A positive blood culture is associated with a lower haemoglobin increment in hospitalized patients after red blood cell transfusion
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Abundant clinical evidence supports the safety of red blood cell (RBC) concentrates for transfusion irrespective of storage age, but still, less is known about how recipient characteristics may affect post-transfusion RBC recovery and function. Septic patients are frequently transfused. We hypothesized that the recipient environment in patients with septicaemia would blunt the increase in post-transfusion blood haemoglobin (Hb). The main objective was to compare the post-transfusion Hb increment in hospitalized patients with or without a positive blood culture. MATERIALS AND METHODS: A retrospective cohort study using data from the Transfusion Research, Utilization, Surveillance, and Tracking database (TRUST) was performed. All adult non-trauma in-patients transfused between 2010 and 2017 with ≥1 RBC unit, and for whom both pre- and post-transfusion complete blood count and pre-transfusion blood culture data were available were included. A general linear model with binary blood culture positivity was fit for continuous Hb increment after transfusion and was adjusted for patient demographic parameters and transfusion-related covariates. RESULTS: Among 210,263 admitted patients, 6252 were transfused: 596 had positive cultures, and 5656 had negative blood cultures. A modelled Hb deficit of 1.50 g/L in blood culture-positive patients was found. All covariates had a significant effect on Hb increment, except for the age of the transfused RBC. CONCLUSION: Recipient blood culture positivity was associated with a statistically significant but modestly lower post-transfusion Hb increment in hospitalized patients. In isolation, the effect is unlikely to be clinically significant, but it could become so in combination with other recipient characteristics.
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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) | 0.000 | 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) | 0.003 | 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 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".