Search Results (17)

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality worldwide, increasingly driven by metabolic dysfunction-associated steatotic liver disease alongside viral and alcohol-related cirrhosis. The tolerogenic immune environment of the liver enables tumor immune escape, with regulatory T cells (Tregs) playing a central role. This review synthesizes human-focused evidence (tissues, blood, clinical cohorts, and single-cell/spatial studies) through September 2025 to define how Tregs are recruited, maintained, and functionally deployed in HCC. Across datasets, intratumoral effector-like Tregs (eTregs) expressing ICOS, CTLA-4, CCR8, and CD39/CD73 accumulate within tumors and co-localize with exhausted cytotoxic PD-1^hi CD8⁺ T cells and suppressive myeloid cells. Recruitment is driven mainly by CCL20–CCR6 and CCL22/CCL17–CCR4 signaling, while CCR8 marks highly suppressive tumor-resident Tregs. Their persistence is supported by TGF-β, IL-10, IL-35, adenosine signaling, IL-2 sequestration, and metabolic adaptation. Spatial biomarkers, including ICOS⁺/CCR8⁺ eTreg density and CD8:Treg ratios, associate with prognosis and emerging immunotherapy responses. Etiology further shapes immune architecture: HBV-related HCC often forms Treg-exhausted T-cell niches around viral antigens, whereas MASLD/MASH promotes stromal and metabolic barriers that may reduce PD-(L)1 efficacy. Current treatments (PD-(L)1 blockade with anti-VEGF or CTLA-4, and some TKIs) intersect with Treg biology, while emerging strategies targeting CCR8, CCR4, ICOS, or the adenosine pathway aim to selectively disrupt intratumoral eTreg networks. This review underscores that an etiology-aware, spatial-biomarker framework may guide the integration of selective Treg targeting with PD-(L)1-based therapies in HCC. Full article

Background: Southeast Asian Americans (SEAAs) experience a disproportionately high burden of hepatocellular carcinoma (HCC), with incidence in several subgroups (i.e., Cambodian, Laotian, and Vietnamese individuals) reaching up to nine times that of non-Hispanic Whites. HCC in SEAAs is largely driven by chronic hepatitis B (HBV), hepatitis C (HCV), metabolic dysfunction–associated steatotic liver disease (MASLD), and alcohol-associated liver disease (ALD). Despite established screening guidelines, under-detection and delayed diagnosis remain common. Objective: To summarize epidemiologic patterns, risk factors, screening challenges, and potential interventions aimed at reducing HCC disparities among SEAAs. Design and Methods: This narrative review synthesized evidence from population based epidemiologic studies, community-based interventions, health services research, and policy analyses. Attention was given to studies reporting disaggregated SEAA subgroup data. Findings derived from SEAA specific studies were distinguished from evidence drawn from broader Asian American or general cirrhosis populations, with inferential steps explicitly noted where subgroup specific data were limited. Key Findings: HCC incidence varies widely across SEAA subgroups, with elevated HBV- and HCV-related HCC in Vietnamese, Cambodian, and Laotian communities, and increasing MASLD-related HCC including among lean individuals who fall outside many surveillance frameworks. Screening and surveillance remain suboptimal, with fewer than 30% of patients with cirrhosis receiving recommended semiannual HCC surveillance and even lower uptake among SEAAs. Barriers include low HBV/HCV screening rates, limited disease awareness, language barriers, underinsurance, provider knowledge gaps, and lack of automated EHR-based reminders. Structural challenges such as poverty, transportation barriers, and limited access to specialty care further delay diagnosis. Proposed Interventions: Culturally tailored outreach programs, bilingual navigators, and community-based screening initiatives have demonstrated improved HBV/HCV testing and linkage to care. AI-enabled EHR tools may enhance identification of high-risk patients, streamline follow-up, and increase surveillance adherence. Expanded use of non-invasive fibrosis assessment and recognition of MASLD-related risk in non-obese individuals may support earlier detection. Policy priorities include mandatory Asian subgroup data disaggregation, expanded insurance coverage, and strengthened community-level healthcare infrastructure. Conclusions: SEAAs face a substantial and preventable HCC burden. A coordinated approach combining culturally tailored community engagement, improved provider support systems, and policy reforms is essential to improving early detection and reducing HCC disparities in this diverse population. Full article

Hepatocellular carcinoma (HCC) remains a major cause of cancer-related mortality worldwide, and its management is limited by heterogeneous risk profiles, suboptimal surveillance performance, diagnostic uncertainty in chronically diseased livers, and difficulty individualizing prognosis after treatment. The aim of this narrative review was to critically evaluate artificial intelligence (AI) applications across the HCC care continuum, with emphasis on their intended clinical role, reported performance, evidence maturity, and barriers to implementation. A major strength of this review is that it moves beyond a descriptive catalog of models by structuring the literature around clinically relevant decision points and by explicitly distinguishing emerging proof-of-concept tools from applications with stronger translational potential. Across risk stratification, surveillance, imaging-based diagnosis, pathology, treatment-response prediction, and prognostication, we found that AI consistently demonstrates promise, particularly for identifying patients at higher future HCC risk, improving lesion detection and characterization on ultrasound, CT, MRI, and contrast-enhanced ultrasound, assisting histopathologic classification, and predicting outcomes such as microvascular invasion, recurrence, survival, and response to locoregional therapies. However, we also found that the evidence base remains highly uneven: many diagnostic studies are retrospective and lesion-enriched rather than embedded in true surveillance populations, many prognostic models lack robust external validation and calibration assessment, and reference standards, imaging protocols, and dataset composition vary substantially across studies. These findings are clinically relevant because they highlight both where AI may offer near-term value and why most published systems are not yet ready for routine use. Overall, AI in HCC should be viewed as a rapidly evolving but still transitional field. Its future impact will depend not only on higher-performing algorithms but on clearly defined clinical use cases, multicenter and prospective validation, transparent reporting, workflow-aware evaluation, and implementation strategies that support safe, equitable, and scalable adoption. Full article

Background: Tumor neoantigens are key targets for personalized vaccines and T-cell therapies, yet most pipelines focus on neoantigens derived from SNV/small indel and often yield a limited number of high-quality candidates. SVs are prevalent in tumors and can generate novel chimeric sequences and neopeptides, making them a promising additional source of neoantigens. However, SV-derived neoantigen prediction remains challenging due to breakpoint uncertainty, isoform-dependent coding inference, and limited integration of multi-dimensional evidence and reproducibility. Methods: We developed SVNeoPP (Structural Variant Neoantigen Prediction and Prioritization), an end-to-end workflow for SV-derived neoantigen analysis. SVNeoPP takes WGS and RNA-seq as inputs, performs SV calling and annotation, and reconstructs altered transcripts and coding sequences in a traceable, isoform-aware manner to generate candidate peptides. Candidates are prescreened by integrating antigen-processing features with HLA binding prediction, and then hierarchically filtered and prioritized based on transcript expression, LC–MS/MS proteomics evidence, immunogenicity predictions, and sequence similarity to experimentally validated neoantigen databases. SVNeoPP is implemented in Snakemake to enable modular extension, checkpoint-based restarts, and end-to-end reproducibility. Results: Using a hepatocellular carcinoma (HCC) multi-omics dataset as a proof of concept, we demonstrated the performance of SVNeoPP and obtained a high-priority shortlist of candidate peptides. Compared with other methods, SVNeoPP substantially expanded the candidate search space for SV-derived neoantigens and showed more favorable distributions of antigen-processing and HLA binding features. Conclusions: SVNeoPP provides a reusable, traceable, and interpretable multi-dimensional evidence-driven framework for SV-derived neoantigens. As a complementary module to SNV/small-indel pipelines, it broadens the neoantigen candidate repertoire and generates ranked candidates with interpretable evidence to facilitate downstream prioritization and decision-making. Full article

Persistent infection with hepatitis D virus (HDV), also known as hepatitis delta, is considered the most severe form of chronic viral hepatitis. HDV is a defective RNA virus that depends on hepatitis B virus (HBV) for propagation. Despite its global distribution, HDV stays a neglected part of the viral hepatitis agenda, often overlooked in surveillance systems and public health policy. This oversight is particularly concerning given HDV’s aggressive clinical course, characterized by more rapid progression to cirrhosis, liver failure, and hepatocellular carcinoma (HCC) compared to HBV mono-infection. Mongolia has the highest incidence and mortality rates of HCC worldwide, with approximately 47% of cases estimated to be attributable to chronic HDV infection. Globally, an estimated 12–25 million people are co-infected with HBV and HDV, although the true prevalence is higher due to insufficient screening and incomplete data collection. Because HDV infection is entirely dependent on HBV, prevention of HBV infection through effective vaccination stands for an indirect yet highly effective strategy to curb HDV transmission. The World Health Organization (WHO), together with the global health community, has established ambitious targets to eliminate viral hepatitis as a public health threat by 2030. However, achieving HDV elimination remains particularly challenging due to limited diagnostic capacity, low awareness, and minimal inclusion of HDV in national hepatitis programs. This review explores the intersection of HDV and HBV, focusing on how expanded and optimized HBV vaccination coverage can serve as a cornerstone of global HDV prevention efforts. We examine epidemiological evidence, scientific rationale, policy developments, and key implementation challenges, with particular attention to high-burden settings such as Mongolia. Finally, we propose strategic recommendations to bridge policy and practice gaps in HDV elimination. Full article

Background: Spatial heterogeneity in tumor tissue has been linked to patient prognosis. To exploit both structural and semantic cues in whole slide images (WSIs), we propose Dual eXplanatory Framework (DuXplore), a dual-branch deep learning framework that integrates tissue architecture and cellular morphology for hepatocellular carcinoma (HCC) prognosis. Method: At the macroscopic level, DuXplore constructs a multi-channel tissue organization probability map (MTOP) to represent the spatial layout of eight tissue categories within the WSIs. At the microscopic level, a feature-guided Fused Structure Tensor (FST) based on tissue composition is employed to extract representative cell morphology patches. Accordingly, MTOP representations are modeled by Macro-Net, while FST-guided patches are modeled by Micro-Net. Each branch produces a 32-dimensional prognostic embedding, which are fused and passed through a multi-layer perceptron with a Cox proportional hazards head to generate patient-level risk predictions. To further elucidate the distinct contributions of the two branches, we conducted model-agnostic interpretability analyses, including occlusion sensitivity mapping (OSM) on MTOP and nuclear morphometrics from CellProfiler on high- versus low-risk tiles. Result: DuXplore achieves promising performance with C-indices of 0.764 on the public Cancer Genome Atlas (TCGA) dataset and 0.713 on the Eastern Hepatobiliary HCC (EHBH) cohort from our clinical center, along with significant patient risk stratification (log-rank p < 0.001). OSM highlighted necrosis and central fibrosis as high-risk and marginal fibrosis as protective; these patterns were corroborated by multivariable Cox using reproducible structural parameters (N-ratio, FIB-center, FIB-edge). Micro-level analysis revealed that higher nuclear staining intensity, increased texture irregularity (GLCM features), and greater morphological heterogeneity characterize high-risk tiles, aligning with pathological understanding. Conclusions: DuXplore advances prognostic modeling by coupling structure-aware micro-sampling with macro architectural encoding, delivering robust, generalizable survival prediction and biologically plausible explanations. While validated on HCC WSIs, broader multi-center, multi-omics studies are warranted to refine sampling scales and enhance clinical translation. Full article

Background: Hepatocellular carcinoma (HCC) is a prominent contributor to global cancer-related mortality and is characterized by unfavorable prognosis despite regional discrepancies in its occurrence. Understanding and awareness of HCC among health science students are crucial for early detection and enhanced patient outcomes. Methods: This cross-sectional study evaluated awareness of HCC among health science students at Jazan University and identified areas that require further education. The study included health science students enrolled in various academic programs at Jazan University. A structured online questionnaire was used to collect demographic information and assess knowledge related to HCC. The sample size was determined based on prevalence estimates, and statistical analyses were performed using the R software (version 4.3.1). Results: The study found that 61% of the health science students had good knowledge of HCC. Of the 411 participants, most were young (≤24 years), single, and enrolled in allied and health sciences programs. Although 55.20% were familiar with HCC, their awareness of screening methods and preventive measures was limited. Hepatitis B vaccination has been recognized as an effective preventive measure. A logistic regression analysis revealed significant associations between age, sex, academic year, and awareness of HCC, with 1.91-, 1.94-, and 2.83-times higher odds ratios, respectively. Conclusions: This study underscores the need for targeted educational interventions and public awareness campaigns to improve understanding, early detection, and prevention of HCC among health science students. Full article

Background: Hepatic splenosis (HS) is a rare para-physiological condition resulting from the ectopic implantation of splenic tissue, most commonly following traumatic or surgical splenectomy. Its radiological features can mimic those of hepatocellular carcinoma (HCC), potentially leading to misdiagnosis and unnecessary invasive procedures, such as biopsies or liver resection. Methods: A literature review was conducted using the PubMed database to identify all reported cases of HS. Case Presentation: We report the case of a 52-year-old male with an incidental finding of a liver lesion in segment V, initially suspected to be HCC, and a history of post-traumatic splenectomy. The patient had no history of underlying liver disease. Due to the lesion’s superficial location, a biopsy was not performed because of the risk of tumor rupture with subsequent bleeding or peritoneal seeding. Consequently, the patient underwent upfront laparoscopic anatomic segmentectomy of segment V. Final pathology revealed a diagnosis of intrahepatic splenosis. Conclusions: HS should be considered in the differential diagnosis of liver lesions in patients with a history of splenectomy but no underlying liver disease, particularly when imaging shows features suggestive of HCC, such as arterial phase hyperenhancement and portal venous washout. Awareness of this entity may prevent unnecessary invasive interventions and guide appropriate patient management. Full article

Background/Objectives: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality, with the Asia-Pacific (APAC) region bearing a disproportionate burden. This paper examines HCC challenges within seven APAC health systems, identifies key barriers at each stage of the patient journey, and proposes tailored, actionable solutions. To effectively address HCC challenges, a stepwise approach should prioritise high-impact solutions, focusing on prevention, early diagnosis, and expanding surveillance to maximise health outcomes and economic benefits, while tailoring strategies to each health system’s unique resources and constraints. Methods: A mixed-methods approach was used, including expert consultations from the 2024 HCC APAC Policy Forum, a literature review, and a review of Japan’s HCC management model. Data were collected through workshops and stakeholder feedback from healthcare professionals, policymakers, researchers and patient advocates across Australia, India, Malaysia, South Korea, Taiwan, Thailand, and Vietnam. Results: Key findings include significant disparities in HCC awareness, prevention, early detection, diagnosis, and access to treatment. Common challenges across APAC include limited public awareness, suboptimal surveillance infrastructure, and financial barriers to care. The integration of novel biomarkers and advanced surveillance modalities were identified as crucial priorities for improving early detection. Japan’s multi-faceted approach to HCC management serves as a successful model for the region. Conclusions: A customised and targeted approach is essential for reducing the HCC burden across APAC. The proposed recommendations, tailored to each health system’s needs, can significantly improve patient outcomes and reduce healthcare costs. Effective collaboration among stakeholders is necessary to drive these changes. Full article

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, so its detection and monitoring are critical. However, contrast-enhanced magnetic resonance imaging (CE-MRI) is particularly vulnerable to complex, unstructured noise, which compromises image quality and diagnostic accuracy. This study proposes the use of NLE-ANSNet, a deep learning-based denoizing framework that integrates multilevel noise level estimators (NLEs) and adaptive noise scaling (ANS) within residual blocks. The model performs progressive, stagewise noise suppression at multiple feature depths, dynamically adjusting normalization based on localized noise estimates. This enables context-aware denoizing, preserving fine anatomical details. To simulate clinically realistic conditions, we developed a hybrid noise simulation framework that combines Gaussian, Poisson, and Rician noise at the pixel level. This framework aims to approximate a balanced noise distribution for evaluation purposes, with both mean and median noise levels reported to enhance evaluation robustness and prevent bias from extreme cases. NLE-ANSNet achieves a PSNR of 34.01 dB and an SSIM of 0.9393, surpassing those of state-of-the-art models. The method aims to support diagnostic reliability by preserving image structure and intensity fidelity in CE-MRI interpretation. In addition to quantitative analysis, a qualitative assessment was conducted to visually compare denoizing outputs across models, further demonstrating NLE-ANSNet’s superior ability to suppress noise while preserving diagnostically critical information. Unlike previous approaches, this study introduces a denoizing framework that combines multilevel noise estimation and adaptive noise scaling specifically tailored for CE-MRI in HCC under hybrid noise conditions—a clinically relevant and underexplored area. Overall, this study supports improved clinical decision making in HCC management. Full article

Introduction: Circulating tumor DNA (ctDNA) is emerging as a promising, non-invasive diagnostic and surveillance biomarker in solid organ malignancy. However, its utility before and after liver transplant (LT) for patients with primary and secondary liver cancers is still underexplored. Methods: Patients undergoing LT for hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), and colorectal liver metastases (CRLM) with ctDNA testing were included. CtDNA testing was conducted pre-transplant, post-transplant, or both (sequential) from 11/2019 to 09/2023 using Guardant360, Guardant Reveal, and Guardant360 CDx. Results: 21 patients with HCC (n = 9, 43%), CRLM (n = 8, 38%), CCA (n = 3, 14%), and mixed HCC/CCA (n = 1, 5%) were included in the study. The median follow-up time was 15 months (range: 1–124). The median time from pre-operative testing to surgery was 3 months (IQR: 1–4; range: 0–5), and from surgery to post-operative testing, it was 9 months (IQR: 2–22; range: 0.4–112). A total of 13 (62%) patients had pre-transplant testing, with 8 (62%) having ctDNA detected (ctDNA+) and 5 (32%) not having ctDNA detected (ctDNA-). A total of 18 (86%) patients had post-transplant testing, 11 (61%) of whom were ctDNA+ and 7 (33%) of whom were ctDNA-. The absolute recurrence rates were 50% (n = 5) in those who were ctDNA+ vs. 25% (n = 1) in those who were ctDNA- in the post-transplant setting, though this difference was not statistically significant (p = 0.367). Six (29%) patients (HCC = 3, CCA = 1, CRLM = 2) experienced recurrence with a median recurrence-free survival of 14 (IQR: 6–40) months. Four of these patients had positive post-transplant ctDNA collected following diagnosis of recurrence, while one patient had positive post-transplant ctDNA collected preceding recurrence. A total of 10 (48%) patients had sequential ctDNA testing, of whom n = 5 (50%) achieved ctDNA clearance (+/−). The remainder were ctDNA+/+ (n = 3, 30%), ctDNA−/− (n = 1, 10%), and ctDNA−/+ (n = 1, 11%). Three (30%) patients showed the acquisition of new genomic alterations following transplant, all without recurrence. Overall, the median tumor mutation burden (TMB) decreased from 1.23 mut/Mb pre-transplant to 0.00 mut/Mb post-transplant. Conclusions: Patients with ctDNA positivity experienced recurrence at a higher rate than the ctDNA- patients, indicating the potential role of ctDNA in predicting recurrence after curative-intent transplant. Based on sequential testing, LT has the potential to clear ctDNA, demonstrating the capability of LT in the treatment of systemic disease. Transplant providers should be aware of the potential of donor-derived cell-free DNA and improved approaches are necessary to address such concerns. Full article

Contrast-enhanced ultrasound (CEUS) is widely used in the characterization of liver tumors; however, the evaluation of perfusion patterns using CEUS has a subjective character. This study aims to evaluate the accuracy of an automated method based on CEUS for classifying liver lesions and to compare its performance with that of two experienced clinicians. The system used for automatic classification is based on artificial intelligence (AI) algorithms. For an interpretation close to the clinical setting, both clinicians knew which patients were at high risk for hepatocellular carcinoma (HCC), but only one was aware of all the clinical data. In total, 49 patients with 59 liver tumors were included. For the benign and malignant classification, the AI model outperformed both clinicians in terms of specificity (100% vs. 93.33%); still, the sensitivity was lower (74% vs. 93.18% vs. 90.91%). In the second stage of multiclass diagnosis, the automatic model achieved a diagnostic accuracy of 69.93% for HCC and 89.15% for liver metastases. Readers demonstrated greater diagnostic accuracy for HCC (83.05% and 79.66%) and liver metastases (94.92% and 96.61%) compared to the AI system; however, both were experienced sonographers. The AI model could potentially assist and guide less-experienced clinicians to discriminate malignant from benign liver tumors with high accuracy and specificity. Full article

Hepatocellular carcinoma (HCC) ranks fourth in cancer-related deaths worldwide. Semiannual surveillance of the disease for patients with cirrhosis or hepatitis B virus allows for early detection with more favorable outcomes. The current underuse of surveillance programs demonstrates the need for intervention at both the patient and provider level. Mail outreach along with navigation provision has proven to increase surveillance follow-up in patients, while provider-targeted electronic medical record reminders and compliance reports have increased provider awareness of HCC surveillance. Imaging is the primary mode of diagnosis in HCC with The Liver Imaging Reporting and Data System (LI-RADS) being a widely accepted comprehensive system that standardizes the reporting and data collection for HCC. The management of HCC is complex and requires multidisciplinary team evaluation of each patient based on their preference, the state of the disease, and the available medical and surgical interventions. Staging systems are useful in determining the appropriate intervention for HCC. Early-stage HCC is best managed by curative treatment modalities, such as liver resection, transplant, or ablation. For intermediate stages of the disease, transarterial local regional therapies can be applied. Advanced stages of the disease are treated with systemic therapies, for which there have been recent advances with new drug combinations. Previously sorafenib was the mainstay systemic treatment, but the recent introduction of atezolizumab plus bevacizumab proves to have a greater impact on overall survival. Although there is a current lack of improved outcomes in Phase III trials, neoadjuvant therapies are a potential avenue for HCC management in the future. Full article

(1) Background: Little is known about facilitators of and barriers to palliative care referral for people with hepatocellular carcinoma (HCC). The objective of this study is to identify facilitators and barriers of palliative care referral described by HCC-treating clinicians. (2) Methods: Semi-structured interviews (n = 16) were conducted with HCC-treating clinicians at two centers, focusing on referral patterns, palliative care needs, and disease course. A code book was created, axial coding was used to code all interviews, and selective coding was used to identify facilitators and barriers of palliative care referral. (3) Results: Facilitators included helpfulness at times of transition; help with management of certain symptoms; provision of psychosocial support; and positive experiences with referral. Barriers included feasibility concerns; lack of information about palliative care and who is appropriate; lack of symptoms requiring outside referral; and concerns that palliative care conveys loss of hope. (4) Conclusions: Participants noted the helpfulness of palliative care at specific points in the disease trajectory and cited barriers related to feasibility, lack of need, lack of awareness, and loss of hope. The results show actionable issues that can be addressed in future research to leverage the benefits of and overcome the barriers to palliative care for people with HCC. Full article

Background: The primary aim of this study was to compare liver transplant (LT) recipients with and without hepatocellular carcinoma (HCC) in terms of COVID-19-related depression, anxiety, and stress. Method: A total of 504 LT recipients with (HCC group; n = 252) and without HCC (non-HCC group; n = 252) were included in the present case–control study. Depression Anxiety Stress Scales (DASS-21) and Coronavirus Anxiety Scale (CAS) were used to evaluate the depression, stress, and anxiety levels of LT patients. DASS-21 total and CAS-SF scores were determined as the primary outcomes of the study. Poisson regression and negative binomial regression models were used to predict the DASS and CAS scores. The incidence rate ratio (IRR) was used as a coefficient. Both groups were also compared in terms of awareness of the COVID-19 vaccine. Results: Poisson regression and negative binomial regression analyses for DASS-21 total and CAS-SF scales showed that the negative binomial regression method was the appropriate model for both scales. According to this model, it was determined that the following independent variables increased the DASS-21 total score: non-HCC (IRR: 1.26; p = 0.031), female gender (IRR: 1.29; p = 0.036), presence of chronic disease (IRR: 1.65; p < 0.001), exposure to COVID-19 (IRR: 1.63; p < 0.001), and nonvaccination (IRR: 1.50; p = 0.002). On the other hand, it was determined that the following independent variables increased the CAS score: female gender (IRR:1.75; p = 0.014) and exposure to COVID-19 (IRR: 1.51; p = 0.048). Significant differences were found between the HCC and non-HCC groups in terms of median DASS-21 total (p < 0.001) and CAS-SF (p = 0.002) scores. Cronbach’s alpha internal consistency coefficients of DASS-21 total and CAS-SF scales were calculated to be 0.823 and 0.783, respectively. Conclusion: This study showed that the variables including patients without HCC, female gender, having a chronic disease, being exposed to COVID-19, and not being vaccinated against COVID-19 increased anxiety, depression, and stress. High internal consistency coefficients obtained from both scales indicate that these results are reliable. Full article