Hepatic cirrhosis and decompensation: Key indicators for predicting mortality risk

Table 1 Accuracy of Child Pugh vs model for end-stage liver disease in predicting decompensation

Ref.	Study population	Patient	End point	c statistic
				Child-Pugh	Model for end-stage liver disease
Kamath et al[16]	TIPS	282	3-month mortality	0.84	0.87
Angermayr et al[17]	TIPS	475	3-month mortality	0.7	0.72
			1-year mortality	0.66	0.66
Schepke et al[18]	TIPS	162	3-month mortality	0.67	0.73
			1-year mortality	0.74	0.73
Botta et al[19]	Cirrhosis	129	1-year mortality	0.69	0.67
Wiesner et al[20]	Cirrhosis, LT	3437	3-month mortality	0.76	0.83
Degré et al[21]	Cirrhosis, LT	137	3-month mortality	0.72	0.7
Said et al[22]	Chronic liver diseases	1611	3-year mortality	0.83	0.79

LT: Liver transplantation; TIPS: Transjugular intrahepatic portosystemic shunt.

Table 2 Comparative accuracy of prognostic scores in predicting decompensation

Prognostic score	Time-dependent area under the curve
ALBI	0.86 (0.78-0.92)
ALBI-fibrosis-4	0.77 (0.68-0.86)
Model for end-stage liver disease	0.66 (0.56-0.75)
Child-Pugh	0.65 (0.55-0.75)

ALBI: Albumin-bilirubin.

Table 3 Summary of prognostic factors in liver disease: Advantages and limitations

Parameter	Description	Advantages	Disadvantages
Child-Pugh score	Liver function assessment based on 5 variables: Bilirubin, albumin, INR, ascites and encephalopathy	Extensive clinical experience, easy to calculate, divides patients into 3 severity classes	Subjective variables
MELD	Considers bilirubin, creatinin and INR	Objective, widely used, predicts mortality and need for transplantation	Does not account for other relevant prognostic indicators
Hepatic venous pressure gradient	Invasive measurement of hepatic venous pressure gradient	Predictive of survival, reflects cirrhosis severity and complication risk, adds value to MELD	Invasive method, influenced by medications and other pathological conditions, not always available
Early prediction of decompensation score	Score based on albumin, bilirubin, platelets	High sensitivity in predicting decompensation, simple and quick to calculate	Limited validation
ALBI	Based on albumin and bilirubin	It assess hepatic functional reserve, greater sensitivity in detecting mild liver function deterioration	Does not account for other relevant prognostic indicators
ALBI-FIB-4	Combines ALBI and FIB-4	Identify the risk of decompensation, improves prediction compared to MELD in high-risk groups, useful for risk stratification of decompensation	Limited validation
FIB-4	Score including age, transaminases and platelets	Simple, valid for estimating hepatic FIB and predicting adverse events like hepatocellular carcinoma and transplant	Limited to FIB evaluation, not always useful for advanced cirrhosis or non-fibrotic liver diseases
Nonalcoholic fatty liver disease FIB score	Score considering body mass index, glucose levels, transaminases, platelets, age and albumin	Valid for estimating hepatic FIB, predictor of cardiovascular events, mortality and liver-related event risks	Primarily applicable to metabolic dysfunction-associated fatty liver disease patients
Sarcopenia (CT and US)	Measurement of muscle mass, with CT as the gold standard and US as an alternative	CT is accurate and provides a reliable muscle mass measurement. US is less expensive, less invasiv and more accessible	CT is costly and not always available. US depends on the operator’s skill and there are no cut-off for diagnosis of sarcopenia
Hand grip strength	Measurement of muscle strength via hand grip, an indicator of overall muscle strength	Simple, inexpensive, non-invasive, useful for diagnosing sarcopenia and monitoring muscle changes	Does not directly measure muscle mass, cut-off value varies across studies
Artificial intelligence	Use of deep convolutional neural networks applied to CT images to automatically analyze muscle mass	High precision and consistency, reduces workload and increases efficiency	Requires computational resources and specialized training, further clinical validations needed
MiRNA (miR-21, miR-1, miR-133)	Small non-coding molecules that regulate gene expression and influence muscle biology, with implications for sarcopenia	Regulate muscle metabolism and are involved in muscle atrophy and FIB. Possible diagnostic and prognostic applications	Role still unclear, further research is needed to clarify their clinical applications in cirrhosis and sarcopenia

ALBI: Albumin-bilirubin; CT: Computed tomography; FIB-4: Fibrosis-4; INR: International normalized ratio; MELD: Model for end-stage liver disease; US: Ultrasound.