Platelet Aggregation Assays Do Not Reliably Diagnose Platelet Delta Granule Storage Pool Deficiency
Bibliographic record
Abstract
Background: Patients with platelet dysfunction disorders present with a variety of mucocutaneous bleeding symptoms including easy bruising, frequent epistaxis, bleeding gums upon tooth brushing and for women, heavy menstrual bleeding. Available laboratory assays to evaluate platelet function include the platelet function analyzer (PFA) and in larger centers with coagulation laboratories, light transmission platelet aggregometry (LTA) analyses. Both assays are known to have a number of limitations, especially in the diagnosis of platelet delta granule storage pool deficiency (δ-SPD). δ-SPD is an underdiagnosed condition caused by decreased numbers of platelet dense granules (DGs) and is best diagnosed by electron microscopy (EM). Patients with platelet δ-SPD have a decreased response to low levels of the agonist adenosine diphosphate (ADP) in the second wave of light transmittance with LTA or decreased ADP secretion by fluorescence lumiaggregometry. There are few reports that have evaluated patients with δ-SPD and their respective LTA results. One report published in 1987 described normal LTA assays in 23% of patients with δ-SPD; a more recent report described LTA as having the sensitivity to detect only about 52% of patients with δ-SPD. The purpose of our study was intended to review the LTA and EM results of patients suspected of having a platelet function disorder at our institution for comparison with previously published studies. Methods: Our study included 344 patients who had been evaluated by both LTA and whole mount EM. Aggregometry utilized five agonists: ADP, epinephrine, collagen, arachidonic acid, and ristocetin. DGs were enumerated in 100 whole-mounted platelets to determine a mean number of dense granules per platelet (DGs/PL). Results: Seventy-seven percent of our patients were found to have δ-SPD (264/344); 68% (179/264) of these subjects had an abnormal platelet LTA. Thirty-two percent (85/264) of our patients had normal LTA results but were found to have δ-SPD with a mean of 2.54 ± 0.15 DG/PL (normal = 4 - 6 DG/PL). Conclusion: These data confirm previous reports suggesting the utilization of LTA alone in patients with histories of unexplained bleeding may miss the diagnosis of platelet δ-SPD. It is, therefore, prudent to assess platelet DG number by EM, especially if platelet LTA assessment is normal.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".