The Evidence for Pharmacist Care in Outpatients with Heart Failure: A Systematic Review and Meta-Analysis
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Bibliographic record
Abstract
Abstract Aims Patients with heart failure (HF) have poor outcomes, including poor quality of life, and high morbidity and mortality. In addition, they have a high medication burden due to the multiple drug therapies now recommended by guidelines. Previous reviews, including studies in hospital settings, provided evidence that pharmacist care improves outcomes in patients with HF. Because most HF is managed outside of hospitals, we aimed to synthesize the evidence for pharmacist care in outpatients with HF. Methods and results We conducted a systematic literature search in PubMed of randomized controlled trials (RCTs) and integrated the evidence on patient outcomes in a meta-analysis. We found 24 RCTs performed in 10 countries, including 8029 patients. The data revealed consistent improvements in medication adherence (independent of the measuring instrument) and knowledge, physical function, and disease and medication management. Sixteen RCTs were included in meta-analyses. Differences in all-cause mortality (odds ratio (OR) = 0.97 [95% CI, 0.84–1.12], Q-statistic, P = 0.49, I2 = 0%), all-cause hospitalizations (OR = 0.86 [0.73–1.03], Q-statistic, P = 0.01, I2 = 45.5%), and HF hospitalizations (OR = 0.89 [0.77–1.02], Q-statistic, P = 0.11, I2 = 0%) were not statistically significant. We also observed an improvement in the standardized mean difference for generic quality of life of 0.75 ([0.49–1.01], P < 0.01), with no indication of heterogeneity (Q-statistic, P = 0.64; I2 = 0%). Conclusions Results indicate that pharmacist care improves medication adherence and knowledge, symptom control, and some measures of quality of life in outpatients with HF. Given the increasing complexity of guideline-directed medical therapy, pharmacists' unique focus on medication management, titration, adherence, and patient teaching should be considered part of the management strategy for these vulnerable patients.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.011 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it