Fibroscan and Low-Density Lipoprotein Versus Non-invasive Markers (APRI test and FIB-4) As Determinants of Severe Liver Fibrosis in Egyptian Diabetic Patients With Non-Alcoholic Fatty Liver Disease.

Document Type : Original Article

Authors

1 hepatology,gastroentroogy and mataria teaching hospital

2 Hepatology, Gastroenterology and infectious disease department, Faculty of Medicine, Al-Azhar University, Egypt

3 hepatology,gastroentroogy and infectious diseases, al azhar university , cairo ,egypt

4 National Hepatology and Tropical Medicine Research Institute (NHTMRI), Egypt

Abstract

Background: Type 2 Diabetes Mellitus (T2DM) cases commonly have non-alcoholic fatty liver disease (NAFLD) that can develop into severe liver fibrosis. Clinical implications might arise from the early detection of hepatic fibrosis.
Aim of the study: to evaluate the role of non-invasive scores (APRI score and FIB-4), fibroscan and low-density lipoprotein in predicting Egyptian patients with NAFLD who have severe liver fibrosis.
Patients and methods: : A prospective cohort study was carried out. in the heptogastroentrology and infectious disease Al-Hussien University Hospital and The National Hepatology and Tropical Research Institute (NHTMRI) over a 3-years period. Ninty patients attended the outpatient clinic who had NAFLD were enrolled in the study on aprospective basis, aged18 to 70 years old.
Result: the cases was separated into two groups diabetic and non diabetic
Concerning the correlation between APRI test and (fib-4, fibrosis LSM, steatosis CAP, and lab tests show significant positive correlation as regard Fib-4, fibrosis Lsm, AST, and ALT, and significant negative correlation as regard platelet and FBS, and the relationship between Fib-4 and fibrosis LSM and steatosis CAP and lab tests show significant positive correlation as regard fibrosis LSM, Age, and AST, and significant negative correlation as regard platelets and urea.
Conclusion: The combination of Fibroscan, APRI score,LDL-c and FIB-4 techniques gives a useful approach for evaluating liver fibrosis in NAFLD cases.
Keywords: Fibroscan;Liver Fibrosis; Diabetic Patients ; Non Alcoholic Fatty Liver Disease

Keywords


INTRODUCTION

Non-alcoholic fatty liver disease (NAFLD) is one of the most frequent causes of liver disease around the world. It is expected to overcome alcoholic liver disease as the most frequent reason for end-stage hepatic disease in the next ten years.1

It includes a wide range of clinical and histological signs,  starting from simple steatosis to steatohepatitis, fibrosis, and cirrhosis. 2

NAFLD is associated with an abnormal buildup of fat in the liver that is not caused by excessive alcohol usage, viral hepatitis, or drugs which be able to cause fatty liver. 3

 

 

 There are Important risk factors for NAFLD as type 2 diabetes (T2DM), hypertension, hypertriglyceridemia, hyperlipidemia and obesity. 4

The liver is a major cause of insulin resistance which is   a key part of how type 2diabetes develops and how it gets worse. NAFLD is mostly happen if you have diabetes, and about 70 percent of people with T2DM have NAFLD. 5

A leading reason for chronic liver disease is NAFLD which frequently has severe effects as decompensated hepatic cirrhosis and hepatocellular cancer. 6

Only 24% of people with high cholesterol have NAFLD. This happens more often with persons who have hypertriglyceridemia and mixed hyperlipidemia, where the rates are 50% and 60%, respectively. Hypertriglyceridemia, low HDL-C, more dense and small LDL-C are all linked to NAFLD. About 60% to 70% of people with NAFLD also have dyslipidemia. 7

Abdominal ultrasonography, measurement of the lipid profile and liver functions, excluding the presence of hepatitis B and C ,alcohol poisoning, and testing for insulin resistance (IR) are all required  for primary assessment  of early stages of fatty liver. 8

liver biopsy is the best way to find out if someone has NAFLD, although it occasionally causes complications, including bleeding, bile leakage, infections, and other potentially catastrophic problems. 9

New non-invasive laboratory and radiographic diagnostic methods have developed during the previous ten years to avoid  the problems of  liver biopsies when finding out  hepatic fibrosis in NAFLD. 10

Numerous researches had indicated the use of imaging and serological markers as non-invasive techniques for assessing fibrosis in NAFLD. 11

Recent research demonstrates that the ultrasound-based controlled attenuation parameter value applied  in the TE method may be used to predict the extent of steatosis in NAFLD patients. 10

Aim of the study to evaluate the role of non-invasive scores (APRI score  and FIB-4), fibroscan and low-density lipoprotein in predicting Egyptian patients with NAFLD who have severe liver fibrosis.

PATIENTS AND METHODS

A prospective cohort study  was carried out  in the heptogastroentrology and infectious disease Al-Hussien University  Hospital  and The National Hepatology and Tropical Research Institute (NHTMRI). Ninty patients attended  the outpatient clinic who had NAFLD over a 3-years period

FIB-4            = age (year) × AST (IU/L)/platelet count (×109/L) × √ALT (IU/L). 12

APRI Score = (AST/Upper Limit Normal AST) x 100] / Platelets (109/L). 13

Inclusions Criteria: Age (18-70 years), gender (male or female), diabetes mellitus (fasting blood sugar levels more than 126 g/dL), nondiabetic patients, patients identified as having NAFLD based on abdominal ultrasound examination (Hyperechoic liver, in which the liver echo-texture was brighter than that of the kidney, with indistinct vascular boundaries and a significant decrease in ultrasound signal), and cases who agreed to take part in the research.

Exclusions Criteria: Patients with alcoholic liver disease, patients taking Hepatotoxic drugs like methotrexate and corticosteroids, patients with advanced hepatic disease, cardiac failure, and hepatic congestion, patients patients that could not do a fibroscan examination due to a very high body mass index (BMI).and other causes of liver disease as viral, metabolic, autoimmune diseases

Ethical Considerations:  before enrollment, each participant gave their signed, informed permission. Written consents were approved by the ethical committee of Al Hussein Hepatology , Gastroenterology department and the National Hepatology and Tropical Medicine Research Institute (NHTMRI).

Methods

Initial Assessment: The outpatient clinic was the first place where all patients were checked. A comprehensive investigation and evaluation were conducted.This included:

History: Name, age, gender, place of residence, employment, marital status, certain behaviors of medical and surgical relevance are all examples of demographic information.

Examination: General examination for vital signs are heart rate, respiratory rate, blood pressure, and temperature. other systems examination, local examination of the liver was done to show site, size, surface, border, and presence of lymph node metastases. Physical examination included: BMI: Weight (Kg) / Height (m)2 (Normal: <25) waist Circumference, which is calculated horizontally at the level of the navel without compressing the skin (Normal: Males 78:94 cm, Females 64:80 cm).

Laboratory investigations: Complete blood count (CBC) is including total leucocytic count ( Total and Differential), red blood cells (RBCs), hemoglobin (Hb), and platelet count, among the laboratory tests that were performed. Bilirubin (total and direct), total proteins, serum albumin, alanine transferase (ALT), aspartate transferase (AST), and alkaline phosphatase (ALP) are all included in the list of liver function tests (LFTs), kidney function tests (KFTs), such as serum urea and creatinine. Prothrombin time (PT) and the International Normalization Ratio are two components of the coagulation profile (INR). Lipid profile is including Serum cholesterol, triglycerides and low-density lipoproteins (LDL), viral markers like hepatitis B surface antigen (HBsAg) and hepatitis C antibodies (HCV Ab).

Abdominal Ultrasonography: Equipment: Philips Envisor C HD

Fibroscan:

Study Procedures: (Fibro Scan 502, Echosens, and Paris, France)

The Fibroscan 502 touch has two probes, M+ and XL+, and can be used to measure LSM and CAP at any participating medical center (TBRI). Each study was conducted by a devoted study coordinator who followed the manufacturer set of rules (Fibro Scan 502, Echosens, and Paris, France).

Statistical analysis: Statistical Package for the Social Sciences (SPSS) version 22 for Microsoft Windows was used to code, process, and analyze the data (IBM SPSS Inc, Chicago, IL, USA). The normality of the data distribution was determined using the Shapiro-Wilk test. We utilized frequency counts and relative percentages to demonstrate qualitative data. Use the chi-square test to discover differences between two or more sets of qualitative variables (2). A ROC curve is utilized to determine a cutoff for a certain outcome. The quantitative data were reported as mean ± standard deviation (Standard deviation). Using the independent samples t-test, two sets of normally distributed variables with independent distributions were compared (parametric data). P values below 0.05 were considered significant.  


RESULTS

This study included 90 cases divided into (50 Diabetic and 40 non Diabetic) with NAFLD. As regards age, the mean age of all studied patients was 41.878 ±8.828 years. As regards sex, there were 28 males(31.11%) and 62 females(68.89%) in all the studied patients

Studied patients (N= 90)

N

%

Asymptomatic

10

11.11

Fatigue

20

22.22

Malaise

15

16.67

RUQ Abdominal pain

40

44.44

Nausea

5

5.56

Table 1: Description of symptoms of all studied patients

This table shows that : 10% of patients with NAFLD are asymptomatic, 40% complaining of right quadrant pain,20% complaining of fatigue,15%complaining of malaise, and 5% have nausea

Clinical symptoms

DM

Chi-Square

Non-Diabetic

Diabetic

N

%

N

%

X2

P-value

Asymptomatic

7

17.50

3

6.00

3.499

0.478

Fatigue

9

22.50

11

22.00

Malaise

7

17.50

8

16.00

RUQ Abdominal pain

15

37.50

25

50.00

Nausea

2

5.00

3

6.00

Table 2:        this table shows that: there was non significant comparison between two groups as regrard clinical symptoms(P-value=0.478)

 

DM

T-Test

Non-Diabetic

Diabetic

t

P-value

Age

Range

20

-

55

32

-

65

-3.210

0.002*

Mean ±SD

38.700

±

8.933

44.420

±

7.949

Weight

Range

67

-

120

53

-

126

-0.006

0.995

Mean ±SD

92.000

±

15.319

92.020

±

16.245

Height

Range

145

-

179

146

-

188

-1.461

0.148

Mean ±SD

159.425

±

7.292

161.900

±

8.498

BMI

Range

23.1

-

51.31

18.78

-

48.01

0.744

0.459

Mean ±SD

36.469

±

7.173

35.354

±

6.970

WC

Range

88

-

144

86

-

144

0.500

0.618

Mean ±SD

110.150

±

11.857

108.920

±

11.393

Chi-Square

N

%

N

%

X2

P-value

Gender

Male

12

30.00

16

32.00

0.041

0.839

Female

28

70.00

34

68.00

Smoking

No

23

57.50

30

60.00

0.057

0.811

Yes

17

42.50

20

40.00

BMI group

Normal

1

2.50

3

6.00

1.315

0.518

Overweight

25

62.50

34

68.00

Obese

14

35.00

13

26.00

Table 3:  baseline demographic data of the whole studied patients      

this table shows that : there was significant increase in age in diabetic patients (p value 0.002)

 

DM

T-Test

Non-Diabetic

Diabetic

t

P-value

Hb

Range

9.9

-

15.7

10.4

-

15.8

0.384

0.702

Mean ±SD

13.493

±

1.257

13.386

±

1.345

PLTs

Range

80

-

353

80

-

450

0.110

0.912

Mean ±SD

206.075

±

66.683

204.320

±

80.822

WBCs

Range

2.6

-

9.3

3

-

10

0.144

0.885

Mean ±SD

6.168

±

1.507

6.114

±

1.914

RBCs

Range

3.6

-

5.4

3.7

-

5.7

0.199

0.843

Mean ±SD

4.628

±

0.474

4.608

±

0.451

T. Bil

Range

0.26

-

1.32

0.39

-

1.29

0.987

0.326

Mean ±SD

0.756

±

0.226

0.710

±

0.213

D. Bil

Range

0.04

-

0.46

0.03

-

0.56

-1.644

0.104

Mean ±SD

0.242

±

0.111

0.282

±

0.117

TP

Range

6.1

-

8.2

6.1

-

8.1

-0.502

0.617

Mean ±SD

7.015

±

0.493

7.064

±

0.431

ALB

Range

3.4

-

5.8

3.1

-

5.8

0.216

0.830

Mean ±SD

4.370

±

0.537

4.344

±

0.592

FBS

Range

32

-

275

48

-

332

-0.008

0.993

Mean ±SD

132.050

±

59.652

132.160

±

64.347

AST

Range

20

-

70

17

-

80

-3.857

<0.001*

Mean ±SD

37.150

±

10.458

45.560

±

10.136

ALT

Range

21

-

75

17

-

76

-1.324

0.189

Mean ±SD

33.850

±

14.508

38.400

±

17.423

ALP

Range

35

-

104

33

-

107

0.482

0.631

Mean ±SD

67.100

±

17.016

65.340

±

17.377

GGT

Range

8

-

48

10

-

54

-1.572

0.119

Mean ±SD

23.625

±

8.095

26.680

±

9.925

Urea

Range

14

-

37

9

-

60

1.224

0.224

Mean ±SD

25.750

±

6.640

23.660

±

9.014

Creat

Range

0.08

-

2.9

0.08

-

2.9

1.609

0.111

Mean ±SD

0.938

±

0.679

0.736

±

0.514

PT

Range

10

-

11

10

-

11

-0.782

0.436

Mean ±SD

10.950

±

0.221

10.980

±

0.141

INR

Range

0.9

-

1.1

0.9

-

1.2

-0.691

0.491

Mean ±SD

1.020

±

0.069

1.030

±

0.068

TG

Range

23

-

359

67

-

318

1.157

0.250

Mean ±SD

169.750

±

79.123

153.520

±

53.576

LDL

Range

87

-

170

75

-

134

5.504

<0.001*

Mean ±SD

121.000

±

21.145

100.600

±

13.868

CHOL

Range

69

-

289

124

-

302

-1.317

0.191

Mean ±SD

198.175

±

45.071

210.940

±

46.195

Table 4: Comparison between  diabetic and non-diabetic patients  as regard lab investigations

This table shows: There was significantly decrease LDL in diabetic patients(p value <0.001)and significantly high AST in diabetic patients (p value <0.001)

 

DM

T-Test

Nondiabetic

Diabetic

t

P-value

APRI

Range

0.2-1.3

0.1-1.3

-0.707

0.481

Mean ±SD

0.548±0.311

0.592±0.284

Chi-Square

N

%

N

%

X2

P-value

APRI

grades

Low

16

40.00

17

34.00

0.344

0.557

Intermediate

24

60.00

33

66.00

Table 5: Comparison of APRI score in diabetic and nondiabetic patients

This table shows: There was non significant comparison between two groups as regard APRI titre (P-value=0.481) and APRI grades(P-value=0.557)

 

DM

T-Test

Nondiabetic

Diabetic

t

P-value

FIB-4

Range

0.2-3.2

0.4-3.7

-2.338

0.022*

Mean ±SD

1.463±0.695

1.816±0.726

Chi-Square

N

%

N

%

X2

P-value

FIB-4

grades

Low

13

32.50

11

22.00

2.186

0.335

Intermediate

25

62.50

33

66.00

High

2

5.00

6

12.00

Table 6: Comparison of Fib-4 in diabetic and nondiabetic patients

This table shows: there was a significant comparison between two groups as regard FIB-4 titre (P-value =0.022 )and non significant comparison between two groups as regard FIB-4 grades (p =0.335)

 

DM

T-Test

Nondiabetic

Diabetic

t

P-value

Fibrosis LSM

Range

2.4-10.3

3.9-15.5

-5.797

<0.001*

Mean ±SD

6.100±1.985

9.394±3.122

Chi-Square

N

%

N

%

X2

P-value

Fibrosis

grades

F0

15

37.50

2

4.00

29.285

<0.001*

F1

15

37.50

10

20.00

F2

7

17.50

16

32.00

F3

3

7.50

11

22.00

F4

0

0.00

11

22.00

Table 7: Comparison of Fibrosis by LSM and fibrosis grades in diabetic and nondiabetic patients

This table shows: there was a significant comparison between two groups as regard Fibrosis LSM  (P-value <0.001)and fibrosis grades (P-value <0.001)

 

APRI grades

Chi-Square

Low

Intermediate

N

%

N

%

X2

P-value

FIB-4 grades

Low

20

60.61

4

7.02

32.213

<0.001*

Intermediate

13

39.39

45

78.95

High

0

0.00

8

14.04

Gender

Male

10

30.30

18

31.58

0.016

0.900

Female

23

69.70

39

68.42

BMI group

Normal

2

6.06

2

3.51

1.516

0.469

Overweight

19

57.58

40

70.18

Obese

12

36.36

15

26.32

Fibrosis grades

F0

12

36.36

5

8.77

16.505

0.002*

F1

12

36.36

13

22.81

F2

4

12.12

19

33.33

F3

3

9.09

11

19.30

F4

2

6.06

9

15.79

Steatosis gardes

S0

6

18.18

10

17.54

0.117

0.990

S1

9

27.27

17

29.82

S2

9

27.27

14

24.56

S3

9

27.27

16

28.07

Table 8: Relation  between APRI grades and (FIB-4grades, gender, BMI Group, fibrosis grades, and steatosis grades)

This table shows: there was a significant comparison between two groups as regard(fib-4 grades (p value<0.001) and fibrosis grades (p value=0.002) and non significant comparison between two groups  as regard (gender ,BMI  group and steatosis grades )

 

FIB-4 grades

Chi-Square

Low

Intermediate

High

N

%

N

%

N

%

X2

P-value

Gender

Male

4

16.67

23

39.66

1

12.50

5.605

0.061

Female

20

83.33

35

60.34

7

87.50

Fibrosis

grades

F0

10

41.67

7

12.07

0

0.00

38.923

<0.001*

F1

12

50.00

13

22.41

0

0.00

F2

2

8.33

20

34.48

1

12.50

F3

0

0.00

10

17.24

4

50.00

F4

0

0.00

8

13.79

3

37.50

Steatosis

grades

S0

5

20.83

11

18.97

0

0.00

2.987

0.810

S1

6

25.00

18

31.03

2

25.00

S2

7

29.17

13

22.41

3

37.50

S3

6

25.00

16

27.59

3

37.50

Table 9: Relation between FIB-4 grades and (gender, fibrosis grades, and steatosis grades)

This table shows: there was statistically significant comparison between two groups as regard fibrosis grades ((P-value<0.001), and There was non significant comparison between FIB-4 grades as regard (Gender and Steatosis grades)       

Correlations

 

APRI

FIB-4

r

P-value

r

P-value

FIB-4

0.704

<0.001*

 

 

Fibrosis LSM

0.370

<0.001*

0.596

<0.001*

Steatosis CAP

-0.067

0.532

0.112

0.295

Age

-0.025

0.815

0.450

<0.001*

Weight

-0.101

0.345

-0.101

0.343

Height

-0.094

0.380

-0.024

0.821

BMI

-0.055

0.607

-0.094

0.377

WC

0.061

0.567

-0.003

0.975

Hb

0.048

0.655

0.016

0.878

PLTs

-0.616

<0.001*

-0.476

<0.001*

WBCs

0.029

0.783

-0.056

0.598

RBCs

-0.179

0.092

-0.181

0.088

T. Bil

-0.031

0.769

0.009

0.935

D. Bil

0.067

0.532

0.049

0.644

TP

0.059

0.584

0.003

0.978

ALB

-0.064

0.549

-0.054

0.611

FBS

-0.244

0.021*

-0.179

0.091

AST

0.359

0.001*

0.535

<0.001*

ALT

0.481

<0.001*

0.014

0.896

ALP

0.017

0.873

0.029

0.787

GGT

0.016

0.877

0.197

0.063

Urea

-0.144

0.175

-0.320

0.002*

Creat

-0.131

0.218

-0.117

0.273

PT

0.109

0.307

0.092

0.390

INR

-0.098

0.356

-0.148

0.163

TG

-0.113

0.288

-0.042

0.692

LDL

-0.144

0.175

-0.133

0.211

CHOL

0.005

0.964

0.022

0.839

Table 10: Correlation between APRI score and (FIB-4, fibrosis LSM and steatosis and lab tests) and Correlation between Fib-4 and (fibrosis LSM, steatosis CAP and lab tests)

This table shows: there was a significant positive correlation  between APRI as regard (FIB-4, fibrosis LSM, ASTand  ALT) and significant  negative correlation  as regard (platelet and FBS) and a significant positive correlation between  FIB-4 as regard (fibrosis LSM, age and AST) and significant  negative correlation  as regard  (platelet and urea)

 

Fig. 1: receiving operating characteristic curve for apri score in diabetic and non diabetic patients (Cutoff >0.5 ) Sens.= 50 Spec.= 75 Accuracy=58.2%

 

Fig.2: receiving operating characteristic curve for FIB-4 in diabetic and non diabetic patients (Cutoff >2 ) Sens.= 42 Spec.= 85 Accuracy=64.4%

 

 

Fig.3: receiving operating characteristic curve for  Fibrosis LSM in diabetic and non diabetic patients                     (Cutoff >0.5 ) Sens.= 86 Spec.= 72.5 Accuracy=83.1%


DISCUSSION

The aim of this study is to assess the impact of diabetes on NAFLD development and identify markers of severe liver fibrosis and to assess the usefulness of Fibroscan and noninvasive parameters in determining liver status

In our study we discovered that the average age of diabetic individuals with NAFLD increased significantly (p-value 0.002)

In a study to assess Fibroscan and low-density lipoprotein as determinants of severe hepatic fibrosis in diabetic cases with NAFLD, Jaafar et al., 14 found that the average age of the diabetic and nondiabetics cases was 53.7±14.6 (range: 27.0–80.0; median=55.2) and 46.1±14.6 (range: 18.0–82.0; median=48.3) years, respectively (P<0.001).

According to Mohamed et al., 15 patients with NAFLD were noticeably older than those in the controls.

In this study, we found that individuals with diabetes and those without diabetes had statistically insignificantly different in APRI grades.

Jaafar et al., 14 found that there was no difference observed in APRI between diabetic and nondiabetic cases.

There was an insignificant difference among the three groups in relation to APRI, according to Cassinotto et al., 16

In this study, we showed that diabetic individuals with NAFLD had significantly higher FIB 4 titre

Fib-4 was statistically substantially higher in diabetes than in the nondiabetic group, according to Hemida et al., 17

There were significant variations among the three groups in terms of FIB-4, according to Cassinotto et al., 16

In this study, we demonstrated that diabetic individuals had considerably greater levels of fibrosis by LSM, higher levels of fibrosis grades overall.

Cases with T2DM and obesity showed greater levels of fibrosis than controls, according to HANAN et al., 18 (p=0.023).

According to Hemida et al., 17 diabetes group fibrosis grades were statistically substantially higher than nondiabetic group fibrosis grades.

According to Jaafar et al. 2019.12 only 46 (26.3%) nondiabetics had significant liver fibrosis, compared to 35 (47.9%) diabetic patients.

In this work, we demonstrated that diabetic individuals had dramatically low LDL and significantly high AST.

According to Dai et al., 19 T2D cases that had NAFLD with liver stiffness had higher levels of High BMI, serum uric acid, triglycerides, glycated hemoglobin, and HDL-C, as well as lower AST and ALT activity than those without liver stiffness.

LDL levels were shown to be considerably lower in diabetes patients by Jaafar et al., 14. LDL levels were 101 ±13.1 mg/dl in diabetic patients compared to 120 ±15.5 mg/dl in non-diabetic individuals (P=0.017).

This research provides evidence that APRI is significantly relevant with FIB-4 and fibrosis grades.

Significant fibrosis group had greater APRI scores (1.18±0.92 vs. 0.25±0.16, respectively; (p<<0.0001) and FIB-4 scores (2.40±2.13 vs. 0.85±0.52, respectively; p=0.0001), according to Kolhe et al., 20.

According to the degree of fibrosis, Itakura et al., 21 found that APRI  increased considerably (P < 0.01) and FIB-4 also significantly increased (P< 0.01).

In this study, we discovered that the correlation between APRI grades and platelet, AST, fibrosis LSM, and FIB-4 is statistically significant.

Alhankawi et al., 22 found that FIB-4, APRI score, and AST/ALT ratio substantially connected with Fibroscan score (r=0.472, p<0.0001; r=0.418, p<0.0001; r =0.219, p=0.003).

Ucar et al., 23 discovered that cases with extensive fibrosis had significantly increased APRI score and FIB-4 (P<0.05).

In this work, we showed that the correlation between FIB-4 grades and fibrosis grades was quite strong.

Eletreby et al.24 showed that although there was no inflammation in the samples used for the study, FIB-4 was substantially linked with the existence of fibrosis.

This was also backed up by research by Kumar et al., 25 who found a connection between liver stiffness as determined by TE and other study parameters as well as other fibrosis indicators, including NFS and FIB-4.

In the research we conducted, we discovered a substantial correlation between FIB-4 grades and age, height, platelets, AST, urea, APRI test, and LSM fibrosis.

In a study published in 2014, El Nakeeb et al., 26 discovered a significant connection among the levels of FIB-4, platelet count, and AST.

According to Cassinotto et al., 16 there was a significantly positive relation between the FIB4 score and the fibrosis stage as determined by fibroscan.

In this study, we discovered that the APRI score correlated positively with FIB-4, fibrosis LSM, AST, ALT, and platelet levels, whereas FIB-4 correlated positively with fibrosis LSM, age, and AST and negatively with platelet levels and urea.

. A previous study by Fallatah et al., 27 reported that there was a substantial variation in liver stiffness score values, APRI, and the FIB-4 among cases had advanced fibrosis of more than F2 and those with mild to moderate fibrosis of F2 or under

Mansour et al., 28 found that there was a negative association between platelets and all fibrosis markers (APRI score and FIB4), and there was a positive association among AST, APRI, and FIB4 )

Our results indicated a significant correlation between LDL and fibrosis severity.

According to Jaafar et al.14 more severe fibrosis was evident in 47.9% of diabetic individuals, and this was linked to substantial variations in LDL levels between the two groups.

CONCLUSION

The combination of Fibroscan, APRI score,LDL-c and FIB-4 techniques gives a useful approach for evaluating liver fibrosis in NAFLD cases. This can reduce the demand for liver biopsy in cases without clear indications.

Limitations of our study include that diagnosis of non alcoholic fatty liver diseae was based on the combination of clinical, laboratory and Fibroscan . This could lead to excluding patients with obesity, A narrow intercostal space, Ascites, The quality of the liver parenchyma and Large vascular structure present in the acquisition window (may lead to false results)

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