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
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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