Predictive Risk Factors of Nonalcoholic Fatty Liver Disease in a Lean Chinese Population

Liu, Lu; Shi, Xiaolan; Gao, Jingwen; Xu, Chunfang; Liu, Xiaolin

doi:10.3390/jpm12121958

Cited by 5 publications

(4 citation statements)

References 47 publications

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“…Indeed, low TBIL[ 35 ] and creatinine levels may be associated with MAFLD risk. The descend creatinine levels in MAFLD are consistent with the findings of Liu et al [ 36 ]. The reduction in creatinine associated with MAFLD may be the result of sarcopenia, which is linked to low skeletal muscle mass and reduced function.…”

Section: Discussionsupporting

confidence: 92%

Impact renaming non-alcoholic fatty liver disease to metabolic associated fatty liver disease in prevalence, characteristics and risk factors

Huang,

Yin,

Zhou

et al. 2023

World J Hepatol

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Primary sclerosing cholangitis (PSC) is a chronic and progressive immune-mediated cholangiopathy causing biliary tree inflammation and scarring, leading to liver cirrhosis and end-stage liver disease. Diagnosis of PSC is challenging due to its nonspecific symptoms and overlap with other liver diseases. Despite the rising incidence of PSC, there is no proven medical therapy that can alter the natural history of the disease. While liver transplantation (LT) is the most effective approach for managing advanced liver disease caused by PSC, post-transplantation recurrence of PSC remains a challenge. Therefore, ongoing research aims to develop better therapies for PSC, and continued efforts are necessary to improve outcomes for patients with PSC. This article provides an overview of PSC’s pathogenesis, clinical presentation, and management options, including LT trends and future aspects. It also highlights the need for improved therapeutic options and ethical considerations in providing equitable access to LT for patients with PSC. Additionally, the impact of liver transplant on the quality of life and psychological outcomes of patients with PSC is discussed. Ongoing research into PSC’s pathogenesis and post-transplant recurrence is crucial for improved understanding of the disease and more effective treatment options.

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Section: Discussionsupporting

confidence: 92%

Impact renaming non-alcoholic fatty liver disease to metabolic associated fatty liver disease in prevalence, characteristics and risk factors

Huang,

Yin,

Zhou

et al. 2023

World J Hepatol

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“…Liu et al. [ 40 ] developed a nomogram based on seven laboratory profiles, including triglyceride levels. Wang et al.…”

Section: Discussionmentioning

confidence: 99%

LASSO-derived model for the prediction of lean-non-alcoholic fatty liver disease in examinees attending a routine health check-up

Hsu,

Wu,

et al. 2024

Annals of Medicine

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Background Lean individuals with non-alcohol fatty liver disease (NAFLD) often have normal body size but abnormal visceral fat. Therefore, an alternative to body mass index should be considered for prediction of lean-NAFLD. This study aimed to use representative visceral fat links with other laboratory parameters using the least absolute shrinkage and selection operator (LASSO) method to construct a predictive model for lean-NAFLD. Methods This retrospective cross-sectional analysis enrolled 2325 subjects with BMI < 24 kg/m 2 from medical records of 51,271 examinees who underwent a routine health check-up. They were randomly divided into training and validation cohorts at a ratio of 1:1. The LASSO-derived prediction model used LASSO regression to select 23 clinical and laboratory factors. The discrimination and calibration abilities were evaluated using the Hosmer–Lemeshow test and calibration curves. The performance of the LASSO model was compared with the fatty liver index (FLI) model. Results The LASSO-derived model included four variables—visceral fat, triglyceride levels, HDL-C-C levels, and waist hip ratio—and demonstrated superior performance in predicting lean-NAFLD with high discriminatory ability (AUC, 0.8416; 95% CI: 0.811–0.872) that was comparable with the FLI model. Using a cut-off of 0.1484, moderate sensitivity (75.69%) and specificity (79.86%), as well as high negative predictive value (95.9%), were achieved in the LASSO model. In addition, with normal WC subgroup analysis, the LASSO model exhibits a trend of higher accuracy compared to FLI (cut-off 15.45). Conclusions We developed a LASSO-derived predictive model with the potential for use as an alternative tool for predicting lean-NAFLD in clinical settings.

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“…It is not unique, another study from China also developed a prediction model to assess the risk of NAFLD in lean people. The model combined seven factors including ALT, TC, TG, LDL-c, Cr, UA, and hemoglobin HbA1c, with an AUC of 0.87 [30] . However, these prediction models only focus on the risk of NAFLD in non-obese people, and the prediction model for disease progression is still rare.…”

Section: Discussionmentioning

confidence: 99%

Develop a Clinical Scoring Model Based on Noninvasive Bioindicators to Predict Fibrosis Risk in Nonobese Nonalcoholic Fatty Liver Patients

Jin

Wang

Weng

et al. 2023

Preprint

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BACKGROUND: The presence of fibrosis is the main cause of the progression of nonalcoholic fatty liver disease (NAFLD). Our study aims to develop a simple clinical scoring system and nomogram for evaluating fibrosis in non-obese NAFLD patients. METHODS: This retrospective study included 99 non-obese NAFLD patients who underwent liver biopsy in China. The clinical scoring system and nomogram were used to predict the disease progression of NAFLD. RESULTS: Of the 99 non-obese patients with NAFLD, 41 (41.1%) were fibrosis. On multivariate logistic regression analysis, age, alanine aminotransferase(AST), platelet(PLT) and red blood cell (RBC) showed significant association with fibrosis (all P＜0.05). The area under curves (AUC) of the prediction model of fibrosis for non-obese patients established by the above four variables was 0.94 (95% confidence interval (CI):0.89-0.98). Moreover, the AUC of the further simplified clinical scoring model was 0.92 (95%CI 0.86-0.97). High risk group with score greater than or equal to 5, and low risk group with score less than or equal to 2. The nomogram had a good effect in evaluating the risk of fibrosis in non-obese NAFLD patients. CONCLUSION: A simple, easily calculated and non-invasive clinical score can reliably assess the presence of fibrosis in non-obese NAFLD patients. This scoring model complements the deficiency of the prediction system for disease progression in non-obese NAFLD patients, and brings good news for early identification and intervention of these patients.

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Predictive Risk Factors of Nonalcoholic Fatty Liver Disease in a Lean Chinese Population

Cited by 5 publications

References 47 publications

Impact renaming non-alcoholic fatty liver disease to metabolic associated fatty liver disease in prevalence, characteristics and risk factors

Impact renaming non-alcoholic fatty liver disease to metabolic associated fatty liver disease in prevalence, characteristics and risk factors

LASSO-derived model for the prediction of lean-non-alcoholic fatty liver disease in examinees attending a routine health check-up

Develop a Clinical Scoring Model Based on Noninvasive Bioindicators to Predict Fibrosis Risk in Nonobese Nonalcoholic Fatty Liver Patients

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