Search for Venous Endothelial Biomarkers Heralding Venous Thromboembolism in Space: A Qualitative Systematic Review of Terrestrial Studies
Bibliographic record
Abstract
Background: The recent discovery of a venous thrombosis in the internal jugular vein of an astronaut has highlighted the need to predict the risk of venous thromboembolism in otherwise healthy individuals (VTE) in space. Virchow’s triad defines the three classic risk factors for VTE: blood stasis, hypercoagulability, and endothelial disruption/dysfunction. Among these risk factors, venous endothelial disruption/dysfunction remains incompletely understood, making it difficult to accurately predict risk, set up relevant prophylactic measures and initiate timely treatment of VTE, especially in an extreme environment. Methods: A qualitative systematic review focused on endothelial disruption/dysfunction was conducted following the guidelines produced by the Space Biomedicine Systematic Review Group, which are based on Cochrane review guidelines. We aimed to assess the venous endothelial biochemical and imaging markers that may predict increased risk of VTE during spaceflight by surveying the existing knowledge base surrounding these markers in analogous populations to astronauts on the ground. Results: Limited imaging markers related to endothelial dysfunction that were outside the bounds of routine clinical practice were identified. While multiple potential biomarkers were identified that may provide insight into the etiology of endothelial dysfunction and its link to future VTE, insufficient prospective evidence is available to formally recommend screening potential astronauts or healthy patients with any currently available novel biomarker. Conclusion: Our review highlights a critical knowledge gap regarding the role biomarkers of venous endothelial disruption have in predicting and identifying VTE. Future population-based prospective studies are required to link potential risk factors and biomarkers for venous endothelial dysfunction to occurrence of VTE.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| 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 | 0.001 |
| 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 teacher head, 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".