Small‐volume blood sample collection tubes in adult <scp>intensive care units</scp>: A rapid practice guideline
Bibliographic record
Abstract
BACKGROUND: This Intensive Care Medicine Rapid Practice Guideline (ICM-RPG) provides an evidence-based recommendation to address the question: in adult patients in intensive care units (ICUs), should we use small-volume or conventional blood collection tubes? METHODS: We included 23 panelists in 8 countries and assessed and managed financial and intellectual conflicts of interest. Methodological support was provided by the Guidelines in Intensive Care, Development, and Evaluation (GUIDE) group. We conducted a systematic review, including evidence from observational and randomized studies. Using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach, we evaluated the certainty of evidence and developed recommendations using the Evidence-to-Decision framework. RESULTS: We identified 8 studies (1 cluster and 2 patient-level randomized trials; 5 observational studies) comparing small-volume to conventional tubes. We had high certainty evidence that small-volume tubes reduce daily and cumulative blood sampling volume; and moderate certainty evidence that they reduce the risk of transfusion and mean number of red blood cell units transfused, but these estimates were limited by imprecision. We had high certainty that small-volume tubes have a similar rate of specimens with insufficient quantity. The panel considered that the desirable effects of small-volume tubes outweigh the undesirable effects, are less wasteful of resources, and are feasible, as demonstrated by successful implementation across multiple countries, although there are upfront implementation costs to validate small-volume tubes on laboratory instrumentation. CONCLUSION: This ICM-RPG panel made a strong recommendation for the use of small-volume sample collection tubes in adult ICUs based on overall moderate certainty evidence.
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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 | 0.080 | 0.196 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.010 | 0.004 |
| Research integrity | 0.011 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".