Bacterial contamination of blood products in Africa
Bibliographic record
Abstract
BACKGROUND: Bacterial contamination of blood components (notably platelets) remains a leading infectious risk to the blood supply. There has been extensive research in high-income countries to characterize the risk of bacterial contamination along with adoption of strategies to mitigate that risk. By contrast, related data in Africa are lacking. STUDY DESIGN AND METHODS: An electronic survey was distributed to members of African Society of Blood Transfusion to assess existing or planned measures at African blood centers and hospitals to mitigate bacterial contamination of blood products. A literature review of studies pertaining to related transfusion-associated risk in Africa was conducted to complement the findings. RESULTS: Forty-five responses were received, representing 16 African countries. All respondents were urban, either in blood centers (n = 36) or hospital-based transfusion services (n = 9). Reported measures included skin disinfection (n = 41 [91.1%]); diversion pouches (n = 14 [31.1%]); bacterial culture (n = 9 [20%]); pathogen reduction (PR) (n = 3 [6.7%]); and point-of-release testing (PoRT) (n = 2 [4.4%]). Measures being considered for implementation included: skin disinfection (n = 2 [4.4%]); diversion pouches (n = 2 [4.4%]); bacterial culture n = 14 (31.1%); PR (n = 11 [24.4%]); and PoRT (n = 4 [8.9%]). Of the 38 respondents who reported collection of platelets, 14 (36.8%) and 8 (21.1%) reported using diversion pouches and bacterial culture, respectively. The literature review identified 36 studies on the epidemiology of bacterial contamination and septic transfusion reactions in Africa; rates of contamination ranged from 0% to 17.9%. CONCLUSIONS: The findings suggest that prevention of bacterial contamination of blood components and transfusion-associated sepsis in Africa remains neglected. Regional preventive measures have not been widely adopted.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".