Bibliographic record
Abstract
During the past decade, the role of inflammation in the pathophysiology of arterial thrombosis has been elucidated. However, comparatively little is known about the relationship between inflammation and venous thrombosis. The aim of this study was to perform a systematic review of clinical studies that have examined the association between inflammation and venous thrombosis, specifically: (1) the value of inflammatory markers in predicting the future development of venous thrombosis; (2) test characteristics of markers of inflammation in the diagnosis of acute venous thrombosis; and (3) effect of venous thrombosis on blood levels of inflammatory markers. Using keywords venous thrombosis, venous thromboembolism, inflammation, acute phase markers, C-reactive protein (CRP), interleukin (IL)-6, IL-8, and monocyte chemotactic protein (MCP)-1, PubMed and Medline computerized databases were searched for English language articles published after 1980. Search results were restricted to clinical studies in humans that used study designs that were appropriate to address the above objectives. Results show that plasma CRP levels do not appear to predict risk of future venous thrombosis (two studies; N = 41,308). Four studies (N=562) have examined the utility of plasma CRP in the diagnosis of venous thrombosis; pooled positive and negative predictive values were 53% (95% CI:47%,59%) and 85% (95% CI: 81%, 89%), respectively. A two- to six-fold increase in the risk of deep vein thrombosis (DVT) is associated with elevations in plasma levels of CRP, IL-6, IL-8, MCP-1 or TNF-alpha (three studies). We can conclude that the nature of the relationship between inflammation and clinical venous thrombosis is not yet established. CRP does not appear to be useful in predicting future venous thrombosis or in the diagnosis of acute venous thrombosis. While several markers of inflammation are elevated in acute venous thrombosis, further research is needed to determine the precise relationship between these markers and venous thrombosis. The identification and elucidation of inflammatory markers relevant to venous thrombosis could provide targets for future therapy.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".