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Korean J Pancreas Biliary Tract > Volume 30(1):2025 > Article
Sotoudeheian: Unveiling the Link between Albumin-Bilirubin Grade and Liver Fibrosis in Patients with a History of Gallstone and Gallbladder Surgery: A Focus on Metabolic Dysfunction-Associated Steatohepatitis

Abstract

Background/Aim

This study investigated the relationship between albumin-bilirubin (ALBI) grade and advanced liver fibrosis in patients with a history of gallstone disease and cholecystectomy, focusing on those diagnosed with metabolic dysfunction-associated steatohepatitis (MASH) using the acMASH algorithm.

Methods

Data from 566 subjects in the National Health and Nutrition Examination Survey 2017-2020 dataset were analyzed. MASH and advanced fibrosis (AF) were determined using acMASH and acFibroMASH algorithms, respectively. Liver stiffness measurement (LSM), ALBI grade, and other fibrosis indices were evaluated.

Results

Of 566 subjects, 13 (2.3%) were diagnosed with MASH, and 65 (11.48%) had AF. MASH subjects showed significantly higher LSM values compared to non-MASH subjects (p=0.032). ALBI grade demonstrated weak positive correlations with LSM, FIB-4, and acFibroMASH in non-MASH subjects. The AUROC for ALBI grade in identifying AF was 0.631 (95% CI 0.590-0.671). Multivariate analysis confirmed ALBI grade as an independent predictor of AF (odds ratio 0.193, 95% CI 0.1025-0.2837, p<0.001).

Conclusions

ALBI grade shows potential as a non-invasive marker for advanced liver fibrosis in patients with a history of gallstone disease and cholecystectomy, particularly in those with MASH. Further studies with larger MASH cohorts are needed to validate these findings.

INTRODUCTION

Liver fibrosis is a significant health concern that can progress to cirrhosis and end-stage liver disease if left undetected and untreated [1]. While various etiologies contribute to liver fibrosis, the relationship between gallstone disease, cholecystectomy, and subsequent liver health remains an area of ongoing research [2,3]. Recent studies have suggested that patients with a history of gallstones and gallbladder surgery may be at an increased risk for liver fibrosis, potentially due to alterations in bile acid metabolism and hepatic blood flow [2,4,5].
The albumin-bilirubin (ALBI) grade has emerged as a simple yet powerful tool for assessing liver function and predicting outcomes in various liver diseases. Originally developed for hepatocellular carcinoma prognosis, the ALBI grade has shown promise in evaluating liver function across a spectrum of hepatic conditions [6]. However, its utility in predicting advanced liver fibrosis, particularly in patients with a history of gallstone disease and cholecystectomy, has not been thoroughly investigated.
Metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease, is increasingly recognized as a major cause of liver fibrosis worldwide [7]. The more severe form, metabolic dysfunction-associated steatohepatitis (MASH), can lead to rapid progression of fibrosis and increased risk of liver-related complications [8]. The relationship between MASH and gallstone disease is complex, with shared risk factors such as obesity and metabolic syndrome potentially contributing to both conditions [9,10].
Recent advancements in non-invasive assessment of liver fibrosis have provided new opportunities for early detection and monitoring of liver fibrosis. The acMASH algorithm offers a promising approach to diagnosing MASH and assessing liver fibrosis without the need for invasive liver biopsy [11].
In this study, we aim to investigate the correlation between ALBI grade and advanced liver fibrosis in subjects with a history of gallstone disease and gallbladder surgery. Additionally, we seek to explore the prevalence of MASH in this population, as diagnosed by the acFibroMASH algorithm. Moreover, the study explores the potential role of ALBI grade in patients with MASH, as a subgroup. By examining these relationships, we hope to shed light on the potential long-term hepatic consequences of gallstone disease and cholecystectomy, and to evaluate the utility of the ALBI grade as a predictor of advanced liver fibrosis in this specific patient population.

METHODS

1. Data origin and participant selection

This research utilized information from the 2017-2020 National Health and Nutrition Examination Survey (NHANES), managed by the Centers for Disease Control and Prevention's National Center for Health Statistics. NHANES is an ongoing cross-sectional study assessing the health and dietary status of Americans. It offers comprehensive data on demographics, eating habits, physical assessments, lab results, and questionnaire responses.

2. Subjects’ data collection

The investigation gathered information through surveys, lab analyses, and physical check-ups to examine various factors. These included age, sex, waist size, body mass index, liver enzymes (alanine transaminase [ALT] and aspartate transaminase [AST]), high-density lipoprotein cholesterol, blood sugar, platelet count (PLT), HbA1c, and liver elastography findings.
Baseline laboratory results were derived from NHANES data; however, the timing relative to cholecystectomy could not be fully determined, which is a limitation that may affect the interpretation of our findings.

3. Transient elastography

Participants underwent liver fibrosis and fat assessment using FibroScan® (Echosens, North America) elastography equipment. Liver stiffness measurement (LSM) was measured in kilopascals (kPa), while liver fat was quantified in decibels per meter (dB/m) via controlled attenuation parameter. Median liver stiffness values of 9.7 kPa or higher indicated advanced fibrosis (AF), while 13.6 kPa or above suggested cirrhosis.

4. Non-invasive biomarkers

FIB-4 is a non-invasive scoring system used to assess liver fibrosis. It incorporates age, AST, ALT, and PLT. The formula for FIB-4is:FIB-4=(Age years×AST U/L)/(PLT 109/L×ALTU/L). The acMASH and acFibroMASH were calculated for all subjects with the following formula: acFibroMASH=e-3.956+0.305*LSM+0.065*acMASH/(1+e-3.956+0.305*LSM+0.065*acMASH) and acMASH=AST (U/L)/SCr (µmol/L)*10.

5. Participant categorization

Participants were sorted into two main groups based on their acMASH results: those with MASH and those without (non-MASH, NM). Individuals scoring 7.73 or higher on the acMASH scale were classified as MASH.
Additionally, we created two separate categories based on liver fibrosis status: AF and non-fibrotic (NF). This classification used the acFibroMASH score, with a threshold of 0.39. Scores at or above this value indicated AF, while lower scores signified NF.

6. Statistical analysis

We presented categorical data as frequencies and continuous variables as either mean±standard deviation (SD) or median (range), depending on data distribution. We compared group averages using unpaired t-tests, Welch’s test and Mann– Whitney test, and employed Pearson or Spearman correlations as appropriate. Our analysis also included AUROC and multivariate logistic regression.
We conducted statistical analyses using three software packages: GraphPad Prism 8, IBM SPSS Statistics 18.0, and MedCalc Statistical Software version 19.2.6. For all tests, we considered p-values below 0.05 as statistically significant.

7. Ethical approval

The studies involving human participants were reviewed and approved by the Centers for Disease Control and Prevention. The participants provided their written informed consent to participate in this study. The NHANES database was approved by the Ethics Review Committee of the National Center for Health Statistics (Protocol #2018-01 [Effective beginning October 26, 2017], Continuation of Protocol #2011-17 [Effective through October 26, 2017]).

RESULTS

1. Demographic and clinical characteristics

A total of 566 subjects with a history of gallstone disease and cholecystectomy, with a mean age of 59.39±15.50 years, were included in this study (Fig. 1). Based on the acMASH algorithm, 13 subjects (2.3%) were diagnosed with MASH, while 553 subjects (97.7%) were classified as NM. Using the acFibroMASH algorithm, 65 subjects (11.48%) were categorized as having AF, while 501 subjects (88.52%) were classified as NF. There were 41 (7.24%) subjects who had cirrhosis (fibrosis grade 4 [F4] or LSM ≥13.6 kPa).
Notably, the MASH group exhibited significantly higher values for LSM (mean LSM=11.49±6.04 kPa) compared to the NM group (mean LSM=7.39±7.84 kPa), indicating a potential correlation between MASH and advanced liver fibrosis. Moreover, the MASH group demonstrated ALBI values with a mean ALBI of -2.69±0.41 in comparison to the NM group with a mean ALBI of -2.81±0.28.
The laboratory characteristics of the study population are summarized in Table 1. This table presents the characteristics of the study population, not stratified by MASH and fibrosis status.
Supplementary Table 1 and 2 showed the demographic and clinical characteristics of the study population in MASH and AF groups. Significant differences were observed between MASH and NM groups in terms of age (p=0.01) (Supplementary Table 3). Similarly, the AF group showed higher weight, body mass index, waist circumference, and prevalence of hypertension and diabetes compared to the NF group (Supplementary Table 4).

2. Liver function and fibrosis parameters

To assess the differences between MASH and NM subjects, Welch’s t-test was performed on LSM values. The results indicated a statistically significant difference in LSM between the two groups (t=2.40, p=0.032), confirming that MASH subjects have higher liver stiffness indicative of AF compared to NM subjects.
Similarly, when comparing AF and NF subjects based on acFibroMASH score, a significant difference was observed in LSM values. The AF group (n=65) had a mean LSM of 22.28 kPa (SD=16.32) versus the NF group (n=501) with a mean LSM of 5.56 kPa (SD=1.72), and this difference was also statistically significant (t=8.25, p<0.001).
To assess the differences between MASH and NM subjects, Welch’s t-test was conducted on ALBI scores. The results showed no statistically significant difference in ALBI values between the two groups (t=1.037, p=0.3199), indicating that MASH subjects did not exhibit higher liver dysfunction compared to NM subjects.
In contrast, when comparing AF and NF subjects, a significant difference was observed in ALBI scores. The AF group had a mean ALBI score significantly lower than the NF group, where with the mean ALBI in AF was -2.67±0.32 and the mean ALBI in NF was -2.82±0.27. This difference was statistically significant (t=3.727, p<0.001), confirming that AF is associated with poorer liver function compared to non-fibrosis.
MASH subjects demonstrated significantly higher levels of ALT, AST, and total bilirubin, and lower BUN, creatinine, and PLT compared to NM subjects (Supplementary Table 3). The AF group showed elevated liver enzymes, glucose level, and bilirubin, lower PLTs, and higher LSM values compared to the NF group (all p<0.001) (Supplementary Table 4).

3. Correlation between ALBI grade and fibrosis indexes

Pearson correlation coefficients were calculated to explore the relationship between ALBI grade and various advanced liver fibrosis indexes, including LSM, FIB-4, and acFibroMASH (Fig. 2).
In subjects with MASH, the ALBI grade showed significant correlations with other fibrosis indexes across the entire study population. No correlation was observed between ALBI grade and acFibroMASH score and LSM (r=0.52, p=0.066 and r=0.52, p=0.065, respectively). No correlation was found between ALBI grade and FIB-4 (r=0.19, p=0.523) (Supplementary Fig. 1).
In NM subjects there was a weak positive correlation was found between ALBI grade and LSM (r=0.15, p<0.001), suggesting that as ALBI grade increases, so does liver stiffness. Additionally, a weak positive correlation was observed between ALBI grade and FIB-4 (r=0.12, p =0.005), as well as with acFibroMASH (r=0.16, p<0.001), indicating that higher ALBI grades are associated with increased values of these advanced liver fibrosis indexes (Supplementary Fig. 2).
Table 2, Supplementary Table 5, and 6 present the correlation coefficients between ALBI grade and fibrosis indexes. Table 2 includes variables reflecting liver function and demographic characteristics alongside fibrosis indices. While these factors provide context, they should be interpreted cautiously as not all are direct markers of fibrosis.

4. ALBI grade as a predictor of advanced liver fibrosis

Receiver operating characteristic (ROC) curve analysis was performed to assess the performance of ALBI grade in predicting AF. The area under the ROC curve (AUROC) for ALBI grade in identifying AF was 0.631 (95% confidence interval [CI] 0.590-0.671, p<0.001) (Fig. 3). At the optimal cut-off value of -2.50, ALBI grade demonstrated a sensitivity of 32.31% and specificity of 88.02% for detecting AF.
In multivariate logistic regression analysis, ALBI grade remained an independent predictor of AF (odds ratio 0.193, 95% CI 0.1025-0.2837, p<0.001).

5. Subgroup analysis: MASH vs. NM

Despite the small number of MASH subjects (n=13), exploratory analyses were conducted to compare the performance of ALBI grade in MASH and NM groups. The AUROC for ALBI grade in predicting AF was higher in the MASH group (0.738, 95% CI 0.430-0.934) compared to the NM group (0.617, 95% CI 0.576-0.658).

DISCUSSION

This study investigated the relationship between ALBI grade and advanced liver fibrosis in patients with a history of gallstone disease and cholecystectomy, with a particular focus on those diagnosed with MASH using the acMASH algorithm. Our findings provide valuable insights into the utility of ALBI grade as a potential marker for liver fibrosis in this specific patient population.
Our results demonstrated a significant difference in LSM between MASH and NM subjects, with MASH patients exhibiting higher LSM values indicative of AF. This finding aligns with previous studies that have shown a strong association between MASH and the progression of liver fibrosis [12,13]. The higher LSM values in MASH patients underscore the importance of early identification and management of this condition to prevent the progression of liver fibrosis.
Interestingly, while we observed a significant difference in LSM between MASH and NM groups, the ALBI scores did not show a statistically significant difference. This contrasts with some previous studies that have reported a correlation between ALBI grade and the severity of liver disease in MASLD patients [14]. The discrepancy in our findings might be attributed to the small sample size of subjects (n=13) in our study, which limits the statistical power to detect subtle differences, and the population group.
When comparing AF and NF subjects based on the acFibroMASH score, we found significant differences in both LSM and ALBI scores. The AF group demonstrated higher LSM values and lower ALBI scores, consistent with previous research showing that AF is associated with deteriorating liver function [15]. This reinforces the potential utility of both LSM and ALBI grade in assessing liver fibrosis severity.
The mean LSM value of 7.48±7.83 in this study reflects a relatively high degree of liver stiffness within the cohort, suggesting that a proportion of patients may have cirrhosis. Future studies should stratify analyses by cirrhosis status to better understand its impact on ALBI grade and fibrosis associations.
Our correlation analysis revealed weak but significant positive correlations between ALBI grade and other fibrosis indexes (LSM, FIB-4, and acFibroMASH) in NM subjects. However, the weak correlations suggest that ALBI grade should be used in conjunction with other fibrosis markers for a more comprehensive assessment. Further studies are needed to investigate whether ALBI grade, in combination with other fibrosis indices, may yield stronger predictive power.
The ROC curve analysis showed that ALBI grade has moderate accuracy in predicting AF, with an AUROC of 0.631. This performance is lower than what has been reported in some previous studies on chronic liver diseases [16,17], which may be due to the specific characteristics of our study population with a history of gallstone disease and cholecystectomy. Nevertheless, the multivariate logistic regression analysis confirmed ALBI grade as an independent predictor of AF, supporting its potential role in fibrosis assessment.
While the AUROC value of 0.631 for ALBI grade is modest, it highlights the potential for ALBI grade to contribute to a composite model for assessing liver fibrosis. Future studies should explore the integration of ALBI grade with other biomarkers to enhance predictive accuracy.
Remarkably, our exploratory analysis suggested that ALBI grade might have better predictive performance for AF in MASH subjects compared to NM subjects. This finding, although limited by the small MASH sample size, is intriguing and warrants further investigation in larger cohorts. It aligns with studies that have shown the particular relevance of ALBI grade in assessing liver function in patients with fatty liver disease [14,18,19].
The association of ALBI grade with AF likely reflects its dependence on liver function parameters. While not a direct measure of fibrosis, it may provide indirect insight into liver dysfunction associated with advanced disease.
Our study has several limitations. The limited number of MASH patients (n=13) significantly restricts the generalizability of our findings for this subgroup. As such, our results should be interpreted as preliminary, emphasizing the need for larger-scale studies to validate these observations. The small number of MASH subjects limits the statistical power and generalizability of our findings specific to this subgroup. Additionally, the cross-sectional nature of our study precludes the assessment of temporal relationships between ALBI grade and fibrosis progression.
Our findings suggest that while ALBI grade had potential to assess liver fibrosis, its alone utility is not sufficient to predict fibrosis with high accuracy, its statistically significant association with AF highlights its potential for inclusion in composite predictive models. We propose that future studies with larger sample sizes and validation cohorts are essential to establish its role more robustly, particularly in patients with MASH.
In conclusion, our study provides evidence for the potential utility of ALBI grade in assessing liver fibrosis in patients with a history of gallstone disease and cholecystectomy, particularly in those with MASH. While the AUROC value suggests limited utility as a standalone marker, the ALBI grade was evaluated primarily to assess its accuracy and role within broader multi-marker models. While ALBI grade shows promise as an independent predictor of AF, its moderate accuracy suggests it should be used in combination with other fibrosis markers. These results suggest that future studies incorporating larger cohorts and additional biomarkers may enhance the predictive accuracy of ALBI grade. Future longitudinal studies with larger MASH cohorts are needed to further elucidate the role of ALBI grade in monitoring liver fibrosis progression in this specific patient population.

Notes

Conflict of Interest
The author has no conflicts to disclose.
AUTHORS’ CONTRIBUTIONS
MS: Reviewing the literature, Methodology, Investigation, Conceptualization, Data curation, Formal analysis, Writing – the original draft, review & and editing.
DATA AVAILABILITY
Data is available at the official website of NHANES (https://wwwn.cdc.gov/nchs/nhanes/continuousnhanes/default.aspx?Cycle=2017-2020).

Acknowledgements

We want to acknowledge the team of the National Health and Nutrition Examination Survey (NHANES) for providing the publicly available data. Special thanks to Dr. SeyedAhmad Hosseini. During the preparation of this work, the authors used ChatGPT for paraphrasing and grammar checking. Following the use of this tool, the authors thoroughly reviewed and edited the content as needed and take full responsibility for the final version of the publication.

SUPPLEMENTARY MATERIALS

Supplementary materials can be found via https://doi.org/10.15279/kpba.2025.30.1.10

Supplementary Table 1.

The demographic and clinical characteristics of the study population in MASH
kpba-30-1-10-Supplementary-Table-1.pdf

Supplementary Table 2.

The demographic and clinical characteristics of the study population in AF group
kpba-30-1-10-Supplementary-Table-2.pdf

Supplementary Table 3.

The t-test result when comparing MASH and NM groups
kpba-30-1-10-Supplementary-Table-3.pdf

Supplementary Table 4.

The t-test result when comparing AF and NF groups
kpba-30-1-10-Supplementary-Table-4.pdf

Supplementary Table 5.

Correlation coeffcients between ALBI grade and fibrosis indexes in MASH group
kpba-30-1-10-Supplementary-Table-5.pdf

Supplementary Table 6.

Correlation coeffcients between ALBI grade and fibrosis indexes in AF group
kpba-30-1-10-Supplementary-Table-6.pdf

Supplementary Fig. 1.

The correlation matrix shows the correlation coeffcients between variables in MASH group (included variables in order: LSM, CAP, BMI, HDL, Cholesterol, PLT, ALT, AST, Albumin, ALP, Cr, Globulin, Glucose, HbA1c, acMASH, acFibroMASH, FIB-4, ALBI). LSM, liver stiffness measurement; CAP, controlled attenuation parameter; BMI, body mass index; HDL, high-density lipoprotein; Chol, cholesterol; PLT, platelet count; ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALB, serum albumin level; ALP, alkaline phosphatase; Cr, creatinine; HbA1c, hemoglobin A1C; FIB-4, fibrosis-4 index; ALBI, albumin-bilirubin grade.
kpba-30-1-10-Supplementary-Fig-1.pdf

Supplementary Fig. 2.

The correlation matrix shows the correlation coeffcients between variables in NM group (included variables in order: LSM, CAP, BMI, HDL, Cholesterol, PLT, ALT, AST, Albumin, ALP, Cr, Globulin, Glucose, HbA1c, acMASH, acFibroMASH, FIB-4, ALBI). LSM, liver stiffness measurement; CAP, controlled attenuation parameter; BMI, body mass index; HDL, high-density lipoprotein; Chol, cholesterol; PLT, platelet count; ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALB, serum albumin level; ALP, alkaline phosphatase; Cr, creatinine; HbA1c, hemoglobin A1C; FIB-4, fibrosis-4 index; ALBI, albumin-bilirubin grade.
kpba-30-1-10-Supplementary-Fig-2.pdf

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19. Xu J, Wang Z, Meng ZH. Associations among albumin-bilirubin grade, metabolic dysfunction-associated fatty liver disease, and exercise. Research Square [Preprint] 2023;[cited 2024 Nov. 6]. Available from: https://doi.org/10.21203/rs.3.rs-3493430/v1.
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Fig. 1.
Flow chart for participants’ selection. NHANES, the National Health and Nutrition Examination Survey; Hx, history.
kpba-30-1-10f1.jpg
Fig. 2.
The correlation matrix shows the correlation coeffcients between variables in all participants. LSM, liver stiffness measurement; CAP, controlled attenuation parameter; Circ, circumference; ALT, alanine aminotransferase; AST, aspartate aminotransferase; GGT, γ-glutamyl transaminase; HbA1c, hemoglobin A1C; FIB-4, fibrosis-4 index; ALBI, albumin-bilirubin grade.
kpba-30-1-10f2.jpg
Fig. 3.
The AUROC of ALBI in detecting advanced liver fibrosis in subjects who had previous history of gallstone and gallbladder surgery. AUROC, area under the receiver operating characteristic curve; ALBI, albuminbilirubin.
kpba-30-1-10f3.jpg
Table 1.
Laboratory characteristics of study participants
Variable Total number of values Median Mean Standard deviation Standard error of mean
Age (years) 566 61 58.39 15.50 0.65
LSM (kPa) 566 5.4 7.48 7.83 0.33
Cirrhosis (F4 or LSM ≥13.6 kPa) 41 22.2 28.25 18.08 2.82
CAP (dB/m) 566 285 283.09 62.60 2.63
Weight (kg) 557 86.5 90.58 25.55 1.08
Height (cm) 555 162.4 162.93 8.97 0.38
Waist circumference (cm) 535 108.3 109.48 17.31 0.75
BMI (kg/cm2) 555 32.3 34.01 8.81 0.37
Hip circumference (cm) 535 113 116.06 17.76 0.77
HDL (mmol/L) 566 1.29 1.35 0.38 0.02
Cholesterol (mmol/L) 566 4.62 4.70 1.05 0.04
PLT (103/μL) 566 247 253.99 74.11 3.12
Hb (g/dL) 566 13.6 13.58 1.56 0.07
ALT (IU/L) 566 17 21.36 13.66 0.57
AST (IU/L) 566 19 20.76 9.36 0.39
ALB (g/L) 566 39 39.36 3.47 0.15
ALP (IU/L) 566 80 84.94 34.31 1.44
Total bilirubin (μmol/L) 566 6.84 7.80 4.92 0.21
BUN (mmol/L) 566 5.36 5.70 2.23 0.09
Cr (μmol/L) 566 71.6 76.75 28.15 1.18
Globulin (g/L) 566 31 31.00 4.41 0.19
Glucose (mmol/L) 566 5.38 6.01 2.14 0.09
GGT (IU/L) 566 22 34.06 62.28 2.62
HbA1c (%) 564 5.7 6.08 1.23 0.05
acMASH 566 2.62 2.96 1.63 0.07
acFibroMASH 566 0.11 0.20 0.22 0.01
FIB-4 566 1.05 1.23 0.79 0.03
ALBI 566 -2.78 -2.80 0.29 0.01

LSM, liver stiffness measurement; CAP, controlled attenuation parameter; BMI, body mass index; HDL, high-density lipoprotein; PLT, platelet count; Hb, hemoglobin; ALT, alanine aminotransferase; AST, aspartate aminotransferase; ALB, serum albumin level; ALP, alkaline phosphatase; BUN, blood urea nitrogen; Cr, creatinine; GGT, γ-glutamyl transaminase; HbA1c, hemoglobin A1C; FIB-4, fibrosis-4 index; ALBI, albumin-bilirubin grade.

Table 2.
Correlation coefficients between ALBI grade with liver tests and fibrosis indexes in all subjects
Variable Pearson r 95% confidence interval R squared p-value p-value summary Number of XY Pairs
Age (years) 0.06 -0.023 to 0.14 0.0036 0.1541 ns 566
LSM (kPa) 0.16 0.077 to 0.24 0.025 0.0002 * 566
CAP (dB/m) 0.011 -0.071 to 0.094 0.00013 0.7876 ns 566
Waist circumference (cm) 0.24 0.16 to 0.32 0.059 <0.0001 * 535
ALT (IU/L) -0.12 -0.20 to -0.035 0.014 0.0054 * 566
AST (IU/L) -0.026 -0.11 to 0.057 0.00066 0.5417 ns 566
Globulin (g/L) 0.31 0.23 to 0.38 0.094 <0.0001 * 566
GGT (IU/L) 0.05 -0.033 to 0.13 0.0025 0.2396 ns 566
HbA1c (%) 0.09 0.0072 to 0.17 0.008 0.0332 * 564
acMASH -0.055 -0.14 to 0.027 0.003 0.1902 Ns 566
acFibroMASH 0.19 0.10 to 0.26 0.034 <0.0001 * 566
FIB-4 0.14 0.054 to 0.22 0.018 0.0012 * 566

ALBI, albumin-bilirubin grade; LSM, liver stiffness measurement; CAP, controlled attenuation parameter; ALT, alanine aminotransferase; AST, aspartate aminotransferase; GGT, γ-glutamyl transaminase; HbA1c, hemoglobin A1C; FIB-4, fibrosis-4 index; ns, not significant.

The table presents variables related to liver function and demographic characteristics, along with fibrosis indices. While these factors offer valuable context, they should be interpreted with caution, as not all of them serve as direct markers of fibrosis.

* Statistically significant.

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