Standard coagulation tests are superior to thromboelastometry in predicting outcome of patients with liver cirrhosis

Evaluation of coagulopathy in cirrhotic patients: A scoping review of the utility of viscoelastic testing

BACKGROUND

Cirrhosis causes significant coagulopathy. Traditional coagulation tests may not accurately measure coagulopathy in well-compensated patients with cirrhosis. Viscoelastic tests are functional tests that may better assess coagulopathy in cirrhotic patients.

METHODS

We searched PubMed, ScienceDirect, Google Scholar, and grey literature using terms meaning viscoelastic testing and cirrhosis. After reviewing over 500 titles and abstracts, 40 full-text papers met inclusion criteria.

RESULTS

Twenty-two papers found viscoelastic testing was a better indicator of baseline coagulation than traditional testing in cirrhosis. Nineteen additional papers evaluated the utility of peri-procedural viscoelastic testing and found they led to a reduction in blood product administration without increasing risk of hemorrhage, thrombotic events, or other complications.

CONCLUSIONS

The usage of viscoelastic testing in patients with cirrhosis allows for better assessment of coagulopathy, resulting in improved outcomes. Educating physicians to optimize care of this high-risk group is necessary to further improve their treatment.

A combination of clot formation abnormalities in thromboelastometry has a high prognostic value in patients with acute-on-chronic liver failure

BACKGROUND

Global coagulation tests offer a better tool to assess procoagulant and anticoagulant pathways, fibrinolysis and clot firmness and evaluate more accurately coagulation defects compared to conventional coagulation tests. Their prognostic role in acute-on-chronic liver disease (ACLF) or acute decompensation (AD) has not been well established.

AIMS

To assess the properties and prognostic value of the coagulation profile measured by rotational thromboelastometry (ROTEM) in ACLF and AD.

METHODS

84 consecutive patients (35 ACLF and 49 AD) were prospectively studied. Twenty healthy persons matched for age and gender were used as controls. 'Hypocoagulable' or 'hypercoagulable' profiles on admission were assessed based on nine ROTEM parameters and mortality was recorded at 30 and 90 days.

RESULTS

Individual ROTEM parameters denoted significantly more hypocoagulability in patients compared to controls. 'Hypocoagulable' profile (defined as a composite of 4 or more ROTEM parameters outside the range) was associated with more severe liver disease assessed either as MELD or Child-Pugh scores ( P  < 0.001 for both) and higher 30-day mortality (Log-rank P  = 0.012). 'Hypocoagulable' profile (HR 3.160, 95% CI 1.003-9.957, P  = 0.049) and ACLF status (HR 23.786, 95% CI 3.115-181.614, P  = 0.002) were independent predictors of 30-day mortality, in multivariate model. A higher early mortality rate was shown in ACLF patients with 'hypocoagulable' phenotype compared to those without (Log-rank P  = 0.017). 'Hypocoagulable' profile was not associated with mortality in AD.

CONCLUSION

'Hypocoagulable' profile was associated with more advanced liver disease and higher short-term mortality in patients with ACLF.

Models to predict the short-term survival of acute-on-chronic liver failure patients following liver transplantation

Background

Acute-on-chronic liver failure (ACLF) is featured with rapid deterioration of chronic liver disease and poor short-term prognosis. Liver transplantation (LT) is recognized as the curative option for ACLF. However, there is no standard in the prediction of the short-term survival among ACLF patients following LT.

Method

Preoperative data of 132 ACLF patients receiving LT at our center were investigated retrospectively. Cox regression was performed to determine the risk factors for short-term survival among ACLF patients following LT. Five conventional score systems (the MELD score, ABIC, CLIF-C OFs, CLIF-SOFAs and CLIF-C ACLFs) in forecasting short-term survival were estimated through the receiver operating characteristic (ROC). Four machine-learning (ML) models, including support vector machine (SVM), logistic regression (LR), multi-layer perceptron (MLP) and random forest (RF), were also established for short-term survival prediction.

Results

Cox regression analysis demonstrated that creatinine (Cr) and international normalized ratio (INR) were the two independent predictors for short-term survival among ACLF patients following LT. The ROC curves showed that the area under the curve (AUC) ML models was much larger than that of conventional models in predicting short-term survival. Among conventional models the model for end stage liver disease (MELD) score had the highest AUC (0.704), while among ML models the RF model yielded the largest AUC (0.940).

Conclusion

Compared with the traditional methods, the ML models showed good performance in the prediction of short-term prognosis among ACLF patients following LT and the RF model perform the best. It is promising to optimize organ allocation and promote transplant survival based on the prediction of ML models.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12876-022-02164-6.