A Systematic Review and Meta-Analysis of the Risk of Microbial Contamination of Aseptically Prepared Doses in Different Environments
Bibliographic record
Abstract
PURPOSE: To review microbial contamination rates about preparation of individual and batch doses using aseptic techniques within pharmaceutical (controlled) and clinical (ward and theatre) environments. METHODS: Systematic review, involving amalgamation of data using a random effect model and metaanalysis. RESULTS: A total of 19 studies from 17 reports (7277 doses), mostly single arm studies, were identified for analysis. The overall contamination rates for doses prepared in clinical environments were found to be 5.0% (95% CI; 1.8%, 13.1%, n = 8 studies) for individual doses and 2.0% (95% CI; 0.3%, 13.1%; n = 5) for doses prepared as part of a batch. Rates for doses prepared in pharmaceutical environments were found to be 1.9% (95% CI; 0.8%, 4.2%; n = 5) for individual doses and 0.0% (95% CI; 0.0%, 0.8%; n= 1) for doses prepared as part of a batch. The results indicate greater overall contamination rates of doses prepared in clinical than pharmaceutical environments, in those prepared individually than in batch preparation, and in those in which additions rather than no additions were made. Significant differences were only found between pharmaceutical and clinical environments for batch doses, and between batch and individual doses prepared in a pharmaceutical environment. The studies differed substantially in sample size, interventions and comparison conditions, especially in the clinical setting. The quality of the data was judged to be low. CONCLUSION: Contamination rates in clinical and pharmaceutical environments were commonly found to be unacceptably high. Intuitive recommendations for reducing contamination rates by carrying out the procedures in a pharmaceutical environment using batch doses are supported by an evidence base that needs to be strengthened further.
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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 | 0.016 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.036 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".