A systematic review and meta-analysis: the effect of pharmacist-led antibiotic stewardship programs on antibiotic consumption and rational use
Bibliographic record
Abstract
Irrational use of antibiotics and antibiotic resistance are one of the major problems encountered in healthcare services. Antibiotic stewardship programs (ASPs) have been one of the most successful attempts in hospitals to control antibiotic resistance. Pharmacists are the core health professionals in ASPs. This study aimed to examine the effect of clinical pharmacist-led ASPs on antibiotic consumption with meta-analysis. ScienceDirect, PubMed, MEDLINE and Cochrane databases were searched for relevant studies. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guideline was used to identify studies for the review. Methodological quality was assessed using Newcastle-Ottawa scale (NOS) and National Heart, Lung and Blood Institute (NHLBI) pre-post comparison studies quality tool. The R (version 4.0.3.) and metafor packages (version 2.1-0) were used for a random-effects meta- analysis. After pharmacist intervention, the pooled rational use of antibiotics was determined as 0.28 (28% improvement, I2=98.26; 95% CI 0.15-0.41). The pooled duration of therapy data was determined as 0.41 (41% reduction, I2=96.30%; 95% CI 0.54-0.29) in favor of the group with the pharmacist’s intervention. As a result of this study, it was determined that clinical pharmacists took part in the evaluation of the patient, regulation of the treatment, follow-up of the patient after treatment, and education in ASPs. These findings can contribute to improving the role of the pharmacist in ASPs and rational antibiotic use, thereby controlling antibiotic resistance.
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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 | 0.027 | 0.056 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.061 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".