Accumulating awareness on the clinical significance and relevance of frailty in cirrhosis: Time to dig deeper into mechanistic basis!

Deng, You; Hui, Yangyang; Cui, Binxin; Xie, Wen; Sun, Chao

doi:10.1111/liv.15639

Cited by 4 publications

(1 citation statement)

References 100 publications

(203 reference statements)

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“…These findings also suggested that cirrhotic patients with frailty may be at high risk for receiving invasive treatments, which may be another potential reason for the poor long-term clinical outcomes of these patients [ 45 ]. Pathophysiologically, frailty has been related to upregulated inflammatory response, impaired systemic immune dysfunction, and gut microbiota disorder [ 46 – 48 ], which may also partly explain the association between frailty and poor TFS in patients with cirrhosis. Studies are warranted to determine the molecular pathways involved.…”

Section: Discussionmentioning

confidence: 99%

Frailty and transplant-free survival of patients with liver cirrhosis: A meta-analysis

Yuan,

Li,

Liu

et al. 2024

PLoS ONE

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Background Frailty is a common condition among patients with liver cirrhosis. Nonetheless, its role in predicting liver transplant-free survival (TFS) remains unclear. Aim This systematic review and meta-analysis were conducted to elucidate the relationship between frailty and TFS in patients with cirrhosis. Methods Cohort studies addressing the objective of this meta-analysis were extracted from PubMed, Embase, and Web of Science databases. Between-study heterogeneity was assessed with the Cochrane Q test, and the I^2 statistic was estimated. Random-effect models, considering potential heterogeneity, were employed to combine the results. Results The meta-analysis encompassed 17 cohort studies involving 6273 patients with cirrhosis, of whom 1983 (31.6%) were classified as frail at baseline. The follow-up periods in the included studies ranged from 3 to 29 months, with an average duration of 11.5 months. The analysis revealed that frailty was significantly associated with a poor TFS (risk ratio [RR]: 2.07, 95% confidence interval: 1.72 to 2.50, p<0.001; I2 = 51%). Sensitivity analyses that sequentially omitted one dataset consistently supported these findings (RR: 1.95 to 2.17, p<0.05 in all cases). Subgroup analyses based on variables such as study design, mean age of patients, baseline Model for End-Stage Liver Disease score, tool used for frailty evaluation, follow-up duration, and study quality score also yielded congruent results. Conclusions The evidence suggests that frailty may be an independent risk factor for poor TFS in patients with liver cirrhosis, thus emphasizing the importance of early identification and management of frailty in this population.

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Section: Discussionmentioning

confidence: 99%

Frailty and transplant-free survival of patients with liver cirrhosis: A meta-analysis

Yuan,

Li,

Liu

et al. 2024

PLoS ONE

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Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis

Yang,

Li,

Yang

et al. 2024

Briefings in Bioinformatics

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We sought to develop and validate a machine learning (ML) model for predicting multidimensional frailty based on clinical and laboratory data. Moreover, an explainable ML model utilizing SHapley Additive exPlanations (SHAP) was constructed. This study enrolled 622 patients hospitalized due to decompensating episodes at a tertiary hospital. The cohort data were randomly divided into training and test sets. External validation was carried out using 131 patients from other tertiary hospitals. The frail phenotype was defined according to a self-reported questionnaire (Frailty Index). The area under the receiver operating characteristics curve was adopted to compare the performance of five ML models. The importance of the features and interpretation of the ML models were determined using the SHAP method. The proportions of cirrhotic patients with nonfrail and frail phenotypes in combined training and test sets were 87.8% and 12.2%, respectively, while they were 88.5% and 11.5% in the external validation dataset. Five ML algorithms were used, and the random forest (RF) model exhibited substantially predictive performance. Regarding the external validation, the RF algorithm outperformed other ML models. Moreover, the SHAP method demonstrated that neutrophil-to-lymphocyte ratio, age, lymphocyte-to-monocyte ratio, ascites, and albumin served as the most important predictors for frailty. At the patient level, the SHAP force plot and decision plot exhibited a clinically meaningful explanation of the RF algorithm. We constructed an ML model (RF) providing accurate prediction of frail phenotype in decompensated cirrhosis. The explainability and generalizability may foster clinicians to understand contributors to this physiologically vulnerable situation and tailor interventions.

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Exercise Therapy for Patients with Chronic Liver Disease：Liver Rehabilitation

Matsuse,

Hashida,

Kawaguchi

2024

Jpn J Rehabil Med

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Accumulating awareness on the clinical significance and relevance of frailty in cirrhosis: Time to dig deeper into mechanistic basis!

Cited by 4 publications

References 100 publications

Frailty and transplant-free survival of patients with liver cirrhosis: A meta-analysis

Frailty and transplant-free survival of patients with liver cirrhosis: A meta-analysis

Development and validation of an explainable machine learning model for predicting multidimensional frailty in hospitalized patients with cirrhosis

Exercise Therapy for Patients with Chronic Liver Disease：Liver Rehabilitation

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