Hepatocyte microvesicle levels improve prediction of mortality in patients with cirrhosis
Bibliographic record
Abstract
Microvesicles (MVs) are extracellular vesicles released by cells following activation or apoptosis. Some MV subpopulations augment with cirrhosis severity and contribute to portal hypertension. This study aimed at determining if plasma MV levels can estimate the presence of hepatic venous pressure gradient (HVPG) ≥10 mm Hg and predict mortality in patients with advanced chronic liver disease. All patients with severe fibrosis or cirrhosis undergoing liver catheterization between 2013 and 2015 at two centers were prospectively included. We measured circulating levels of annexin V + , platelet, leukocyte, endothelial, and hepatocyte MVs. The test cohort included 139 patients. Hepatocyte MV levels were 4.0‐fold and 2.2‐fold higher in patients with Child‐Pugh C than in those with Child‐Pugh A or B liver disease, respectively. Levels of other MV subpopulations were not influenced by liver disease severity. Hepatocyte MV levels correlated with HVPG but could not identify patients with HVPG ≥10 mm Hg. Hepatocyte MV level >65 U/L predicted 6‐month mortality independently of Child‐Pugh score and of Model for End‐Stage Liver Disease (MELD). Patients with hepatocyte MV levels >65 U/L and MELD >15 had a higher 6‐month mortality than other patients (23% versus 3%; P = 0.001). These findings were confirmed in a validation cohort including 103 patients. Conclusion : Circulating MV levels cannot identify patients with HVPG ≥10 mm Hg; by contrast, hepatocyte MV levels strongly improve prediction of 6‐month mortality in patients with advanced chronic liver disease; therapies associated with decreased levels of circulating hepatocyte MV might be attractive strategies in patients with severe cirrhosis. (H epatology 2018).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".