A retrospective, analytic, observational study was conducted, utilizing nonrandomized sampling. To guarantee diagnostic accuracy, the STARD list was applied.

During 2020, a project for evaluating “fatty liver” was carried out in the Mexican city of Veracruz.12 The program involved 585 individuals from the general population. The participants had no known liver disease and did not have significant alcohol use, nor did they use drugs that could be associated with steatosis. The program consisted of a detailed clinical and biochemical evaluation. In addition, the FIB-4 index score was calculated for all the participants. The individuals with scores indicating a high or indeterminate risk for liver fibrosis were selected for a more in-depth evaluation through transient liver elastography (TLE), employing FibroScan® equipment.

Our study focused specifically on Mexican individuals, all of whom were above 18 years of age and residing in Veracruz, Mexico, and who completed the TLE study within the time frame of the program. In the selection process, only the medical records that were complete and contained a written statement of informed consent were chosen. Records with incomplete or missing information were not included (Fig. 1).

Figure 1.

Flow diagram showing the selection process of the participants.

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Importantly, two gastroenterologists and a clinical nutritionist carried out the TLE; they had the relevant certifications and solid experience in the elastography technique. A certified hepatologist was consulted regarding the interpretation of the results.

The variables of weight (kg), height (cm), body mass index (BMI), amount of visceral fat (l) and fat mass (l) were obtained using SECA mBCA514 bioimpedance anthropometry equipment.22

The clinical and biochemical parameters were obtained from the medical records of the participants and included the pathologic personal history and different biochemical parameters, such as leukocytes, hemoglobin, hematocrit, creatinine, urea, uric acid, total bilirubin (TB), alkaline phosphatase (ALP), HDL, low-density lipoprotein (LDL), AST, alanine aminotransferase (ALT), triglycerides, total cholesterol, and the homeostatic model assessment for insulin resistance (HOMA-IR).23

TLE was used as the reference method for the evaluation of liver fibrosis and steatosis. Liver stiffness was quantified and expressed in kilopascals (kPa). We established a cutoff point with the controlled attenuation parameter (CAP) with a median of ≥ 248 db/m for identifying the presence of steatosis.24 A cutoff point of ≥ 12.1 kPA was utilized to categorize liver fibrosis.21

The diagnosis of MASLD was based on international consensus criteria, considering individuals that showed liver steatosis through TLE. Diagnosis required the presence of at least one of the following metabolic criteria: BMI ≥ 25 kg/m² or a waist circumference ≥ 94 cm; fasting serum glucose ≥ 100 mg/dl or 2 h post-load glucose levels ≥ 140 mg/dl, or treatment for type 2 diabetes; blood pressure ≥ 130/85 mmHg or specific treatment for high blood pressure; plasma triglycerides ≥ 150 mg/dl or lipid lowering treatment; plasma HDL cholesterol ≤ 40 mg/dl in men and ≤ 50 mg/dl in women, or lipid lowering treatment.3

The APRI, FIB-4, HFS, and NFS were the four noninvasive scores employed. The following formulas were utilized to calculate the scores: APRI: (AST/LSN) x 100/platelets(109/l);17 FIB-4: age × AST (U/l)/platelets (109/l) x √ALT (U/l);21 NFS: −1.675 + 0.037 – age + 0.094 – BMI (kg/m2) + 1.13 × IR/diabetes (yes = 1, no = 0) + 0.99 × AST/ALT ratio – 0.013 × platelet count (×109/l) – 0.66 × albumin (g/dl);17 HFS: 1 / (1 + e (5.390 − 0.986 x age [45-64] – 1.719 x age [>65] + 0.875 x male sex – 0.896 x AST [35-69 IU/l] – 2.126 x AST [> 70 IU/l] – 0.027 x albumin [4-4.49 g/dl] – 0.897 x albumin [4 with no diabetes mellitus] – 2.184 x diabetes mellitus – 0.882 x platelets x 1.000/microl [155-219] – 2.233 x platelets x 1.000/microl [< 155]).25

The distribution of the data was evaluated through the Kolmogorov-Smirnov test and the Levene’s test of homoscedasticity. The numerical variables were expressed as mean ± standard deviation or median with interquartile range and compared using the corresponding Student’s t test or Wilcoxon test. The categorical variables were expressed as frequencies and percentages and compared using the chi-square test or the Fisher’s exact test. The correlations were made with the Pearson or Spearman correlation coefficients. Receiver operating characteristic (ROC) curves were utilized to determine the area under the curve (AUC) of each score, whereas sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratio (LR) were calculated using the Youden index. Statistical significance was set at a p < 0.05 and the data analysis was carried out using the R Studio version 4.2.0 and SPSS® version 25 programs.

All study participants provided their written statements of informed consent, which were reviewed and approved by the Research and Ethics Committee of our institution (folio llMB-007-2020) before their incorporation. The study strictly followed the official data protection regulations and ethical principles established in the Declaration of Helsinki, at no monetary expense to the participants. All participants received the study results, with the option to receive free medical and/or nutritional counseling if they so desired. The data of the participants was handled with strict confidentiality and security measures, including de-identification, and access was restricted to authorized personnel. The participants had the right to withdraw from the study at any time, with no penalization.

A total of 194 subjects were included in the study; 129 (66.5%) were women and 65 (33.5%) were men. Median patient age was 55 years (IQR 48-65). Based on the CAP, 150 (77.3%) of the participants were categorized as having MASLD, with a predominance of women and a median patient age of 55 years (IQR 47.7-64). Forty-four (22.7%) of the participants were classified as having no liver disease. Table 1 provides a detailed summary of the sociodemographic and epidemiologic characteristics of the participants.

Of the 150 subjects diagnosed with MASLD, 15.3% (n = 23) were classified with advanced liver fibrosis (kPa ≥ 12.1). Compared with the individuals with no fibrosis, those with liver fibrosis had significantly higher kPa (17.1 [14.2-25.5] vs 5.4 [4.4-6.3], p < 0.0001) and waist circumference (107.5 [98-118] vs 100.5 [90.5-109], p = 0.013). No statistically significant differences were observed regarding age (62 [52-67] vs 55 [46-64], p = 0.126), BMI (33.2 [30-37.7] vs 31.3 [27.9-34.4], p = 0.141), visceral fat (3.85 [2.95-5] vs 3.4 [2.6-4.5], p = 0.275), or CAP (323 [283-339] vs 307 [279-337], p = 0.652).

With respect to educational level, there were significant differences (p = 0.031) between the groups with and without fibrosis, with a lower educational level in the liver fibrosis group. There was also a higher prevalence of history of type 2 diabetes mellitus (56.5% vs 33.9%, p = 0.039) and high blood pressure (69.6% vs 33.9%, p = 0.009) in the fibrosis group. Table 1 provides detailed distributions of these and other sociodemographic characteristics.

In the subjects diagnosed with MASLD, those with liver fibrosis had significant biochemical differences, compared with the subjects with no fibrosis. In the fibrosis group, elevated levels of fasting glucose (114 [91-182] vs 95 [89-103], p < 0.0001) and AST (49 [37-66] vs 32 [26-41], p = 0.0020) were observed. On the other hand, that group had lower LDL (97.1 ± 31 vs 115 ± 32.1, p = 0.015), total cholesterol (183.6 ± 41.4 vs 204 ± 36.2, p = 0.008), albumin (4 [3.5-4.2] vs 4.1 [3.9-4.2], p = 0.022), erythrocyte (4.37 [3.91-4.63] vs 4.5 [4.2-4.8], p = 0.001), hemoglobin (13.4 [12.6-14.4] vs 14 [13.3-15.1], p = 0.011), and platelet (188 [133-222] vs 213 [183-252], p = 0.002) levels, compared with the group with no liver fibrosis. Table 2 shows the comparisons of the rest of the biochemical variables.

The individuals diagnosed with MASLD and liver fibrosis showed significant increases in the scores calculated with the APRI (0.74 [0.51-1.2] vs 0.45 [0.34-0.62], p = 0.004), FIB-4 (2.37 [1.74-3.47] vs 1.57 [1.08-1.96], p = 0.007), and HFS (0.15 [0.06-0.58] vs 0.04 [0.01-0.10], p = 0.009), compared with the subjects with no fibrosis. Even though the score calculated with the NFS was higher in the individuals with MASLD and fibrosis (0.12 [-1.18-1.10] vs (-0.96 [-1.91- -0.12]), the difference was not statistically significant (p = 0.628).

The correlations between the kPa values and the scores calculated with the APRI, FIB-4, HFS, and NFS were (r = .445, p = 0.0001), (r = .230, p = 0.005), (r = .247, p = 0.002), and (r = .208, p = 0.011), respectively. In addition, all the scores had a moderate-to-strong correlation with each other.

Fig. 2 shows the ROC curves for the APRI, FIB-4, HFS, and NFS scores, describing the values of the AUC of 0.79, 0.80, 0.70, and 0.68, respectively. The cutoff points equivalent to ≥ 12.1 kPa in the elastography test for each of the following were: APRI: 0.56, FIB-4: 1.82, HFS: 0.08, and NFS: -0.54. Table 3 includes a summary of the cutoff points, sensitivity, specificity, PPV, NPV, and LR for each score.

Figure 2.

Diagnostic yield of FIB-4, APRI, HFS, and NFS for evaluating liver fibrosis in MASLD. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic yield of different noninvasive scores for liver fibrosis in subjects with metabolic dysfunction-associated steatotic liver disease (MASLD). Liver fibrosis was evaluated through transient liver elastography, with a threshold ≥ 12.1 kPa indicating the presence of fibrosis.

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