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Liver fibrosis has been associated with hepatitis C virus (HCV) genotype and genetic variation near the interleukin 28B (IL28B) gene, but the relative contribution is unknown. We aimed to investigate the relation between HCV genotypes, IL28B and development of liver stiffness. This cross-sectional study consists of 369 patients with chronic hepatitis C (CHC). Liver stiffness was evaluated using transient elastograhy (TE). Factors associated with development of liver fibrosis were identified by logistic regression analysis. We identified 369 patients with CHC. 235 were male, 297 Caucasians, and 223 had been exposed to HCV through intravenous drug use. The overall median TE value was 7.4 kPa (interquartile range (IQR) 5.7-12.1). HCV replication was enhanced in patients carrying the IL28B CC genotype compared to TT and TC (5.8 vs. 5.4 log10 IU/mL, p = 0.03). Patients infected with HCV genotype 3 had significantly higher TE values (8.2 kPa; IQR, 5.9-14.5) compared to genotype 1 (6.9 kPa; IQR, 5.4-10.9) and 2 (6.7 kPa; IQR, 4.9-8.8) (p = 0.02). Within patients with genotype 3, IL28B CC genotype had the highest TE values (p = 0.04). However, in multivariate logistic regression, using various cut-off values for fibrosis and cirrhosis, only increasing age (odds ratio (OR) 1.09 (95% confidence interval (CI), 1.05-1.14 per year increment)), ALT (OR 1.01 (95% CI, 1.002-1.011), per unit increment) and HCV genotype 3 compared to genotype 1 (OR 2.40 (95% CI, 1.19-4.81), were consistently associated with cirrhosis (TE>17.1 kPa). Age, ALT and infection with HCV genotype 3 were associated with cirrhosis assessed by TE. However, IL28B genotype was not an independent predictor of fibrosis in our study.

Most children are transiently colonized with Streptococcus pneumoniae, but very few develop invasive pneumococcal disease (IPD). Host genetic variation of innate immunity may predispose to IPD. We investigated the effect of genetic variation in the mannose-binding lectin gene, MBL2, on susceptibility and disease severity of IPD in previously healthy children aged <5 years. IPD cases were identified through national registries. DNA was obtained from the Danish Neonatal Screening Biobank. Pneumococcal serotypes were determined by Quellung reaction. The associations between MBL2 diplotypes and IPD susceptibility, serotypes, and outcome were investigated using logistic regression analysis. We included 372 cases with meningitis, 907 with bacteremia, and 1263 age- and sex-matched controls; 2372 individuals were successfully genotyped and assigned MBL2 diplotypes. The median age in our combined case series was 13 months. Children with defective diplotypes were not at higher risk for meningitis than children with other diplotypes (odds ratio [OR], 0.85; 95% confidence interval [CI], .56-1.28). Similar results were found for bacteremia (OR, 0.89; 95% CI, .68-1.15) as well as for all cases (OR, 0.87; 95% CI, .70-1.09). There was no association with susceptibility to recurrent IPD (n = 12) for children with defective diplotypes compared with cases with a single episode (OR, 0.53; 95% CI, .07-4.13) and with all controls (OR, 0.46; 95% CI, .06-3.56). There was no association between diplotypes and mortality or between diplotypes and pneumococcal serotypes. Defective MBL2 polymorphisms did not predict increased IPD susceptibility in children born in Northern Europe.

Genetic variation upstream of the apoptosis pathway has been associated with outcome of hepatitis C virus (HCV) infection. We investigated genetic polymorphisms in the intrinsic apoptosis pathway to assess their influence on sustained virological response (SVR) to pegylated interferon-α and ribavirin (pegIFN/RBV) treatment of HCV genotypes 1 and 3 infections. We conducted a candidate gene association study in a prospective cohort of 201 chronic HCV-infected individuals undergoing treatment with pegIFN/RBV. Differences between groups were compared in logistic regression adjusted for age, HCV viral load and interleukin 28B genotypes. Four single nucleotide polymorphisms (SNPs) located in the B-cell lymphoma 2-like 1 (BCL2L1) gene were significantly associated with SVR. SVR rates were significantly higher for carriers of the beneficial rs1484994 CC genotypes. In multivariate logistic regression, the rs1484994 SNP combined CC + TC genotypes were associated with a 3.4 higher odds ratio (OR) in SVR for the HCV genotype 3 (p = 0.02). The effect estimate was similar for genotype 1, but the association did not reach statistical significance. In conclusion, anti-apoptotic SNPs in the BCL2L1 gene were predictive of SVR to pegIFN/RBV treatment in HCV genotypes 1 and 3 infected individuals. These SNPs may be used in prediction of SVR, but further studies are needed.

Objective Liver fibrosis has been associated with hepatitis C virus (HCV) genotype and genetic variation near the interleukin 28B (IL28B) gene, but the relative contribution is unknown. We aimed to investigate the relation between HCV genotypes, IL28B and development of liver stiffness. Patients and Methods This cross-sectional study consists of 369 patients with chronic hepatitis C (CHC). Liver stiffness was evaluated using transient elastograhy (TE). Factors associated with development of liver fibrosis were identified by logistic regression analysis. Results We identified 369 patients with CHC. 235 were male, 297 Caucasians, and 223 had been exposed to HCV through intravenous drug use. The overall median TE value was 7.4 kPa (interquartile range (IQR) 5.7-12.1). HCV replication was enhanced in patients carrying the IL28B CC genotype compared to TT and TC (5.8 vs. 5.4 log10 IU/mL, p = 0.03). Patients infected with HCV genotype 3 had significantly higher TE values (8.2 kPa; IQR, 5.9-14.5) compared to genotype 1 (6.9 kPa; IQR, 5.4-10.9) and 2 (6.7 kPa; IQR, 4.9-8.8) (p = 0.02). Within patients with genotype 3, IL28B CC genotype had the highest TE values (p = 0.04). However, in multivariate logistic regression, using various cut-off values for fibrosis and cirrhosis, only increasing age (odds ratio (OR) 1.09 (95% confidence interval (CI), 1.05-1.14 per year increment)), ALT (OR 1.01 (95% CI, 1.002-1.011), per unit increment) and HCV genotype 3 compared to genotype 1 (OR 2.40 (95% CI, 1.19-4.81), were consistently associated with cirrhosis (TE>17.1 kPa). Conclusions Age, ALT and infection with HCV genotype 3 were associated with cirrhosis assessed by TE. However, IL28B genotype was not an independent predictor of fibrosis in our study.

Background Infections are among the most common reasons for consultations in primary care, and appropriate infection management is essential to patient safety and antimicrobial stewardship. Educational interventions can improve diagnostic and prescribing practices, but in-person training is resource-intensive and difficult to scale. E-learning offers a flexible alternative; however, little is known about factors that influence its implementation in primary care. Objective To identify barriers and facilitators to implementing e-learning interventions for infection management in primary care settings. Methods A scoping review was conducted in accordance with established methodological guidance. Systematic searches across five databases was performed and updated in October 2025 to identify studies describing asynchronous, interactive e-learning interventions targeting infection management in primary care. Eligible studies were screened, and implementation determinants were extracted and mapped using the Consolidated Framework for Implementation Research (CFIR). Results Seven studies published between 2017 and 2025 were included, with implementation determinants typically reported alongside feasibility or contextual findings rather than as primary outcomes. Most studies employed quantitative designs, and one used mixed methods. Reported determinants were mainly mapped to the CFIR Innovation and Individuals domains, highlighting the importance of intervention design, adaptability, and perceived relevance for professional roles. Barriers frequently related to misalignment between intervention content and participants’ level of expertise, platform complexity, and challenges related to IT infrastructure. Determinants related to organizational context, implementation processes, and external conditions were reported less frequently. Conclusions The available evidence on the implementation of e-learning for infection management in primary care is limited and heterogeneous. Future research should include more robust implementation studies, including qualitative approaches, to better capture the important determinants for implementation at the individual, organizational, and system levels. Such insights are needed to inform the development and implementation of scalable and sustainable e-learning interventions in primary care.