Microbiological environmental contamination in the blood supply chain: An international survey by the bacterial subgroup of the <scp>ISBT Transfusion‐Transmitted Infectious Diseases Working Party</scp>
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Blood transfusion centres ensure the quality and safety of transfusable blood components. However, septic transfusion reactions involving environmental contaminants occur. An international survey issued by the ISBT Transfusion-Transmitted Infectious Diseases Working Party (ISBT-TTID-WP) Bacterial Subgroup aimed to collect information regarding microbiological environmental monitoring from transfusion services. MATERIALS AND METHODS: A Form survey (English and Spanish) with 35 questions was sent to ISBT-TTID-WP members. The survey had four sections: (1) respondent personal information, (2) cleaning/disinfection practices during blood component manufacturing, (3) cleaning/disinfection practices during blood component storage and (4) blood component storage bag integrity. Respondents completed the survey electronically, and data were comparatively analysed using Microsoft Excel. RESULTS: There were 49 responses from 20 countries. Five of 49 sites manufacture blood components in a cleanroom, and most use personal protective equipment, although the type varied between sites. Approximately 40% of sites perform environmental monitoring during blood component production, with seven sites providing details about frequency and methods. Most (~94%) centres have procedures for cleaning/disinfection of processing and storage facilities with varying responses regarding areas, frequency and methods. Inconsistency was reported regarding the orientation of platelet component incubation (portrait vs. landscape). Over 93% of sites assess storage bag integrity and report damage to manufacturers, and 49% of centres report septic transfusion reactions potentially linked to damaged storage containers. CONCLUSION: Data from this survey highlight the need for consensual guidelines for transfusion services regarding cleaning and disinfection practices. Environmental monitoring could be adopted to minimize the risk of blood component contamination for transfusion patient safety.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".