The association of fever with transfusion‐associated circulatory overload
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Fever is described in transfusion-associated circulatory overload (TACO), reflecting either comprehensive haemovigilance or an inflammatory pathobiology (such as congestion-associated atheroma disruptions). METHODS: Hospital haemovigilance data (1/1/2010-31/12/2012) were reviewed for TACO cases (frequency and mode of referral). TACO with or without fever (TACO+F/-F) was examined for its association with patient age (as a surrogate for atheroma burden) and product age (as a surrogate for storage-related pyrogens). Fever in allergic transfusion reactions was also compared. RESULTS: Of 972 reactions, 107 suspected cases of TACO (11%) were seen. TACO+F vs. TACO-F occurred in 42·1 vs. 57·9%, respectively. TACO+F cases were discovered in referrals to investigate either a fever (in 47·1%) or dyspnoea (in 52·9%). Among TACO+F cases, 24·4% had already been febrile, whereas 75·6% exhibited a new reaction-associated fever. After excluding preexisting fevers, TACO+F occurred in 31·8% of TACO, compared with 8·2% of allergic reactions with fever, for an odds ratio of 5·2 (2·9-9·4 [95% CI]), P < 0·001. TACO+F/TACO-F showed no difference in median host age (69 vs. 64 years, P = 0·3), RBC age (22 days +F/-F, P = 0·9) or severity. CONCLUSION: Transfusion-associated circulatory overload disproportionately exhibits fever compared with allergic reactions. However, TACO+F did not associate with patient or product age, nor reflect severity. To better understand TACO+F, the fever-congestion sequence merits attention. Further study is needed to see whether TACO+F occurs as reproducibly elsewhere, and in association with atherosclerosis in a better characterized cohort.
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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) | 0.000 | 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 it