Comparison of canine core bone marrow biopsies from multiple sites using different techniques and needles
Bibliographic record
Abstract
BACKGROUND: Commonly used 11 or 13ga needles are relatively large for collection of bone marrow (BM) biopsies from small dogs. OBJECTIVES: The aims of this study were to assess ease of BM collection and quality of specimens obtained from small dogs using 13 and 15ga needles and to determine if specimen encasement would improve quality. METHODS: Humeral and iliac biopsies obtained from 17 Beagle dogs with a 15ga needle and a power driver were compared with humeral biopsies obtained with a 13ga Jamshidi needle. Ease of collection (scored as 1 [very difficult] to 5 [very easy] for 3 components of collection with scores summed), section quality (scored as 1 [poor] to 5 [good]), and lesions at collection sites were scored. Quality of additional humeral biopsies obtained with a 15ga needle and wrapped in tissue paper prior to fixation was assessed. RESULTS: Use of a 15ga needle to obtain a humeral BM biopsy was significantly easier (mean score ± SD = 13.6 ± 1.7) than obtaining humeral BM using a 13ga needle (11.4 ± 1.6; P < .001) or obtaining iliac BM using a 15ga needle (10.9 ± 2.0, P < .001). Quality of humeral biopsies obtained with a 13ga needle (3.9 ± 1.2) was better than for biopsies of the humerus (1.9 ± 1.3, P < .001) or ilium (1.4 ± 0.6, P < .001) using a 15ga needle. Only sites sampled with a 13ga needle were identifiable grossly after the procedure. In most biopsies, cell density and cellularity were lower when a 15ga needle was used. Paper-wrapping of biopsies did not improve quality. CONCLUSIONS: In small dogs, collection of humeral BM biopsies using a 15g needle is feasible and more easily accomplished than collection using a 13ga needle. Hematopoiesis may be underestimated in specimens collected using the smaller needle.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".