Blood loss from laboratory testing, anemia, and red blood cell transfusion in the intensive care unit: a retrospective study
Bibliographic record
Abstract
BACKGROUND: Anemia is common in critically ill patients and associated with adverse outcomes. Phlebotomy associated with laboratory testing is a potentially modifiable contributor. This study aims to 1) characterize the blood volume taken for laboratory testing, and 2) explore the effect of blood loss on red blood cell (RBC) transfusion and anemia in adult intensive care unit (ICU) patients. METHODS: Using a transfusion research database, we retrospectively reviewed consecutively admitted patients to four medical-surgical ICUs in Hamilton, Ontario, Canada. The primary outcome was estimated blood loss for laboratory testing during ICU admission. Secondary outcomes were hemoglobin (Hb) of 90 g/L or less and RBC transfusion. RESULTS: Among the 7273 patients included, the median blood volume per patient taken for laboratory testing during their ICU stay was 213 mL (interquartile range [IQR], 133-382 mL). On ICU admission, median Hb was 97 g/L (IQR, 82-116 g/L). An Hb of 90 g/L or less occurred in 67.0% of patients during their ICU stay. Median Hb on ICU discharge adjusted for RBC transfusion was 84 g/L (IQR, 58-105 g/L). RBC transfusion was administered to 47.5% of patients, who received a median of 3 units (IQR, 2-7 units). Cumulative blood loss due to laboratory testing from Day 2 to Day 7 of ICU admission was independently associated with RBC transfusion (hazard ratio, 2.28 for each 150-mL increment; 95% confidence interval, 2.02-2.59). CONCLUSIONS: Blood loss for laboratory testing is substantial in ICU patients and significantly associated with RBC transfusion. Strategies to reduce blood loss from laboratory testing represents an area for further investigation.
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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) | 0.001 | 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 | 0.001 |
| 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".