Platelet quality measured with dynamic light scattering correlates with transfusion outcome in hematologic malignancies
Bibliographic record
Abstract
BACKGROUND: A clinically meaningful test for platelet (PLT) quality could improve the transfusion management of patients. The aim of this pilot study was to determine whether a new measure of PLT quality and function based on dynamic light scattering (DLS) correlates with transfusion outcome. STUDY DESIGN AND METHODS: For a total of 160 transfusions, the pretransfusion, 1 hour posttransfusion, and 24-hour posttransfusion PLT counts were routinely measured in 49 patients (31 male, 18 female; age 46 +/- 15 years) with hematologic malignancies. The corrected count increments (CCIs) at 1 hour (PLT recovery) and 24 hours (PLT survival) were calculated and used as the transfusion outcome measures. The ThromboLUX score (LightIntegra Technology, Inc., Vancouver, BC, Canada; range, 0-40; cutoff, 12) and the PLT morphology score of the PLT concentrates were determined and compared to transfusion outcome. RESULTS: The CCIs and ThromboLUX scores were normally distributed and showed a strong correlation (n = 96, in the mixed regression model the adjusted coefficient is R = 0.6292, p < 0.0001), while other variables such as product type, age, and microscopic PLT morphology score were not correlated with transfusion outcome (p > 0.05). Importantly, 12 of 96 transfusions with poor PLT quality were clinically ineffective, that is, did not adequately increase the PLT counts in the recipients. One patient died after receiving three consecutive ineffective PLT transfusions with a low ThromboLUX score. CONCLUSION: In this pilot study, the ThromboLUX score strongly correlated with transfusion outcome (PLT recovery and survival) independent of clinical and product issues.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".