Laparoscopic cholecystectomy: Histopathological analysis of metabolic associated fatty liver disease and fibrosis

Rodríguez-Antonio, Itzayana; López-Sánchez, Guillermo Nahúm; Reyes-Gómez, Victor Alfonso; Contreras-Flores, Ericka Hazzel; Farías-García, Fernanda; Espejel-Deloiza, Mariana; Durán-Padilla, Marco A; Chablé-Montero, Fredy; Uribe, Misael; Chávez-Tapia, Norberto C.; Montalvo-Javé, Eduardo E.; Nuño‐Lámbarri, Natalia

doi:10.1016/j.aohep.2021.100651

Cited by 6 publications

(4 citation statements)

References 18 publications

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“…Cortés et al [ 64 ] conducted an interesting study evaluating the effect of cholecystectomy on hepatic fat accumulation and IR in non-obese Hispanic patients; it was obtained as a conclusion that cholecystectomy is a risk factor of metabolic syndrome-associated complications, particularly NAFLD. Rodríguez-Antonio et al [ 16 ] also performed an observational study in which they emphasized the importance of early detection of risk factors and potential complications in patients diagnosed with MASLD who undergo cholecystectomy. They consider medical follow-up necessary after surgery to monitor liver function and prevent long-term complications.…”

Section: Discussionmentioning

confidence: 99%

“…Symptomatic cholelithiasis is the main indication of cholecystectomy, either by biliary colic or complicated gallstone disease (acute cholecystitis, cholangitis or acute biliary pancreatitis) [ 14 ]. It is also the main biliary manifestation of the metabolic syndrome, closely related with an MASLD diagnosis [ 15 , 16 , 17 ]. Most of the published studies have focused on complications after surgery [ 13 , 14 , 18 , 19 , 20 ], but there is also evidence that cholecystectomy has metabolic effects, especially in NAFLD patients [ 21 , 22 , 23 ].…”

Section: Introductionmentioning

confidence: 99%

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A Machine Learning-Based Method for Detecting Liver Fibrosis

Suárez,

Martínez,

Torres

et al. 2023

Diagnostics

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Cholecystectomy and Metabolic-associated steatotic liver disease (MASLD) are prevalent conditions in gastroenterology, frequently co-occurring in clinical practice. Cholecystectomy has been shown to have metabolic consequences, sharing similar pathological mechanisms with MASLD. A database of MASLD patients who underwent cholecystectomy was analysed. This study aimed to develop a tool to identify the risk of liver fibrosis after cholecystectomy. For this purpose, the extreme gradient boosting (XGB) algorithm was used to construct an effective predictive model. The factors associated with a better predictive method were platelet level, followed by dyslipidaemia and type-2 diabetes (T2DM). Compared to other ML methods, our proposed method, XGB, achieved higher accuracy values. The XGB method had the highest balanced accuracy (93.16%). XGB outperformed KNN in accuracy (93.16% vs. 84.45%) and AUC (0.92 vs. 0.84). These results demonstrate that the proposed XGB method can be used as an automatic diagnostic aid for MASLD patients based on machine-learning techniques.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Machine Learning-Based Method for Detecting Liver Fibrosis

Suárez,

Martínez,

Torres

et al. 2023

Diagnostics

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“…In the general population, the reported prevalence of gallbladder polyps is 4-7% (2). Cholelithiasis is widespread and associated with common risk factors such as obesity, hypertriglyceridemia, and fasting glucose levels (5).…”

Section: Introductionmentioning

confidence: 99%

Correlation between the histopathological findings of gallbladder samples and clinical outcomes within the framework of a hybrid study

Kasalovic,

Igrutinovic,,

Jakovljevic,

et al. 2024

Interciencia

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Background: This study focuses on the histopathological characteristics of benign and potentially malignant lesions of the gallbladder, with a specific emphasis on the efficacy of cholecystectomy as a secondary preventive measure in specific clinical contexts. The aim is to contribute to the development of improved preventive and therapeutic approaches. Methodology: This research study employed a hybrid approach of retrospective and prospective data analysis on cholecystitis during the year 2023. Various variables were analyzed to explore their associations with clinical outcomes. Results: The study included 63 patients, with no statistically significant differences in age between male and female patients. Analysis of the length, width, and thickness of the gallbladder wall did not reveal statistically significant differences (p > 0.05). Correlation analysis showed weak connections between age and gallbladder characteristics. The average recovery time was 4.46 days, and the duration of hospitalization positively correlated with age (p<0.001). Regression analysis indicated an association between symptoms and age and the duration of hospitalization (p = 0.015, p<0.001). Logistic regression demonstrated an accuracy of 61.9%, with high precision in predicting stays longer than 3 days. Chi-square tests confirmed statistically significant differences in histopathological diagnoses related to comorbidities (p = 0.021). Conclusion: Gender-specific approaches in postoperative treatment of patients with gallbladder issues highlight significant differences in patient characteristics, while the analysis of comorbidities reveals a connection between hypertension and pathological changes in the gallbladder.

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“…Gallstones and MAFLD may develop concurrently, and their association is strongly influenced by the presence of common risk factors, such as those mentioned earlier (i.e., epigenetics, genetic variations, metabolic factors) [18]. In addition to insulin resistance (IR), other significant mechanisms contributing to metabolic dysfunction have been investigated, notably the dysfunction of FXR signaling [19].…”

Section: Introductionmentioning

confidence: 99%

Molecular Mechanisms Involved in MAFLD in Cholecystectomized Patients: A Cohort Study

Pal,

Castillo-Castañeda,

Díaz-Orozco

et al. 2023

Genes

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Gallstone disease and metabolic dysfunction-associated fatty liver disease (MAFLD) share numerous common risk factors and progression determinants in that they both manifest as organ-specific consequences of metabolic dysfunction. Nevertheless, the precise molecular mechanisms underlying fibrosis development in cholecystectomized MAFLD patients remain inadequately defined. This study aimed to investigate the involvement of farnesoid X receptor 1 (FXR1) and fibroblast growth factor receptor 4 (FGFR4) in the progression of fibrosis in cholecystectomized MAFLD patients. A meticulously characterized cohort of 12 patients diagnosed with MAFLD, who had undergone liver biopsies during programmed cholecystectomies, participated in this study. All enrolled patients underwent a follow-up regimen at 1, 3, and 6 months post-cholecystectomy, during which metabolic biochemical markers were assessed, along with elastography, which served as indirect indicators of fibrosis. Additionally, the hepatic expression levels of FGFR4 and FXR1 were quantified using quantitative polymerase chain reaction (qPCR). Our findings revealed a robust correlation between hepatic FGFR4 expression and various histological features, including the steatosis degree (r = 0.779, p = 0.023), ballooning degeneration (r = 0.764, p = 0.027), interphase inflammation (r = 0.756, p = 0.030), and steatosis activity score (SAS) (r = 0.779, p = 0.023). Conversely, hepatic FXR1 expression did not exhibit any significant correlations with these histological features. In conclusion, our study highlights a substantial correlation between FGFR4 expression and histological liver damage, emphasizing its potential role in lipid and glucose metabolism. These findings suggest that FGFR4 may play a crucial role in the progression of fibrosis in cholecystectomized MAFLD patients. Further research is warranted to elucidate the exact mechanisms through which FGFR4 influences metabolic dysfunction and fibrosis in this patient population.

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Laparoscopic cholecystectomy: Histopathological analysis of metabolic associated fatty liver disease and fibrosis

Cited by 6 publications

References 18 publications

A Machine Learning-Based Method for Detecting Liver Fibrosis

A Machine Learning-Based Method for Detecting Liver Fibrosis

Correlation between the histopathological findings of gallbladder samples and clinical outcomes within the framework of a hybrid study

Molecular Mechanisms Involved in MAFLD in Cholecystectomized Patients: A Cohort Study

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