Global Epidemiology of Chronic Liver Disease

Cheemerla, Shantan; Balakrishnan, Maya

doi:10.1002/cld.1061

Cited by 349 publications

(259 citation statements)

References 28 publications

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“…Consistent with our finding, a study from Togo has reported HBV (66%), alcohol abuse (57%), and HCV (12.3%) as the three principal causes of CLD [ 11 ]. Globally, HBV and HCV are the major cause of CLD [ 6 , 41 ]. Similarly, viral hepatitis B and C are the predominant etiologies of CLD in eastern European countries [ 40 ].…”

Section: Discussionmentioning

confidence: 99%

Chronic Liver Disease in Ethiopia with a Particular Focus on the Etiological Spectrums: A Systematic Review and Meta-Analysis of Observational Studies

Tesfaye

Mulugeta

Bekele

et al. 2021

Canadian Journal of Gastroenterology and Hepatology

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Background. In Ethiopia, chronic liver disease (CLD) is the 7th leading cause of death, accounting for about 24 deaths per 100000 populations in 2019. Despite its burden, there is a lack of compiled pieces of evidence on CLD in the country. Thus, this systematic review and meta-analysis is intended to provide the pooled estimates of CLD etiologies and mortality rate in CLD patients in Ethiopia. Method. PubMed, Google Scholar, ScienceDirect, institutional repositories, national digital library, and the bibliography of the eligible articles information were the source of data for the present review. The keywords “hepatitis, chronic” [Mesh], “end-Stage Liver Disease” [Mesh], “chronic liver disease”, “liver cirrhosis” [Mesh], and “Ethiopia” were used for the searches. Overall, we retrieved 199 records and 12 were included in this review. We used the DerSimonian-Laird random-effects models to perform the meta-analysis. We conducted subgroup and meta-regression analyses to account for the heterogeneity of the estimates. Result. Hepatitis B virus, alcohol, and hepatitis C virus are the three most common etiologies of CLD in Ethiopia accounting for a pooled estimate of 40.0% [95% CI: 29.0, 51.0, I2 = 96.3, p < 0.001 ], 17.0% [95% CI: 9.0, 25.0, I2 = 96.7, p < 0.001 ], and 15.0% [95% CI: 9.0, 21.0, I2 = 95.8, p < 0.001 ], respectively. Unidentified etiology report has a substantial contribution accounting for an estimated pooled proportion of 45% [95% CI: 34.0, 56.0%, Q = 32.08, p < 0.001 , I2 = 87.53] of the CLD cases in the country. On the other hand, the overall hospital mortality rate in CLD patients is 25.0% [95% CI: 2.0, 47.0, I2 = 94.6, p < 0.001 ] in Ethiopia. Conclusion. Hepatitis B virus, hepatitis C virus, and alcohol are the three most common contributors to CLD cases in Ethiopia. The authors warrant routine screening and strengthening of preventive and treatment programs for viral hepatitis B and C, further enhancing the alcohol policy of the country.

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Section: Discussionmentioning

confidence: 99%

Chronic Liver Disease in Ethiopia with a Particular Focus on the Etiological Spectrums: A Systematic Review and Meta-Analysis of Observational Studies

Tesfaye

Mulugeta

Bekele

et al. 2021

Canadian Journal of Gastroenterology and Hepatology

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“…Globally, end-stage liver disease is a primary cause of morbidity and mortality, accounting for more than one million deaths per year ( Cheemerla and Balakrishnan, 2021 ). End-stage liver disease is a growing public health hazard for which liver transplantation is the only available remedy.…”

Section: Introductionmentioning

confidence: 99%

Recent Advances in Liver Engineering With Decellularized Scaffold

Dai

Jiang

Huang

et al. 2022

Front. Bioeng. Biotechnol.

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Liver transplantation is currently the only effective treatment for patients with end-stage liver disease; however, donor liver scarcity is a notable concern. As a result, extensive endeavors have been made to diversify the source of donor livers. For example, the use of a decellularized scaffold in liver engineering has gained considerable attention in recent years. The decellularized scaffold preserves the original orchestral structure and bioactive chemicals of the liver, and has the potential to create a de novo liver that is fit for transplantation after recellularization. The structure of the liver and hepatic extracellular matrix, decellularization, recellularization, and recent developments are discussed in this review. Additionally, the criteria for assessment and major obstacles in using a decellularized scaffold are covered in detail.

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“…Chronic liver disease prevalence is increasing globally [ 1 ]. Repetitive liver damage, secondary to any cause of liver injury, results in progressive fibrosis, disrupted hepatic architecture, and aberrant regeneration [ 2 ].…”

Section: Introductionmentioning

confidence: 99%

Combining Hepatic and Splenic CT Radiomic Features Improves Radiomic Analysis Performance for Liver Fibrosis Staging

et al. 2022

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Background: The exact focus of computed tomography (CT)-based artificial intelligence techniques when staging liver fibrosis is still not exactly known. This study aimed to determine both the added value of splenic information to hepatic information, and the correlation between important radiomic features and information exploited by deep learning models for liver fibrosis staging by CT-based radiomics. Methods: The study design is retrospective. Radiomic features were extracted from both liver and spleen on portal venous phase CT images of 252 consecutive patients with histologically proven liver fibrosis stages between 2006 and 2018. The radiomics analyses for liver fibrosis staging were done by hepatic and hepatic–splenic features, respectively. The most predictive radiomic features were automatically selected by machine learning models. Results: When using splenic–hepatic features in the CT-based radiomics analysis, the average accuracy rates for significant fibrosis, advanced fibrosis, and cirrhosis were 88%, 82%, and 86%, and area under the receiver operating characteristic curves (AUCs) were 0.92, 0.81, and 0.85. The AUC of hepatic–splenic-based radiomics analysis with the ensemble classifier was 7% larger than that of hepatic-based analysis (p < 0.05). The most important features selected by machine learning models included both hepatic and splenic features, and they were consistent with the location maps indicating the focus of deep learning when predicting liver fibrosis stage. Conclusions: Adding CT-based splenic radiomic features to hepatic radiomic features increases radiomics analysis performance for liver fibrosis staging. The most important features of the radiomics analysis were consistent with the information exploited by deep learning.

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Global Epidemiology of Chronic Liver Disease

Cited by 349 publications

References 28 publications

Chronic Liver Disease in Ethiopia with a Particular Focus on the Etiological Spectrums: A Systematic Review and Meta-Analysis of Observational Studies

Chronic Liver Disease in Ethiopia with a Particular Focus on the Etiological Spectrums: A Systematic Review and Meta-Analysis of Observational Studies

Recent Advances in Liver Engineering With Decellularized Scaffold

Combining Hepatic and Splenic CT Radiomic Features Improves Radiomic Analysis Performance for Liver Fibrosis Staging

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