Effect of microcollection tube fill volume on common acute care tests
Bibliographic record
Abstract
BACKGROUND: Microcollection tubes are frequently used in pediatric phlebotomy. We performed a pilot study to determine what clinical biochemistry and hematology tests can be reported on different microcollection tube fill volumes. METHODS: Blood was collected from 11 volunteers into Becton Dickinson (BD) Vacutainers® and microcollection tubes (BD Microtainers® and the Sarstedt Microvette® 300 FH) at different fill volumes (Filled: top line; Intermediate: second line; Short: third line. If there was no second or third line, 200 µL was used for short fills) for 36 clinical biochemistry tests and the complete blood count (CBC) with differential (23 components). At each fill volume, tests were strong candidates to report if they did not have statistically significant biases compared to results in Vacutainers®. Potential candidates had statistically significant biases that were small (median absolute bias < 25 % of total allowable error and less than desirable bias from biological variation). Tests were not candidates if biases were significant and large (median absolute bias ≥ 25 % of TEa or ≥ desirable bias). Biases that increased or decreased across concentration ranges invalidated reporting candidacy. RESULTS: Twenty four clinical biochemistry tests were strong or potential candidates to report on all fill volumes, 7 were strong or potential candidates to report on some fill volumes and 5 were not candidates to report on any fill volumes. Seventeen CBC components were strong or potential candidates to report on all fill volumes, 2 were strong or potential candidates to report on some fill volumes and 4 were not candidates to report on any fill volumes. CONCLUSIONS: While most tests were valid to report on different fill volumes, some were not. We encourage laboratories to perform their own studies on fill volumes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".