Bone marrow aspirate collection and preparation – A comparison of three methods
Bibliographic record
Abstract
PURPOSE: Preparing bone marrow smears using non-anticoagulated bone marrow aspirate is a traditional practice but many laboratories now use anticoagulated aspirate samples in K-EDTA. There are no published studies comparing the effectiveness of these two methods. This report compares the readability of slides, prepared using non-anticoagulated and anticoagulated methods, from three laboratories in Hamilton Ontario. METHODS: A blinded set of 129 aspirate slides prepared using anticoagulated and non-anticoagulated methodologies (using K-EDTA) was reviewed by three reviewers. Slides were classified as unreadable if two of the three observers rejected them based on a standardized survey. RESULTS: The proportion of slides classed as unreadable varied widely (5.0% to 46.9%) depending on collection and slide preparation methods. Degree of coagulation did not affect readability. CONCLUSION: A measurable advantage to using non-anticoagulated bone marrow was not demonstrated. Immediate anticoagulation of bone marrow samples, with laboratory personnel at the bedside to assess sample quality, followed by slide preparation in the laboratory provided the best results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".