients; pharmacy services may have a role to play in medication adherence but were not found to impact on quality of life.
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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 | 0.005 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".