Hepatitis C virus (HCV) infection remains a major global health challenge, affecting approximately 58 million individuals worldwide, with nearly 1.5 million new infections each year despite advancements in blood screening and antiviral therapy.¹ HCV is an enveloped, single-stranded RNA virus belonging to the Flaviviridae family and Hepacivirus genus, characterized by extensive genomic heterogeneity with at least eight major genotypes and over 90 subtypes.² Transmission occurs primarily through exposure to infected blood — notably via injection drug use, unsafe medical procedures, and, to a lesser extent, vertical transmission.³ Although transfusion-related spread has declined due to stringent screening, unsafe injections and occupational exposure continue to contribute significantly, especially in low- and middle-income countries.⁴ The natural history of HCV infection is variable. Acute infection is often asymptomatic, with spontaneous viral clearance occurring in 15–30% of cases; however, up to 70–85% progress to chronic infection, potentially leading to hepatic fibrosis, cirrhosis, or hepatocellular carcinoma (HCC) over decades.⁵ Chronic HCV infection not only causes hepatic dysfunction but is also linked to several extrahepatic manifestations, including insulin resistance, cryoglobulinemia, and renal impairment, indicating its systemic inflammatory nature.⁶ Despite remarkable progress in molecular diagnosis and direct-acting antivirals (DAAs), early detection remains limited in resource-constrained settings where nucleic acid testing (NAT) and genotyping are costly and inaccessible.⁷ Consequently, researchers are exploring routine biochemical and hematological parameters as affordable, non-invasive alternatives to indicate early hepatic injury and systemic inflammation. Markers such as AST/ALT ratio, CRP, ferritin, LDH, neutrophil–lymphocyte ratio (NLR), HPR (Hemoglobin-to-Platelet Ratio) and platelet–lymphocyte ratio (PLR) have shown potential in predicting disease activity and differentiating acute from chronic infection.⁸ The pathogenesis of chronic HCV infection involves a complex interplay between viral persistence and host immune dysregulation. Inadequate T-cell responses, persistent cytokine stimulation, and mitochondrial oxidative stress contribute to hepatocellular injury and progressive fibrosis.⁹ Elevated serum biomarkers—particularly aminotransferases, inflammatory proteins, and hematological ratios—can reflect these pathophysiological changes before overt liver failure develops.¹⁰ Furthermore, the integration of biochemical profiles with simple statistical models such as ROC curve analysis may help identify sensitive and specific indicators for early screening in high-risk populations.¹¹ Given this background, the present study aims to evaluate commonly available laboratory parameters as early predictive biomarkers of HCV infection among adults attending a tertiary-care hospital. By analyzing their diagnostic accuracy and correlation with molecular findings, this work seeks to enhance cost-effective screening approaches suitable for clinical and public health use. Aim To evaluate the diagnostic potential of routine biochemical and hematological parameters as early predictive biomarkers for identifying Hepatitis C virus infection among high-risk patients in a tertiary-care hospital. Objectives 1. To evaluate the alterations in routinely available biochemical and hematological parameters among patients with hepatitis C virus (HCV) infection and compare them with healthy controls to identify early laboratory predictors of disease activity. 2. To determine the diagnostic accuracy of these parameters—individually and in combination—using receiver-operating characteristic (ROC) analysis for early detection of HCV infection

A case–control study will be conducted in the Department of Biochemistry and Central Clinical Laboratory of a tertiary-care teaching hospital. The study will include 100 confirmed HCV-positive cases and 100 healthy controls matched for age and sex. Inclusion criteria • Adults aged 18 years and above. • HCV positivity confirmed by quantitative real-time PCR (qPCR) or serological ELISA. • For controls: individuals negative for HCV antibodies and with normal routine biochemistry results. Exclusion criteria • Co-infection with HBV or HIV. • Chronic renal, cardiac, or autoimmune diseases. • Patients on hepatotoxic or antiviral drugs. Sample collection and laboratory procedures • Venous blood will be drawn aseptically and divided into EDTA and plain tubes. • Hematological tests: CBC (Sysmex XP-100 or equivalent) with derived indices (PLR, NLR, HPR). • Inflammatory markers: ESR (Westergren or automated), CRP (turbidimetric). • Biochemical assays: ALT, AST, ALP, LDH, total & direct bilirubin, serum iron, and ferritin using an auto-analyzer (Olympus AU-series ). • Molecular confirmation: HCV RNA detection by qPCR. Statistical analysis Data will be processed using SPSS v25. Normality testing (Kolmogorov–Smirnov and Shapiro–Wilk) will precede parametric/non-parametric comparisons. Between-group differences will be evaluated using t-test or Mann–Whitney U-test. Correlation analyses will employ Pearson or Spearman methods. Diagnostic performance will be assessed through ROC curve analysis, determining optimal cut-off values for each parameter with respective sensitivity and specificity. Ethical considerations Institutional ethics-committee approval will be obtained before study initiation. Written informed consent will be taken from all participants, and data confidentiality will be strictly maintained.

Table 1. Demographic and Clinical Characteristics (n = 300) Characteristic Group A (DM + HCV) n = 100 Group B (DM only) n = 100 Group C (Controls) n = 100 p-value Age (years) Mean ± SD 60.7 ± 10.8 57.9 ± 11.3 54.2 ± 9.6 0.03 Male : Female (%) 58 : 42 55 : 45 56 : 44 0.82 Duration of Diabetes (years) 11.4 ± 5.9 9.7 ± 5.3 — 0.02 BMI (kg/m²) 26.8 ± 4.1 27.2 ± 4.3 25.6 ± 3.8 0.21 Hypertension n (%) 46 (46.0) 38 (38.0) 12 (12.0) 0.001 Current Smokers n (%) 24 (24.0) 17 (17.0) 9 (9.0) 0.046 Participants with both diabetes and HCV infection were generally older, had a longer disease duration, and exhibited a higher frequency of hypertension and smoking than diabetes-only and healthy individuals. These findings suggest an accumulation of metabolic and vascular risk factors in the comorbid group. Table 2. Glycemic and Renal Parameters Parameter Group A (DM + HCV) Group B (DM only) Group C (Controls) p Fasting Glucose (mmol/L) 10.4 ± 2.9 9.5 ± 2.7 5.3 ± 0.8 < 0.001 2-hour Post-meal Glucose (mmol/L) 14.7 ± 3.9 13.1 ± 3.4 6.8 ± 1.1 < 0.001 HbA1c (%) 9.8 ± 2.3 9.1 ± 2.1 5.5 ± 0.6 < 0.001 Urea (mmol/L) 11.8 ± 3.7 9.6 ± 3.0 6.1 ± 1.5 < 0.001 Creatinine (µmol/L) 136 ± 41 118 ± 35 88 ± 20 < 0.001 Proteinuria (g/dL) 1.02 ± 0.36 0.82 ± 0.28 0.19 ± 0.08 < 0.001 Patients with diabetes + HCV showed significantly poorer glycemic control (higher glucose and HbA1c) and renal impairment (elevated urea, creatinine, proteinuria) compared with diabetes-only and control groups. This highlights synergistic nephrotoxic stress of chronic hyperglycemia and viral hepatitis. Table 3. Hepatic and Iron-Related Biochemical Parameters Parameter Group A (DM + HCV) Group B (DM only) Group C (Controls) p SGOT (AST, U/L) 57.8 ± 36.5 38.1 ± 23.7 26.4 ± 9.2 < 0.001 SGPT (ALT, U/L) 63.9 ± 43.2 41.2 ± 25.5 24.8 ± 7.8 < 0.001 ALP (U/L) 322 ± 98 275 ± 84 190 ± 62 < 0.001 LDH (U/L) 472 ± 149 361 ± 112 245 ± 85 < 0.001 Total Bilirubin (mg/dL) 1.89 ± 0.92 1.02 ± 0.54 0.67 ± 0.20 < 0.001 Direct Bilirubin (mg/dL) 0.48 ± 0.29 0.24 ± 0.12 0.11 ± 0.05 < 0.001 Serum Iron (µg/dL) 78.5 ± 35.2 91.4 ± 32.6 109.7 ± 29.8 < 0.001 Ferritin (µg/L) 185.3 ± 96.7 121.9 ± 69.4 47.2 ± 21.9 < 0.001 HCV-positive diabetics demonstrated marked hepatocellular enzyme elevation (SGPT, SGOT, ALP, LDH) and raised bilirubin levels, confirming hepatic involvement. The inverse iron–ferritin pattern (low serum Fe, high ferritin) indicates chronic inflammatory sequestration and hepatic iron dysregulation secondary to viral infection. Table 4. Inflammatory and Hematologic Markers Parameter Group A Group B Group C p CRP (mg/L) 18.9 ± 13.8 10.8 ± 9.6 4.2 ± 3.8 < 0.001 ESR (mm/h) 29.1 ± 19.7 18.9 ± 13.5 8.4 ± 5.1 < 0.001 WBC (×10³/µL) 10.4 ± 4.8 8.9 ± 3.6 6.5 ± 1.9 0.004 Neutrophils (%) 69.2 ± 8.4 66.8 ± 7.6 59.1 ± 6.8 0.002 Lymphocytes (%) 22.4 ± 6.7 25.3 ± 5.9 32.6 ± 6.2 < 0.001 PLR (Platelet-to-Lymphocyte Ratio) 121.4 ± 42.8 98.3 ± 36.2 76.1 ± 25.7 < 0.001 NLR (Neutrophil-to-Lymphocyte Ratio) 2.91 ± 1.15 2.31 ± 0.89 1.64 ± 0.52 < 0.001 HPR (Hemoglobin-to-Platelet Ratio) 0.54 ± 0.19 0.61 ± 0.17 0.73 ± 0.13 0.002 CRP, ESR, NLR, and PLR were significantly higher in HCV-infected diabetics, signifying systemic inflammation and immune activation. Reduced lymphocyte counts and HPR values indicate impaired antioxidant potential and catabolic predominance, consistent with chronic inflammatory load. Table 5. Correlation Matrix Between Key Parameters (Pearson r) Variable Pair r p Interpretation Duration of Diabetes vs Urea +0.46 < 0.001 Prolonged diabetes increases urea levels Duration vs Proteinuria +0.41 0.001 Chronic disease duration linked to renal leakage HbA1c vs CRP +0.52 < 0.001 Poor glycemic control amplifies inflammation HbA1c vs Ferritin +0.44 < 0.001 Metabolic stress triggers hepatic iron release HbA1c vs Creatinine +0.47 < 0.001 Glycemic toxicity accelerates nephropathy CRP vs ESR +0.56 < 0.001 Strong inflammatory parallelism CRP vs Ferritin +0.59 < 0.001 Both act as acute-phase reactants LDH vs Bilirubin +0.48 < 0.001 Linked to hepatocellular injury severity Ferritin vs Bilirubin +0.42 0.002 Oxidative and hepatic coupling Serum Iron vs Ferritin −0.46 < 0.001 Inverse relation due to inflammatory sequestration NLR vs CRP +0.51 < 0.001 Cellular inflammation mirrors biochemical rise Positive correlations among HbA1c, CRP, Ferritin, and Creatinine highlight the interdependence of metabolic control, inflammation, and renal-hepatic dysfunction. The negative iron–ferritin correlation confirms iron sequestration typical of chronic inflammation. NLR ↔ CRP further validates immune activation. Table 6. ROC Curve Analysis (DM + HCV vs DM only) Marker AUC 95 % CI Sensitivity (%) Specificity (%) Optimal Cut-off p CRP (mg/L) 0.89 0.82 – 0.95 85 83 > 11.5 < 0.001 Ferritin (µg/L) 0.87 0.81 – 0.94 82 80 > 140 < 0.001 LDH (U/L) 0.84 0.76 – 0.91 80 78 > 400 < 0.001 Direct Bilirubin (mg/dL) 0.82 0.75 – 0.89 78 77 > 0.35 0.002 ESR (mm/h) 0.78 0.70 – 0.85 76 74 > 18 0.006 PLR 0.80 0.72 – 0.88 77 72 > 105 0.004 ROC analysis demonstrated that CRP, Ferritin, LDH, and Direct Bilirubin are the most powerful biomarkers (AUC ≥ 0.82) for identifying diabetic patients with concurrent HCV infection. Their high sensitivity and specificity confirm their diagnostic utility as integrated indicators of combined metabolic–inflammatory hepatic injury.

The present hospital-based analytical study explored the diagnostic utility of commonly available laboratory parameters—both biochemical and hematological—in predicting early hepatitis C virus (HCV) infection. The findings demonstrated a consistent rise in WBC, PLR, ferritin, ESR, CRP, LDH, ALT/SGPT, ALP, TBIL, and DBIL, with corresponding reductions in RBC, lymphocyte counts, HPR, and serum iron among HCV-positive individuals. Receiver operating characteristic (ROC) analysis revealed that DBIL (AUC ≈ 0.97), LDH (AUC ≈ 0.90), CRP (AUC ≈ 0.90), TBIL (AUC ≈ 0.86), ferritin (AUC ≈ 0.86), and PLR (AUC ≈ 0.92) were the strongest discriminators of infection status. These parameters, individually and collectively, underline a characteristic biochemical–inflammatory pattern of hepatic injury that can complement molecular diagnostics, particularly where advanced testing is limited. Inflammation and Hepatocellular Injury The elevated CRP and ESR values recorded in this study underscore the active inflammatory milieu in HCV-infected patients. These markers demonstrated a direct proportionality to ALT and bilirubin levels, reflecting hepatocellular necro-inflammation. Studies by Bagheri et al. and Uto et al. have similarly highlighted CRP as a reliable correlate of hepatic injury severity, proposing its inclusion as an adjunct to transaminases for early clinical screening [15, 10]. In our setting, CRP levels exceeding 12 mg/L showed strong alignment with LDH activity, supporting the hypothesis that hepatocyte membrane disruption releases both inflammatory and cytosolic enzymes into circulation. LDH elevation—observed at nearly 1.8-fold above the control mean—further supports its diagnostic role. LDH, while non-specific, rises sharply with hepatocyte damage and mitochondrial dysfunction. Recent literature emphasizes LDH as a marker reflecting not only hepatocellular lysis but also oxidative stress in chronic HCV [9]. The co-elevation of LDH and direct bilirubin (DBIL) in our study likely reflects a mixed hepatocellular-cholestatic pattern, strengthening their combined ROC performance (AUC > 0.9). Iron Metabolism and Ferritin Significance Hyperferritinemia with concomitant hypoferremia observed in our HCV cohort aligns with previous reports suggesting altered iron homeostasis secondary to hepcidin dysregulation and inflammatory sequestration [16]. Chronic hepatic inflammation promotes iron storage within Kupffer cells and hepatocytes, contributing to oxidative injury and fibrosis progression. Our findings corroborate Chang et al. (2024) [16], who found elevated serum ferritin levels to be an independent predictor of fibrosis risk in chronic HCV. In our dataset, ferritin values above 400 ng/mL correlated positively with ALT and ESR, reinforcing its potential as a surrogate index for ongoing necro-inflammatory activity. Moreover, ferritin’s excellent diagnostic performance (AUC ≈ 0.86) confirms its potential as a low-cost, non-invasive biomarker. Its routine availability in hospital laboratories makes it suitable for use in screening algorithms in resource-limited settings, where reliance on molecular tests remains challenging. Integrating ferritin with transaminase ratios and inflammatory markers may thus yield an improved diagnostic composite for early detection. Hematological Ratios and Systemic Response Among hematologic indices, the platelet-lymphocyte ratio (PLR) exhibited strong predictive ability (AUC ≈ 0.92), while the neutrophil-lymphocyte ratio (NLR) showed minimal discrimination (AUC ≈ 0.55). This contrast aligns with findings by Hong et al. (2024) [18], who reported that PLR reflects a balance between pro-inflammatory platelet activity and immune regulation, outperforming NLR when liver inflammation predominates over systemic infection. Elevated platelet counts in chronic HCV may mirror cytokine-driven thrombopoiesis, whereas declining lymphocytes indicate immune exhaustion—a hallmark of chronic viral persistence [9]. Consequently, PLR emerges as a sensitive composite marker in differentiating active infection from remission. The decline in hemoglobin and RBC counts observed in our study may also reflect anemia of chronic disease due to cytokine-mediated marrow suppression and reduced erythropoietin response. These hematologic shifts complement the biochemical pattern of inflammation and hepatic dysfunction, supporting a systemic rather than organ-restricted pathology. Bilirubin Fractions and Liver Enzyme Dynamics The present analysis identified DBIL as the most powerful individual discriminator (AUC ≈ 0.97) among all markers studied. Elevated DBIL reflects impaired hepatocellular conjugation and biliary excretion—processes directly compromised by viral cytopathy and immune-mediated injury. While TBIL and ALT/SGPT levels have traditionally served as indicators of hepatocellular integrity, the high diagnostic accuracy of DBIL highlights its enhanced sensitivity in early disease phases. Consistent findings have been reported in similar biomarker analyses, suggesting that direct bilirubin mirrors both the cytolytic and cholestatic components of HCV pathology [15]. Comparative Context with Non-Invasive Fibrosis Models Although the current work focused on early biochemical predictors rather than fibrosis staging, several observed parameters paralleled established non-invasive indices such as APRI and FIB-4. Both of these indices, as emphasized in the 2025 scoping review by Dantas et al. [17], continue to serve as valuable alternatives to biopsy and elastography in low-resource environments. Our results suggest that combinations including LDH, ferritin, and DBIL could further refine these existing models, particularly for early disease stratification prior to fibrosis onset. The clinical implication is that integration of these simple biochemical metrics may improve risk-based patient referral systems. Public-Health Implications Globally, approximately 50 million individuals continue to live with HCV infection, with a significant proportion undiagnosed due to limited screening coverage [14, 21, 22]. Updated CDC and AASLD–IDSA recommendations advocate universal, one-time screening for adults aged ≥ 18 years and repeat testing during every pregnancy [12, 13, 20]. However, the implementation of these recommendations remains inconsistent in many regions. In such contexts, the predictive parameters identified in this study—especially DBIL, LDH, CRP, ferritin, and PLR—could form a low-cost laboratory triage tool to identify probable cases warranting confirmatory molecular testing. This approach is particularly relevant in tertiary centers managing mixed medical caseloads, where rapid, inexpensive indicators can expedite clinical decision-making. From a clinical management standpoint, early recognition of biochemical perturbations allows timely antiviral initiation and secondary prevention of hepatic fibrosis and carcinoma. The study thus aligns with WHO’s 2024–2025 elimination targets by supporting context-appropriate diagnostic algorithms adaptable to varying levels of resource availability [21, 22].

The study reaffirms that routine laboratory markers can serve as reliable early predictors of hepatitis C virus infection in a tertiary-care setting. Among these, direct bilirubin, LDH, CRP, ferritin, and PLR emerged as strong independent indicators, achieving high sensitivity and specificity on ROC analysis. These findings reinforce the concept that a biochemical–hematological signature reflecting hepatocellular injury, inflammation, and immune dysregulation precedes overt clinical manifestation. Integrating such markers into initial screening workflows could enhance diagnostic yield, reduce dependence on costly molecular assays, and strengthen early linkage to care, particularly in low-resource environments. When applied alongside existing guidelines, this approach offers a pragmatic bridge between epidemiological necessity and diagnostic feasibility. Limitations Several limitations should be recognized. First, the study was conducted at a single tertiary-care hospital, limiting generalizability to community or rural populations. The sample size, though adequate for statistical significance, may not fully capture genotype-specific or ethnic variability in biomarker expression. Second, molecular confirmation by HCV RNA quantitation was available only for a subset of participants, restricting the ability to correlate biochemical indices with viral load or genotype. Third, potential confounders such as nutritional status, alcohol intake, or co-existing metabolic disorders were not uniformly controlled and may have influenced certain biochemical parameters, particularly ferritin and CRP. Additionally, liver fibrosis and necro-inflammatory grading were not assessed histologically, precluding direct correlation between laboratory findings and tissue pathology. Finally, the cross-sectional design restricts inference regarding causality or longitudinal biomarker kinetics. Future studies should incorporate larger, multi-center cohorts, include non-invasive fibrosis imaging, and evaluate post-treatment biomarker modulation to validate these results and strengthen clinical translation. Despite these limitations, the study’s strength lies in its well-defined control groups and comprehensive biomarker analysis.

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