Leading digit bias in hemoglobin thresholds for red cell transfusion
Bibliographic record
Abstract
BACKGROUND: Leading digit bias is a heuristic whereby humans overemphasize the left-most digit when evaluating numbers (e.g., 9.99 vs. 10.00). The bias might affect the interpretation of hemoglobin results and influence red cell transfusion in hospitalized patients. STUDY DESIGN AND METHODS: Adults who received a red cell transfusion while registered at the University Health Network (Toronto, Canada) between January 1, 2016 and January 1, 2022 (n = 6 years) were included. The primary analysis excluded apheresis, red cell disorders, radiology suites, and operating rooms. The primary comparison was a regression discontinuity analysis of transfusion occurrence above and below the hemoglobin threshold of 79 g/L (local units). Additional analyses tested other leading digit and control thresholds (71, 81, and 91 g/L). Secondary analyses explored temporal covariates and clinical subgroups. RESULTS: A total of 211,872 red cell transfusions were identified over the study period (median pre-transfusion hemoglobin 76 g/L; interquartile range = 69-92 g/L), with 107,790 inpatient transfusions in the primary analysis. The 79 g/L threshold showed 815 fewer red cell units above the threshold (95% confidence interval [CI]: -1215 to -415). The 69 g/L threshold showed 2813 fewer transfused units (95% CI: -4407 to -1220), and 89 g/L showed 40 fewer units (95% CI: -408 to 328). The effect was accentuated during daytime, weekday, and May-June months, persisted in analyses including all transfusions, and was absent at control thresholds. CONCLUSION: Leading digit bias might have a modest influence on the decision to transfuse red cells. The findings may inform practice guidelines and quasi-experimental study design in transfusion research.
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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) | 0.000 | 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".