Copyright: ©Author(s) 2026.
World J Hepatol. Mar 27, 2026; 18(3): 117465
Published online Mar 27, 2026. doi: 10.4254/wjh.v18.i3.117465
Published online Mar 27, 2026. doi: 10.4254/wjh.v18.i3.117465
Table 2 Comparison of baseline characteristics and biochemical parameters between the training and validation cohorts, n (%)
| Parameters | Training dataset (n = 214) | Validation dataset (n = 102) | P value |
| Group | 0.815 | ||
| F0-F1 | 106 (49.5) | 49 (48) | |
| F2 | 36 (16.8) | 21 (20.5) | |
| F3 | 38 (17.8) | 18 (17.6) | |
| F4 | 34 (15.9) | 14 (13.7) | |
| Gender | 0.994 | ||
| Males | 109 (50.9) | 52 (51) | |
| Females | 105 (49.1) | 50 (49) | |
| Age (years) | 46.88 ± 13.5 | 47.12 ± 11.6 | 0.871 |
| Body mass index | 23.86 ± 3.44 | 24.01 ± 3.39 | 0.715 |
| Diabetes | 0.70 | ||
| Yes | 30 (14) | 16 (15.6) | |
| No | 184 (86) | 86 (84.3) | |
| Platelet count (× 109/L) | 145.44 ± 30.83 | 144.1 ± 29.2 | 0.708 |
| Bilirubin (mg/dL) | 0.75 ± 0.26 | 0.756 ± 0.27 | 0.852 |
| AST (U/L) | 36 (25, 60) | 40 (25, 63) | 0.55 |
| ALT (U/L) | 42 (23, 47) | 39 (25, 51) | 0.66 |
| GGT (U/L) | 34 (21, 55) | 36 (20, 53) | 0.90 |
| ALP (U/L) | 59 (48, 77) | 63.7 (54, 80) | 0.07 |
| Serum albumin (g/dL) | 3.53 ± 0.26 | 3.57 ± 0.33 | 0.284 |
| Total protein (g/dL) | 7.02 ± 1.21 | 7.01 ± 1.13 | 0.943 |
| Total cholesterol (mg/dL) | 148.33 ± 19.12 | 146.6 ± 22.61 | 0.505 |
| Triglycerides (mg/dL) | 128 (111, 167) | 133.2 (112, 174) | 0.38 |
| HDL (mg/dL) | 35 (27, 43) | 31.9 (25, 48) | 0.98 |
| LDL (mg/dL) | 80.11 ± 14.3 | 78.33 ± 15.2 | 0.323 |
| VLDL (mg/dL) | 24.32 ± 11.16 | 23.89 ± 17.68 | 0.822 |
- Citation: Bashir A, Arora R, Mehrotra D, Bala M, Parry AH, Iqball A, Bhat SA, Wani ZA. Non-invasive prediction of significant hepatic fibrosis in individuals with chronic hepatitis C infection using fibrosis risk score and machine learning models. World J Hepatol 2026; 18(3): 117465
- URL: https://www.wjgnet.com/1948-5182/full/v18/i3/117465.htm
- DOI: https://dx.doi.org/10.4254/wjh.v18.i3.117465