Acute Transfusion Reactions at a National Referral Hospital in Uganda: A Prospective Study
Bibliographic record
Abstract
Background Very little has been published about acute transfusion reactions (ATRs) in developing countries. This study was undertaken to determine the incidence, type, imputability, severity, and possible associated factors of ATRs observed in a university-affiliated hospital in Uganda. Study Design and Methods We prospectively followed the transfusion of blood units issued over a 7-week period from the hospital blood bank during regular working hours to nonbleeding patients. For each transfusion, we recorded the patient's status before, during, at the end of, and 4 hours after transfusion. Three physicians independently reviewed all reports of suspected ATRs and related hospital charts. Using predefined criteria, the presence, type, imputability, and severity of ATRs were adjudicated by consensus of two of three physicians. Factors potentially associated with ATRs were analyzed for statistical significance. Results A total of 507 transfusions were analyzed. Fifty-three acute transfusion events were recorded and 49 of 53 or 9.6% of the 507 transfusions were confirmed to be ATRs by physician consensus: 24 febrile, seven allergic, five hypertensive, three hypotensive, three transfusion-associated circulatory overload, two acute hemolytic, and five others. Imputability of ATRs was definite, probable, or possible in 45 of 49 ATRs (92% of ATRs or 8.9% of transfusions) and judged to be severe in nine of 45. No significant associated factors were identified. Conclusions Our findings suggest that ATRs may occur more commonly in resource-limited settings than in high-income countries. Although some reactions are unavoidable, improved surveillance of transfusions and implementation of transfusion guidelines could improve the safety of transfusions in these settings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".