Variability in clinical laboratory practice in testing for disorders of platelet function
Bibliographic record
Abstract
Disorders of platelet function are important causes of abnormal bleeding that require laboratory tests for diagnosis. Currently there are limited guidelines on how to perform clinical testing for these disorders. The goal of our study was to obtain information on how disorders of platelet function are currently evaluated in clinical laboratories. Two patterns-of-practice surveys were distributed to laboratories of the North American Specialized Coagulation Laboratory Association (NASCOLA). The information collected was analyzed to determine practices and common problems. Forty-seven NASCOLA laboratories participated and 54% completed both surveys. The majority of the laboratories that responded performed more than 50 aggregation tests per year, mainly using platelet rich plasma based methodologies. A minority performed testing for platelet secretion and dense granule abnormalities. While platelet aggregation results were reviewed in various ways, laboratories most commonly issued a combined report containing quantitative values (% aggregation and/or slope) and a qualitative interpretation. Although laboratories used similar agonists for aggregation testing, the final agonist concentrations varied widely. Several approaches were also used to obtain reference intervals. Comments offered by the participants indicated that performing, and interpreting platelet function tests were challenging for many clinical laboratories. Although common practices have evolved, there is considerable variability in the diagnostic test procedures used by clinical laboratories to evaluate disorders of platelet function. These patterns-of-practice surveys illustrate a need for guidelines and recommendations for clinical laboratories performing tests of platelet function.
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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 | 0.047 | 0.142 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".