Effect on lipid, complete blood count and blood proteins of a standardized preparation for drawing blood: a randomized controlled trial.
Bibliographic record
Abstract
OBJECTIVE: To compare a standardized recommended procedure for drawing blood to measure blood lipid and lipoprotein levels with the procedure commonly used in clinical practice. The aim was to see if hemoconcentration and spuriously elevated lipid levels could be avoided. DESIGN: An open randomized crossover clinical trial. SETTING: The University of Calgary. PATIENTS: Twenty-five patients with dyslipidemia. INTERVENTIONS: Blood drawing using a standardized procedure in which the patient remained seated for 5 minutes before blood collection and tourniquet use was minimized or avoided. MAIN OUTCOME MEASURES: Differences in lipid levels between the usual clinical procedure and the recommended procedure for drawing blood. RESULTS: Prior to drawing blood, laboratories have sat patients for an average of 1.4 minutes (95% CI, 0.9 to 1.9) and used a tourniquet in every patient. In the standardized procedure, patients rested for an average of 5.6 minutes (95% CI 5.0 to 6.2), and a tourniquet was used briefly in only 3 of 23 patients. There were no differences in lipid and lipoprotein values and no clinically significant difference in hemoglobin or albumin levels or in the calculation of hemoconcentration. CONCLUSIONS: Efforts to rest patients and avoid tourniquet use when drawing blood for assessment of lipid levels are unlikely to be useful.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".