Role of Controlled Attenuation Parameter in Metabolic Associated Fatty ‎Liver Disease Patients

El-Khashab, Yehia M; Zaher, Tarik I; Shaheen, Noha E; Abdel Monem, Sameh M

doi:10.21608/aeji.2022.143733.1228

Role of Controlled Attenuation Parameter in Metabolic Associated Fatty ‎Liver Disease Patients

Afro-Egyptian Journal of Infectious and Endemic Diseases

Article 2, Volume 12, Issue 3, September 2022, Page 196-207 PDF (307.2 K)

Document Type: Original Article

DOI: 10.21608/aeji.2022.143733.1228

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Authors

Yehia M El-Khashab

; Tarik I Zaher

; Noha E Shaheen; Sameh M Abdel Monem

Department of Tropical Medicine, Faculty of Medicine, Zagazig University, Egypt

Abstract

Background and study aim: Metabolic associated fatty liver disease (MAFLD) is an increased serious clinical concern .Novel physical parameter, ‎based on the properties of ultrasonic signals acquired by the Fibroscan®, is called the controlled attenuation parameter ‎‎(CAP). This study aimed at assessing the role of CAP in disease staging in MAFLD patients‎‎‎‎.‎
Patients and Methods: This is a comparative cross sectional study conducted on 84 patients diagnosed as having fatty liver by abdominal ‎ultrasonography and, features of MAFLD according to international consensus guideline. Patients classified as MAFLD ‎with chronic liver disease, HCV, HBV (Group 2) and MAFLD without other chronic liver disease (Group 1)‎.‎
Results: Most patients had marked hepatic steatosis. The diagnostic accuracy of CAP in disease staging in MAFLD patients ‎was 88% at cut off value of >297 dB/m with sensitivity 88.5% and specifity 82.8%.The diagnostic accuracy of ‎combined CAP and FLI(Fatty liver index) for liver steatosis diagnosis was 95% with sensitivity 96.2% and specifity 87.7%‎‎‎‎‎‎‎.
Conclusion: CAP may be used as a promising noninvasive tool for assessment and quantifying of steatosis in MAFLD patients. ‎Combination of both noninvasive imaging technique (CAP) and laboratory score (FLI) may improve the diagnostic ‎accuracy in assessing steatosis in MAFLD patients‎ ‎‎‎‎‎‎‎‎.

Highlights

Metabolic associated fatty liver disease (MAFLD) is increasingly becoming a serious clinical concern owing to its severe morbidity and potential progression to end stage of liver disease .
CAP may be used as a promising noninvasive tool for assessment and quantifying of steatosis in MAFLD patients.
Combination of both noninvasive imaging technique and laboratory score may improve the diagnostic accuracy in assessing steatosis in MAFLD patients, which may add to CAP.

Keywords

CAP; Fibroscan; MAFLD

Full Text

INTRODUCTION

In the twenty-first century, the prevalence of non-alcoholic fatty liver disease (NAFLD) has expanded ‎dramatically, with a current worldwide disease burden estimated to be around 25% of the global ‎population. If total intrahepatic fat mass exceeds 5% of liver mass, hepatic steatosis is observed [1, 2]. ‎

The crucial involvement of metabolic variables as significant pathogenic drivers is not covered or ‎indicated in the NAFLD terminology. However, diagnosis of alcoholic liver disease and NAFLD may ‎overlap, making it difficult to identify one from the other. To propose a more thorough redefinition of ‎fatty liver disease linked with metabolic dysfunction to replace NAFLD, we propose, "Metabolic ‎dysfunction associated fatty liver disease (MAFLD)." MAFLD diagnosis does not necessitate the ‎exclusion of patients who consume alcohol or have other chronic liver disorders, nor does it ‎necessitate the existence of a metabolic imbalance [3].‎

Serum liver enzyme abnormalities are an important aspect of regular clinical tests for individuals ‎with NAFLD; nevertheless, they are influenced by a variety of factors, including obesity, metabolic ‎syndrome, diabetes, ethnicity, and genetics. [4]. The reference standard for the diagnosis of NAFLD and ‎the assessment of NAFLD-related pathological abnormalities such as the degree of steatosis and liver ‎fibrosis is often liver biopsy [5]. However, there are well-known disadvantages to liver biopsy, such as ‎invasiveness and sample unpredictability. Noninvasive laboratory and radiographic assessment ‎methods for hepatic steatosis and fibrosis in NAFLD have evolved, which may help overcome the ‎limitations of liver biopsy, such as the FIB4, APRI score, FLI, and NFS, as well as radiological methods ‎such as Transient elastography [6]‎.

The FibroScan's vibration-controlled transient elastography (VCTE) method monitors the velocity ‎of the shear wave, which is then translated to stiffness using the Young's module. It has been ‎established as a quick and painless method for diagnosing and staging liver fibrosis [7]. The controlled ‎attenuation parameter (CAP) is a physical parameter based on the FibroScan's ultrasonic signal ‎characteristics. CAP detects ultrasonic attenuation at the VCTE's core frequency using a M or standard ‎probe, which may aid in the diagnosis of steatosis [8]. This study aimed to assess role of CAP in ‎disease staging in MAFLD patients.‎

PATIENTS‎ AND METHODS

This is a comparative cross sectional study conducted on 84 patients, diagnosed as having fatty ‎liver by abdominal ultrasonography at Tropical Medicine Department, Faculty of medicine, Zagazig ‎University from September 2021 to May 2022. Patients were classified as MAFLD with other chronic ‎liver disease (HCV, HBV) (G2), and MAFLD without other chronic liver disease (G1).‎

Inclusion Criteria:‎

MAFLD is diagnosed based on the presence of hepatic steatosis detected by ultrasonography, as ‎well as one of the three diseases listed below: 1- overweight/obesity, 2- diabetes mellitus (DM), or 3- ‎metabolic dysregulation. The presence of two or more of the following conditions was considered as ‎metabolic dysregulation: (a) Men's waist circumference > 102 cm, while women's waist circumference > ‎‎88 cm. (b) Blood pressure >130/85 mmHg or treatment with a specific medication. b) A TG of more ‎than 1.70 mmol/L (150 mg/dl) or a specific pharmacological therapy (d) Male HDL-C < 1.0 mmol/L (40 ‎mg/dl) and female HDL-C < 1.3 mmol/L (50 mg/dl). (e) Prediabetes (fasting glucose levels of 5.6 to 6.9 ‎mmol/L (100 mg/dl to 125 mg/dl) or 2-hour post-load glucose levels of 7.8-11.0 mmol/L (140 mg/dl to ‎‎199 mg/dl) or HbA1c of 5.7 to 6.4%).(f) C-reactive protein (CRP) level >2 mg/L [3].‎

Exclusion Criteria:‎

Hepatic decompensation, morbid obesity BMI>35 and presence of hepatocellular carcinoma

Operational design:‎

All cases were subjected to complete history taking included a history of alcohol consumption, ‎drug use. Comorbidities such as type 2 diabetes, ‎hypertension, and cardiovascular disease should also be identified. A comprehensive clinical ‎examination with measurement of blood pressure, weight, height and waist circumference was performed. Body mass ‎index (BMI) was calculated by dividing body weight (in kg) by the square of height (in meters).‎

Imaging investigations:‎

Abdominal Ultrasound was done to all patients. NAFLD suspected when sonographic features ‎unique to NAFLD are standardized as (bright liver echoes, increased hepatorenal echogenicity and ‎poor or no visualization of portal, hepatic vein or diaphragm) and hepatic steatosis grading was done ‎according to Hernaez et al. [9].‎

Biochemical assessment:‎

Complete Blood Count, Liver function tests including: bilirubin level, serum albumin, ALT, ‎AST. Kidney function tests including : serum creatinine and serum urea. Prothrombin time, INR. ‎Virological markers as HCV antibody, HBVsAg, HCV RNA by PCR. Alfa feto protein and Fasting ‎blood glucose (FBG) were done. Diagnosis of T2DM based on American Diabetes Association revised ‎criteria, using a value of fasting blood glucose 126 mg/dl or greater on at least 2 occasions, ‎postprandial blood glucose >200 mg/dl and glycosylated hemoglobin >6.5%. Lipid profile: Total ‎cholesterol (TC), triglycerides (TG), LDL cholesterol and HDL cholesterol. Serum fibrosis markers ‎include NAFLD fibrosis score (NFS) fibrosis 4 (FIB-4) and FLI(Fatty liver index) for hepatic steatosis were also done[10].‎

a- NAFLD fibrosis score = −1.675 + 0.037 – age (years) + 0.094 BMI (kg/m²) + 1.13 × [Impaired ‎FBG/DM (yes = 1, no = 0)] + 0.99 × AST/ALT ratio – 0.013× platelet count (×109/l) – 0.66 × albumin ‎‎(g/dl).‎

b- FIB-4 index = Age (years) × AST (U/L)/ [PLT (109/L) × ALT1/2 (U/L)].‎

c- FLI= (e0.953 × loge (triglycerides) + 0.139 × BMI + 0.718 × loge (GGT) + 0.053 × waist ‎circumference − 15.745)/(1 + e0.953 × loge (triglycerides) + 0.139 × BMI + 0.718 × loge (GGT) + ‎‎0.053 × waist circumference − 15.745) × 100.‎

Fibroscan was done for all patients for measuring LSM defined in KPa, CAP defined in dB/m, using ‎Fibroscan 502 (Echosens, Paris, France) device using two probes M+ and XL+.‎

Controlled attenuation parameter:‎

The controlled attenuation parameter (CAP) is a new physical parameter based on the ‎FibroScan's ultrasonic signal characteristics. At the M or XL probes, CAP measures ultrasonic ‎attenuation at the core frequency of Vibration-controlled transient elastography (VCTE).‎

Statistical analysis:

The collected data analyzed using SPSS program (Statistical Package for Social Sciences) ‎software version 26.0, Microsoft Excel 2016 and MedCalC program software version 19.1. Descriptive ‎statistics were done for numerical parametric data as mean ± SD and minimum & maximum of the range ‎and for numerical non parametric data as median and 1st& 3rd inter-quartile range, while they were ‎done for categorical data as number and percentage. Using independent t-test, Mann Whitney U, Chi ‎square test and Spearman's method. The ROC Curve to evaluate the Sensitivity and specificity for ‎quantitative diagnostic measures that categorize cases into one of two groups. Excellent accuracy =0.90 ‎to 1 (%), Good accuracy = 0.80 to 0.90 (%), Fair accuracy = 0.70 to 0.80 (%), Poor accuracy = 0.60 to ‎‎0.70 (%), Failed accuracy = 0.50 to 0.60 (%). The level of significance was taken at P value

RESULTS:

This study included 84 MAFLD patients, their age ranged from 23-69 years old, 63 males and 21 ‎females, classified as (group 1) MAFLD patients without chronic liver diseases, (group 2), MAFLD ‎patients with chronic liver diseases. HBV (6 patients), HCV(20 patients). 30 MAFLD patients were ‎hypertensive, 21 MAFLD patients were diabetics. BMI was 32.16 ± 2.7 kg/m2, waist circumference was ‎‎110.98 ±9.4 cm. Only 3 cases out of 84 patients have NFS >0.675 (3.6%), mean ± SD of FIBS score ‎was 1.27 ± 0.67 with 69% had FIB4 score less than 1.45 that indicates no fibrosis, none of our patients ‎has FIB4score >3.25. In this study, the mean ± SD of fatty liver index was 85.34 ± 12.55 with (80 ‎patients) 95.2% had FLI more than 60 that indicates fatty liver ruled in . AST, ALT and LDL were ‎independent risk factors for advanced fibrosis assessed by FIB-4. AST, ALT, uric acid and triglycerides ‎were independent risk factors for advanced fibrosis assessed by NFS .By using fibroscan ; the majority ‎of MAFLD patients had no or mild fibrosis (F0-F1 69%), while,16.9% had moderate fibrosis, and only ‎‎12 patients had advanced fibrosis (F3 9.5%, F4 4.8%). Most patients had marked hepatic steatosis as ‎demonstrated by CAP (S2, 31% at cutoff value 260-290 Db/m and S3 58.3% a cut off value >290 ‎dB/m). While 8,3% showed mild steatosis (S1 at cut off value 238-260 dB/m) (Table 1).‎

The present study showed a significant difference between the two studied groups regarding sex ‎‎(p=0.014) as females were more in group 1, compared to group 2. Age was significantly higher in group ‎‎2 compared to group 1. Group 2 showed significant prevalence of smoking compared to group ‎‎1.Abdominal distension was significant in group 1 (P<0.001) ,while most patients in group 2 were ‎asymptomatic (P<0.001). There was no significant difference between the two studied groups regarding ‎hypertension and DM (P>0.05). Waist circumference was significantly higher in group 2 compared to ‎group 1 (P=0.005). There was no significant difference between the two studied groups regarding ‎weight, height and BMI (P>0.05) (Table 2).‎

Regarding biochemical analysis, Group 1 showed significant increase in platelets count compared ‎to group 2 (P=0.002). Group 2 showed significant increase in INR compared to group 1 (P=0.005) ‎‎.Group 2 showed significant increase in fasting blood sugar, postprandial blood sugar and HbA1c ‎compared to group 1 (p=0.015, 0.004 & 0.013 respectively). There was no significant difference ‎between the two studied groups regarding urea, creatinine and uric acid (P>0.05). (Table 3).‎

Both NFS and FIB4 were significantly higher in group2 compared to group 1, however there was ‎no significant difference between the two studied groups regarding FLI (Table 4).‎

Regarding fibrosis reading and CAP, fibrosis score reading was significantly higher in group 2 ‎compared to group 1 (P<0.001). There was no statistically significant difference between steatosis in ‎the two studied groups regarding CAP (P>0.05) (Table 5).‎

There was significant negative correlation between CAP with total bilirubin, direct bilirubin and ‎HDL and positive correlation with triglyceride(r=0.348,p=0.001) .Also, there was significant positive ‎correlation between CAP with waist circumference (r= 0.270, p=0.013) and BMI (r= 0.246, p=0.024) ‎‎(Data not shown). However the results of multivariate analysis showed that steatosis had no significant ‎association between the parameters mentioned (Table 6).‎

There was no significant correlation between fibrosis and steatosis detected by fibroscan (r= ‎‎0.130,p= o.238). The results of multivariate analysis showed that AST, ALT, platelets, cholesterol and ‎LDL were independent risk factors for fibrosis detected by fibroscan (Table7).‎

At cut off value of 6.3 Kpa TE has the highest sensitivity, specificity and accuracy to detect ‎fibrosis (80.8%%, 81%,83% respectively) in MAFLD patients .The diagnostic accuracy of FLI in ‎disease staging in MAFLD patients was 87% at cut off value >88.29 with sensitivity and specificity of ‎‎88.5%, 80.7% respectively .The diagnostic accuracy of CAP in disease staging in MAFLD patients ‎was 88% at cut off value of >297 dB/m with sensitivity 88.5% and specificity 82.8. The diagnostic ‎accuracy of combined CAP and FLI for diagnosis of liver steatosis was 95%. with sensitivity 96.2% ‎and specificity 87.7% % (Table 8).‎

Table (1): Distribution of the studied cases as FIB4,NFS, Fatty liver index (FLI) , fibrosis and CAP reading by fibroscan.

Test	No
FIB4
<1.45	58
(1.45-3.25)	26
>3.25	0
NFS
<-1.455	38
(-1.455-0.675)	43
>(0.675)	3
FLI
(<30)	0
(30-60)	4
(>60)	80
Fibrosis
F0-F1(2-7)	58
F2(7.5-10)	14
F3(10-14)	8
F4>14	4
CAP
S0(<238)	2
SI(238-260)	7
S2(260-290)	26
S3(>290)	49

Table (2): Comparison between the two studied groups regarding demographic characteristics & Clinical data.

			Group (1) (No. = 58)				Group (2) (No. = 26)				Test value		P-value
			N		%		n		%
Sex	Male		39		67.2%		24		92.3%		X²= 6.02		0.014
	Female		19		32.8%		2		7.7%
Age (years)	Mean± SD		44.26± 11.89				50.42± 6.96				T = 2.97		0.004
	Median		42.50				51.5
	Range		23.0 – 69.0				37.0 - 68.0
Smoking	No		37		63.8%		9		34.6%		X²= 6.17		0.013
	Yes		21		36.2%		17		65.4%
Alcohol intake	No		58		100.0%		26		100.0%		NA		NA
	Yes		0		0.0%		0		0.0%
Clinical symptoms	Asymptomatic		9		15.5%		14		53.8%
	Fatigue
	32		55.2%		15		57.7%
	Heart burn
	28		48.3%		13		50.0%
Abdominal distension
49		84.5%		12		46.2%
Cardiac symptoms
5		8.6%		2		7.7%
Hypertension
	No		38		65.5%		16		61.5%
Yes
20		34.5%		10		38.5%
DM	No		36		62.1%		6		23.1%
	Prediabetic
	10		17.2%		11		42.3%
Diabetic		12		20.7%		9		34.6%
HBsAg	Negative		58		100.0%		20		76.9%
	Positive
0		0.0%		6		23.1%
HCV Ab.	Negative		58		100.0%		6		23.1%
	Positive
0		0.0%		20		76.9%
Other clinical numerical parameters
		Group (1) (No. = 58)				Group (2) (No. = 26)						Test value		P-value
		Mean	± SD	Median		Mean		± SD		Median
Weight (Kg)		92.78	8.83	92.50		97.04		9.98		99.00		T= 1.96		0.053
Height (cm)		170.81	7.40	171.00		171.85		5.81		171.50		T= 0.631		0.530
BMI (Kg/m²)		31.85	2.72	31.80		32.85		2.61		33.90		Z MWU= 1.61		0.108
Waist circumference (cm)		109.07	9.52	108.00		115.25		7.75		118.00		Z MWU=2.799		0.005

P≤0.05 is considered statistically significant, p≤0.01 is considered high statistically significant, SD= standard deviation, comparison between groups done by Student T test, Mann-Whitney U test and Chi- Square test

Table (3): Comparison between the two studied groups regarding renal function tests and other laboratory tests.

	Group (1) (No. = 58)			Group (2) (No. = 26)			Test value	P-value
	Mean	± SD	Median	Mean	± SD	Median	Test value	P-value
Urea (mg/dL)	39.50	10.52	37.00	39.88	11.15	37.50	ZMWU= 0.272	0.786
Creatinine(mg/dL)	.98	.17	.90	1.06	.23	.95	ZMWU= 1.442	0.149
Uric Acid (mg/dL)	5.07	1.01	5.10	5.40	1.08	5.60	T= 1.360	0.177
F.B.S(mg/dL)	106.09	30.52	92.00	131.08	44.09	121.50	ZMWU= 2.432	0.015
PostPrandial BS(mg/dL)	158.28	63.27	129.00	211.31	90.13	188.00	ZMWU= 2.89	0.004
HBA1C	5.64	0.81	5.40	6.19	0.81	6.10	ZMWU= 2.484	0.013

p≤0.05 is considered statistically significant, p≤0.01 is considered highly statistically significant Z: Mann-Whitnney U Test , T: Student T Test. SD: standard deviation.

Table (4): Comparison between the two studied groups regarding FIB4, NFS and fatty liver index.

	Group (1) No. = 58		Group (2) No. = 26		Test value	P value
FIB4
	Mean + SD	Median	Mean + SD	Median	Test value	P value
	1.10 + 0.52	0.98	1.64 + 0.81	1.44	ZMWU= 2.94	0.003
	No.	%	No.	%
FIB4 (<1.45)	45	77.6	13	50.0	X²= 5.167	0.023
FIB4 (1.45-3.25)	13	22.4	13	50.0
FIB4 (>3.25)	0	0.0	0	0.0
NFS
	Mean + SD	Median	Mean + SD	Median	Test value	P value
	-1.58 + 1.28	-1.94	-0.47+ 1.18	-0.33	T= 4.66	<0.001
	No.	%	No.	%
NFS (<-1.455)	33	56.9	5	19.2	X²= 14.716	0.001
NFS (-1.455-0.675)	25	43.1	18	69.2
NFS (>0.675)	0	0.0	3	11.5
Fatty liver index
	Mean + SD	Median	Mean + SD	Median	Test value	P value
	83.91 + 13.42	89.89	88.55 + 9.83	91.94	ZMWU= 1.113	0.266

Table (5): Comparison between the two studied groups regarding fibrosis reading and CAP.

	Group (1) (No. = 58)		Group (2) (No. = 26)		Test value	P-value
Fibrosis reading
	Mean ± SD	Median	Mean ± SD	Median	Test value	P-value
	5.31± 2.21	4.60	9.11± 3.97	8.45	ZMWU= 4.875	<0.001
	No.	%	No.	%
F0-F1 (2-7)	49	84.5%	9	34.6%	X2= 24.44	<0.001
F2 (7.5-10)	7	12.1%	7	26.9%
F3(10-14)	1	1.7%	7	26.9%
F4 (>14)	1	1.7%	3	11.5%
CAP
	Mean ± SD	Median	Mean ± SD	Median	Test value	P-value
	307.79± 49.96	295.5	290.69± 53.47	301.5	ZMWU= 0.561	0.575
	No.	%	No.	%
S0 (	0	6.9%	2	7.7%	X2= 6.473	0.091
S1 (238-260)	5	8.6%	2	7.7%
S2 (260-290)	21	36.2%	5	19.2%
S3 (>290 )	32	55.2%	17	65.4%

p≤0.05 is considered statistically significant, p≤0.01 is considered highly statistically significant Z Mann-Whitney U Test, T: Student T Test. X2:Chi- Square test, SD: standard deviation

Table (6): Multivariate regression analysis for steatosis.

Parameters	B	S.E	Wald	P-value	Odds ratio (OR)	95% CI
Parameters	B	S.E	Wald	P-value	Odds ratio (OR)	Lower limit	Upper limit
ALT	.010	.026	.142	.707	1.010	.959	1.064
AST	.016	.037	.193	.660	1.016	.946	1.092
T. bilirubin	-4.368-	2.899	2.270	.132	.013	.000	3.719
D. bilirubin	-1.363-	4.886	.078	.780	.256	.000	3688.663
GGT	.000	.030	.000	.996	1.000	.944	1.060
Albumin	1.836	1.308	1.970	0.160	6.274	.483	81.516
INR	-.857-	3.059	.079	.79	.424	.001	170.385
Urea	-.049-	.033	2.154	.142	.952	.892	1.016
Creatinine	-1.466-	1.896	.598	.439	.231	.006	9.481
Uric acid	-.474-	.326	2.113	.146	.622	.328	1.180
HB	-.007-	.228	.001	.976	.993	.636	1.552
TLC	-.126-	.141	.794	.373	.882	.669	1.163
Platelets	-.004-	.005	.534	.465	.996	.985	1.007
Cholesterol	-.012-	.013	.963	.326	.988	.963	1.013
Triglycerides	-.007-	.006	1.157	.282	.993	.981	1.006
LDL	.022	.013	3.005	.083	1.022	.997	1.048
HDL	-.087-	.047	3.389	.066	.917	.836	1.006
SBP	-.017-	.027	.399	.527	.983	.933	1.036
DBP	.007	.031	.053	.817	1.007	.948	1.070
F.B.S	.081	.046	3.125	.077	1.085	.991	1.187
P.P.B.S	-.006-	.021	.082	.775	.994	.955	1.035
HBA1C	-1.712-	1.101	2.417	.120	.180	.021	1.563
Waist circumference	.015	.061	.058	.810	1.015	.901	1.142
BMI	.224	.184	1.490	.222	1.251	.873	1.793

Table (7): Multivariate regression analysis for fibrosis detected by fibroscan in MAFLD patients.

Parameters	B	S.E	Wald	P-value	Odds ratio (OR)	95% CI
Parameters	B	S.E	Wald	P-value	Odds ratio (OR)	Lower limit	Upper limit
ALT	-.82-	.037	4.939	.026	.921	.857	.990
AST	.093	.041	5.322	.021	1.098	1.014	1.189
T. bilirubin	.538	3.156	.029	.865	1.713	.004	831.577
D. bilirubin	-2.191-	5.949	.136	.70.	.112	.000	12960.143
GGT	.041	.028	2.105	.147	1.042	.986	1.101
Albumin	1.240	1.244	.993	.319	3.454	.302	39.547
INR	1.631	1.895	.741	.389	5.108	.125	209.436
Urea	.009	.032	.086	.769	1.009	.948	1.075
Creatinine	2.612	1.879	1.932	.165	13.626	.343	541.793
Uric acid	-.133-	.307	.188	.665	.875	.479	1.599
HB	-.028-	.239	.014	.905	.972	.608	1.553
TLC	.125	.147	.729	.393	1.134	.850	1.512
Platelets	.031	.010	10.428	.001	.969	.951	.988
Cholesterol	.178	.068	6.903	.009	.837	.732	.956
Triglycerides	.022	.012	3.315	.069	1.002	.998	1.046
LDL	.155	.072	4.648	.031	.856	.744	.986
HDL	-.017-	.032	.266	.606	.983	.923	1.048
Systolic pressure	-.001-	.028	.002	.965	.999	.946	1.055
Diastolic pressure	-.042-	.039	1.158	.282	.959	.889	1.035
F.B.S	-.007-	.036	.033	.855	.993	.925	1.067
P.P.B.S	.006	.016	.129	.720	1.006	.974	1.039
HBA1C	.381	.891	.182	.669	1.463	.255	8.393
Waist circumference	.062	.067	.867	.352	1.064	.934	1.212
BMI	-.025	.243	.011	.917	.975	.605	1.571

B: Regression coefficient; S.E.: Standard error,, CI: Confidence interval

Table (8): Diagnostic accuracy of FLI & CAP in disease staging in MAFLD patients

Parameter	Cutoff value	AUC	Sensitivity	Specificity	PPV	NPV	Accuracy	P value
FLI	>88.29	0.866	88.5%	80.7%	82.1%	87.5%	87%	<0.001
CAP	>297	0.878	88.5%	82.8%	83.7%	87.8%	88%	<0.001
CAP+ FLI		0.947	96.2%	87.7%	88.7%	95.8%	95.0%	<0.001

PPV= Positive Predictive Value, NPV= Negative Predictive Value, AUC= Area Under Curve

DISCUSSION

NAFLD is one of the world's most frequent chronic liver illnesses. MAFLD is a new concept that may help clinicians identify patients who are more likely to have a negative result [3,11].

The reference standard for the detection of NAFLD and the assessment of NAFLD-related pathological abnormalities such as the degree of steatosis and liver fibrosis is often liver biopsy [5]. However, there are well-known disadvantages to liver biopsy. Noninvasive laboratory and radiographic assessment methods for hepatic steatosis and fibrosis in NAFLD have evolved, which may help overcome the limitations of liver biopsy, such as the FIB4, APRI score, FLI, and NFS, as well as radiological methods such as Transient elastography [6].

In this study, the mean ± SD of age was 46.17± 10.95 years. Age was significantly higher in group 2 compared to group 1 (P=0.004). 63 (75%) cases were males and 21 (25%) were females. There was significant difference between the two studied groups regarding sex (P=0.014) as females was significantly more in group 1 compared to group 2. These findings are in agreement with Taheri et al. [12] as the mean ± SD of the patients age was 43.5 ± 12.7 years. Also, Yuan et al. [13] reported that ,there was significant difference between males and females (36.80% vs. 28.65%, P<0.001). The prevalence of MAFLD in males and females both increased with age (P<0.001) also, NAFLD is prevalent among male gender.

In the current study, the average weight, BMI were 94.10 ± 9.36 Kg, and 32.16 ± 2.71 Kg/m² respectively. There was no significant difference between the two studied groups regarding weight, and BMI (P>0.05). Waist circumference were 110.98 ± 9.41 cm and was significantly higher in group 2 compared to group 1 (P=0.005). De ledinghen and Vergniol [14] revealed that high BMI and WC are the main obesity indices and risk factor for NAFLD. In addition, WC had the greatest power to predict fatty liver and correlated with the severity of fatty liver [15].

Also, Mansour et al.[16] showed that the mean ± SD of BMI of MAFLD patients was 35.59 ± 5.77 Kg/m² and waist circumference (cm) 109.44 ± 11.54 as, MAFLD is tightly linked to the weight and metabolic syndrome, in addition, there was a statistically significant positive correlation between hepatic steatosis and, fibrosis with BMI, WC. In addition, Hu et al. [17] showed that BMI was higher in the NAFLD group than in the non-NAFLD group.

On the other hand Yuan et al. [13] found that, in the general population, 3.72% had non obese MAFLD. The lean/normal weight MAFLD group had a female predominance than the non-MAFLD group.

Abdominal distension was significantly higher in group 1 (P<0.001), while most patients in group 2 were asymptomatic (P<0.001), while there was no significant difference between the two studied groups regarding fatigue, heart burn and cardiac symptoms (P>0.05).

NAFLD seems frequently asymptomatic at diagnosis, feeling of fullness, discomfort in right upper abdomen and malaise are reported in many cases, NAFLD is detected on doing ultrasonography or performing investigation for other aliments [18].

Regarding comorbidities, 35.7% were hypertensive, 25% were prediabetics and 25% were diabetics. There was no significant difference between the two studied groups regarding hypertension and DM (P>0.05). Group 2 showed significant increase in fasting blood sugar, postprandial blood and HbA1c compared to group 1 (p=0.015, 0.004 & 0.013 respectively) as hepatitis C virus and hepatitis B virus are associated with insulin resistance and more diabetes prevalence [19].

Also, Taheri et al., (2021) [12], reported that the incidence of diabetes, hypertension, and cardiovascular disease was higher in the NAFLD group than in the non-NAFLD group, and the differences were statistically significant (PYuan et al. (2022) [13] reported that the prevalence of hypertension and DM in lean/normal weight MAFLD participants was higher than that in non-MAFLD participants.

In addition, Jiaofeng et al. 2021 [20] recorded that, 28.65% of MAFLD patients had diabetes, and 35.8% had hypertension and this is in line with this study as MAFLD patients may have one or more metabolic conditions.

In this study MAFLD with HCV patients were 20 patients (23.8%) and MAFLD with HBV were 6 patients (7.1%) . Those patients were classified before as viral hepatitis rather than MAFLD; it was found that steatosis occur more frequently with chronic hepatitis C (55%) than in general population (20-30%). This may be due to insulin resistance associated with HCV or viral factor like core antigen. Also HBV commonly associated with steatosis (41%) due to insulin resistance and viral factor like x antigen and poly morphism in interleukin 28B which may affect lipid metabolism [21].

Huang et al. 2021 [20] reported that in between 4087 patients with MAFLD there was ninety patients with HCV and, 17 with HBV, this may be due to geographic difference and prevalence of HCV, HBV.

In the present study, the mean ± SD ALT was 46.48± 33.65 U/L.Normal levels of liver enzymes have been demonstrated in 80% NAFLD patients [22].

In the present study, Group 1 showed significant increase in platelets count compared to group 2(p=0.002), but still within normal range as majority of our patients has no or mild fibrosis as the prevalence and degree of thrombocytopenia increase with severity of chronic liver disease and fibrosis. It may be due to extrahepatic manifestation to HBV, HCV, antiplatelet antibodies, bone marrow suppression or hypersplenism [23].

This study revealed that the mean ± SD FIBS score was 1.27± 0.67 with 69% had FIB4 score less than 1.45 that indicates no fibrosis, none of our patients has FIB4score >3.25 . Mean ± SD FIBS score was significantly higher in group 2 compared to group 1 (p=0.003).

As regards NFS, in this study only 3 cases out of 84 patients have NFS > 0.675 (3.6%). NFS Mean ± SD was significantly higher in group 2 compared to group 1 (p<0.001) with increasing score level in group 2 (P=0.001). As MAFLD patients associated with chronic HCV, HBV liver disease had higher grade of fibrosis ; those patients have multiple risk factors for fibrosis [24].

In this study, the mean ± SD of fatty liver index was 85.34± 12.55 with(80 patients) 95.2% had FLI more than 60 that indicates fatty liver ruled in. There was no significant difference between the two studied groups regarding fatty liver index (p>0.05). This finding is consistent with Motamed et al. 2016 [25] who revealed a significant positive high correlation between serum FLI and NAFLD, which was also confirmed by binary regression, to the point where a one-unit increase in FLI resulted in a 5.8% increase in the risk of developing NAFLD and showed good predictive performance in the diagnosis of NAFLD.

The present study revealed that, Fibrosis reading using fibroscan ;the majority of MAFLD patients had no or mild fibrosis (F0-F1 69%),while,16.9% had moderate fibrosis,and only 12 patients had advanced fibrosis (F39.5%, F4 4.8%) and these results agreed with Mansour et al. (2020) [16] who found that most of NAFLD patients had mild liver fibrosis [F0: 52 (57.78%), F1: 20 (22.22%)], while 16 patients had moderate fibrosis [F2: 16 (17.78%)], and only 2 patients had advanced fibrosis [F4:2 (2.22%)].

While, Fallatah et al.2016 [26] who evaluated in 122 Saudi patients with NAFLD, the role of FibroScan vs. various non-invasive evaluation scores was investigated. In his study, FibroScan identified advanced liver fibrosis in a considerable number of people [F4: 40 (32.8 percent)]. This could be due to demographic variations between patients in two studies, where his patients have a high prevalence of metabolic syndrome and type 2 diabetes, which could explain progressive fibrosis. Fibroscan revealed AST, ALT, platelets, cholesterol, and LDL as independent risk factors for fibrosis. Pathik et al .2015 [27] reported the platelet count may be a biomarker of the severity of liver fibrosis in NAFLD patients, with a high statistical correlation between liver transaminases and increased LMS indicative of liver fibrosis [28].

In the present study, there was no significant correlation between fibrosis detected by fibroscan and steatosis (r= 0.130, p=0.238), as the association between steatosis and fibrosis invariably dependent on simultaneous association between steatosis, and hepatic inflammation as hepatic inflammation may mediate fibrogenesis [29]

In terms of CAP, in this study, 82 out of 84 patients exhibited steatosis, with the majority of patients having severe hepatic steatosis as seen by CAP (S2, 31 percent at 260-290 Db/m, and S3 58.3 percent at >290 dB/m). while 8.3% had moderate steatosis (S1 at 238-260 dB/m cut-off value). Ahn et al. 2016 [30] reported that CAP can distinguish between the different grades of steatosis, however, Chon et al. 2014 considered that it is less accurate and has greater diagnostic value for S1 and S2. However, this problem of CAP in obese individuals was overcome by using the X probe. [33].

There was significant negative correlation between CAP with total bilirubin, and HDL .Also, there was significant positive correlation between CAP and waist circumference (r= 0.270, p=0.013), positive correlation with triglyceride(r=0.348,p=0.001) and BMI (r= 0.246, p=0.024) ‎‎(Data not shown). However the results of multivariate analysis showed that steatosis had no significant ‎association between the parameters mentioned.AS BMI,WC are the major obesity indices and strong risk factors for NAFLD, with a 66 percent rise in NAFLD in obese people [33]. This is in line with the findings of Dehnavi et al. 2018 [31] who reported that BMI, WC, and steatosis grades were demonstrated to have a highly significant association in between.

In this study the diagnostic accuracy of CAP in disease staging in MAFLD patients is 88% at cut off value of>297dB/m with sensitivity 88.5% and specificity 82.8%.This was in agreement with Eddowes et al .2019 [32], who assessed the diagnostic accuracy of CAP by TE for evaluating liver steatosis in NAFLD patients with AUROC of 0.87,sensitivity of 80% and specificity of 83%. While, Chon et al. [33] found that the sensitivity and specificity of CAP for S1 at cut off 250 dB/m were 73.1% and 95.2% respectively for detection of S2 at cut off 299 dB/m were82.4%,86.1 respectively and for S3 at cut off 327dB/m were 77.8%,84.1 respectively, difference may be due to variation in geographical region.

CAP has the ability to detect hepatic steatosis with >5% steatosis on histology [34]. Here the possibility to assess concomitant fibrosis and steatosis using CAP make TE a promising noninvasive tool for assessment and quantifying of both steatosis and fibrosis in MAFLD patients [16,35]

In this study, diagnostic accuracy of FLI in disease staging in MAFLD patients is 87% at cut off value >88.29 with sensitivity and specificity of 88.5%,80.7% respectively. Score of FLI varies from zero to 100 and at cut off value of >60,sensitivity and specifity were 86%, 87% respectively, FLI is also, independently associated with cardiovascular and cancer related mortality [36].

In the present study the diagnostic accuracy of combined CAP and FLI for diagnosis of liver steatosis was 95%. with sensitivity 96.2% and specificity 87.7%,

So, combination of both noninvasive imaging technique and laboratory score may improve the diagnostic accuracy in assessing steatosis in MAFLD patients ,which may add to CAP, as FLI is independently associated with overall ,cardiovascular and cancer related mortality [37].

CONCLUSION

CAP could be a promising noninvasive tool for assessing and quantifying steatosis in MAFLD patients. Combining noninvasive imaging with a laboratory score could increase diagnostic accuracy in assessing steatosis in MAFLD patients, which could be beneficial to CAP.

No Conflict of interest.

Funding:Non.

Ethical considerations :Prior to the study's execution, the Ethical Committee of Zagazig University's Faculty of Medicine gave its approval (IRB no. 7092-7-9-2021 ). After a thorough description of the study's objectives and methodology, all participants were asked to sign a written informed consent form. The study conformed with the guidelines of the Helsinki Declaration.

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