The epidemiology of platelet transfusions: an analysis of platelet use at 12 US hospitals
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Using the Recipient and Donor Epidemiology Study-III (REDS-III) recipient and donor databases, we performed a retrospective analysis of platelet use in 12 US hospitals that were participants in REDS-III. STUDY DESIGN AND METHODS: Data were electronically extracted from participating transfusion service and blood center computer systems and from medical records of the 12 REDS-III hospitals. All platelet transfusions from 2013 to 2016 given to patients aged 18 years and older were included in the analysis. RESULTS: There were 28,843 inpatients and 2987 outpatients who were transfused with 163,719 platelet products (103,371 apheresis, 60,348 whole blood derived); 93.5% of platelets were leukoreduced and 72.5% were irradiated. Forty-six percent were transfused to patients with an International Classification of Diseases, 9th/10th Revision (ICD-9/10) diagnosis of leukemia, myelodysplastic syndrome (MDS), or lymphoma. The general ward and the intensive care unit (ICU) were the most common issue locations. Only 54% of platelet transfusions were ABO identical; and 60.6% of platelet transfusions given to Rh-negative patients were Rh positive. The most common pretransfusion platelet count range for inpatients was 20,000 to 50,000/μL, for outpatients it was 10,000 to 20,000/μL. Among ICU patients, 35% of platelet transfusion episodes had a platelet count of greater than 50,000/μL; this was only 8% for general ward and 2% for outpatients. The median posttransfusion increment, not corrected for platelet dose and/or patient size, ranged from 12,000 to 20,000/μL for inpatients, and from 17,000 to 27,000/μL for outpatients. CONCLUSIONS: These data from one of the largest reviews of platelet transfusion practice to date provide guidance for where to focus future clinical research studies and platelet blood management programs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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 it