Methodologic issues in the use of bleeding as an outcome in transfusion medicine studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Prophylactic platelet transfusions are given to thrombocytopenic patients to prevent bleeding. The benefit of platelet transfusions has frequently been assessed by measuring the count increment; however, more recently, an assessment of bleeding has been used because it is a more clinically relevant outcome measure. The purpose of this study was to identify platelet transfusion trigger studies that used bleeding as an outcome measure, compare and contrast methods used to document bleeding and analyze bleeding outcomes, and identify and discuss methodologic issues to consider when bleeding is used as a study outcome. STUDY DESIGN AND METHODS: A systematic search to identify platelet transfusion trigger studies was performed. Relevant articles were reviewed to identify how bleeding data was captured and analyzed, and methodologic considerations were identified. RESULTS: Seven articles meeting the predefined entry criteria were identified. Methods used to document bleeding included chart review and clinical assessment. The frequency of assessment and the type of personnel performing the assessment were variable. Four approaches to analysis were identified: descriptive; comparison of the proportions of patients having at least one bleed; comparison of patient days with bleeding expressed as a proportion of the total days at risk of bleeding; and time-to-event (first bleed) analysis. CONCLUSION: Methodologic issues for consideration when designing a clinical study with bleeding as the outcome measure included approaches to minimize bias in the documentation and classification of bleeding and selection of an analysis approach that is appropriate to the question being asked. The need for development of a valid and reliable bleeding scale was also identified.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 it