Red cell distribution width to platelet ratio predicts liver fibrosis in patients with autoimmune hepatitis

Use of Non-Invasive Biomarkers and Clinical Scores to Predict the Complications of Liver Cirrhosis: A Bicentric Experience

Background and objectives: Liver cirrhosis is a chronic, progressive condition characterized by fibrosis and architectural distortion of the liver, leading to impaired liver function and severe complications. Accurately predicting these complications is crucial to the improvement of patient outcomes. Therefore, this study aimed to evaluate the accuracy of various non-invasive biomarkers and clinical scores in assessing the risk of complications among cirrhotic patients. Materials and methods: We conducted an observational retrospective study involving 236 cirrhotic patients from two tertiary care hospitals in Italy and Romania, in a timespan ranging from January 2021 to March 2024. Data on clinical characteristics, liver function tests, hematological indices, various non-invasive biomarkers, and clinical scores were collected and analyzed. Receiver operating characteristic analysis was performed to assess the accuracy of these biomarkers and clinical scores in predicting complications, including the presence of varices and hepato-renal syndrome. Results: The Child-Pugh score showed the highest accuracy for cirrhosis-related complications, with an area under curve (AUC) = 0.667. The red cell distribution width coefficient of variation followed closely with an AUC = 0.646. While the Child-Pugh score had a high specificity (85.42%), its sensitivity was low (37.97%). In patients with varices, non-invasive scores such as platelet distribution width (PDW) and the RDW-to-platelet ratio (RPR) showed modest predictive ability, with an AUC = 0.594. For hepato-renal syndrome, the Model for End-Stage Liver Disease (MELD) score showed the highest diagnostic accuracy with an AUC = 0.758. Conclusions: The most reliable biomarkers for detecting complications, varices, and hepato-renal syndrome, are, respectively, the Child-Pugh Score, PDW along with RPR, and the MELD score. However, while these scores remain valuable, the moderate diagnostic accuracy of other indices suggests the need for a more integrated approach to risk stratification. Future research should focus on validating these tools across different populations and incorporating emerging biomarkers to enhance predictive accuracy and inform more effective clinical decision-making.

Development and validation of a noninvasive prediction model for significant hepatic liver fibrosis in Chinese patients with autoimmune hepatitis

INTRODUCTION AND OBJECTIVES

Autoimmune hepatitis (AIH) is a prevalent noninfectious liver disease. However, there is currently a lack of noninvasive tests appropriate for evaluating liver fibrosis in AIH patients. The objective of this study was to develop and validate a predictive model for noninvasive assessment of significant liver fibrosis (S ≥ 2) in patients to provide a reliable method for evaluating liver fibrosis in individuals with AIH.

MATERIALS AND METHODS

The clinical data of 374 AIH patients were analyzed. A prediction model was established through logistic regression in the training set, and bootstrap method was used to validate the models internally. In addition, the clinical data of 109 AIH patients were collected for external verification of the model.The model was expressed as a nomogram, and area under the curve (AUC) of the receiver operating characteristic (ROC), calibration curve, and decision curve analysis were used to evaluate the accuracy of the prediction model.

RESULTS

Logistic regression analysis revealed that age, platelet count (PLT), and the A/G ratio were identified as independent risk factors for liver fibrosis in AIH patients (P < 0.05). The diagnostic model that was composed of age, PLT and A/G was superior to APRI and FIB-4 in both the internal validation (0.872, 95%CI: 0.819-0.924) and external validation (0.829, 95%CI: 0.753-0.904).

CONCLUSIONS

Our predictive model can predict significant liver fibrosis in AIH patients more accurately, simply, and noninvasively.

Prognostic value of red cell distribution width in non-ST elevation myocardial infarction: A cohort study

Non-ST elevation myocardial infarction (NSTEMI) has a higher risk of long-term mortality than ST-elevation myocardial infarction; thus, identifying such high-risk patients is essential. Red cell distribution width (RDW) recently emerged as a strong predictor of mortality in several cardiovascular diseases, however, it is scarcely known whether RDW has a prognostic value in NSTEMI patients, therefore, this study aims to elucidate this issue. 421 consecutive patients with NSTEMI between January 2020 and June 2022 were prospectively enrolled. Patients were divided into 2 groups by the optimal cutoff value of RDW using time-dependent receiver operating characteristic curves. The optimal cutoff value of RDW for predicting all-cause mortality was 13.4 and the study population was divided into low RDW (≤13.4) and high RDW (>13.4). The primary endpoint of this study was long-term all-cause mortality. The secondary endpoint was the association between RDW and long-term adverse events, including heart failure, gastrointestinal hemorrhage, stroke events, re-infarction rate, cardiovascular mortality, and major adverse cardiovascular events. The association of RDW with the outcome was analyzed by Cox regression analysis. Patients with high RDW tended to be older, had a higher history of previous MI, a higher history of percutaneous coronary intervention, a higher level of neutrophil, high-sensitivity C-reactive protein, a lower level of albumin, and a lower level of ejection fraction (all P < .05). During a median follow-up of 720 days (IQR, 534-913 days), the all-cause mortality was significantly higher in the high RDW group than in the low RDW group (24.8% vs 6.3%, P < .001). In the multivariate Cox proportional hazard analysis, RDW > 13.4 was an independent predictor for long-term all-cause mortality [hazard ratio 3.008; 95% confidence interval 1.005, 9.003, P = .049]. Admission RDW could be used as a new biomarker for predicting long-term mortality in patients with NSTEMI, and high RDW was associated with an increased risk of all-cause mortality.

Non-Invasive Serum Biomarkers for the Diagnosis of Cirrhosis in Patients with Autoimmune Hepatitis (AIH) and AIH-Primary Biliary Cholangitis Overlap Syndrome (AIH-PBC): Red Cell Distribution Width to Platelet Ratio (RPR) Yielded the Most Promising Result

Several serum biomarkers for fibrosis assessment have been proposed in various liver diseases, but in autoimmune hepatitis (AIH) or overlap with primary biliary cholangitis (PBC; AIH-PBC) patients, the data are scarce. This retrospective cross-sectional study was conducted to validate six non-invasive biomarkers in the diagnosis of cirrhosis (F4 fibrosis) in such patients. We included adult patients diagnosed with AIH or AIH-PBC overlap syndrome who underwent a liver biopsy between 2011 and 2021. Laboratory data were collected to calculate the following scores: red cell distribution width to platelet ratio (RPR), aspartate aminotransferase/platelet ratio index (APRI), Fibrosis-4 index (FIB-4), aspartate aminotransferase (AST) to alanine aminotransferase (ALT) ratio (AAR), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-platelet ratio (LPR). A total of 139 patients were eligible (111 AIH and 28 AIH-PBC). The prevalence of cirrhosis was 35.3% (36% in AIH and 32.1% in AIH-PBC). The AUROCs of the RPR, FIB-4, APRI, AAR, LPR, and NLR in all patients were 0.742, 0.724, 0.650, 0.640, 0.609, and 0.585, respectively. RPR was significantly superior to APRI, NLR, and LPR. Moreover, RPR showed the highest AUROC (0.915) in the overlap AIH-PBC subgroup. In conclusion, RPR yielded the highest diagnostic accuracy to predict cirrhosis in AIH and AIH-PBC overlap syndrome patients, while FIB-4 was considerably optimal.

A novel web-based online nomogram to predict advanced liver fibrosis in patients with autoimmune hepatitis-primary biliary cholangitis overlap syndrome

Background

Patients with autoimmune hepatitis-primary biliary cholangitis (AIH-PBC) overlap syndrome have a worse prognosis compared to AIH or PBC alone and accurately predicting the severity and dynamically monitoring the progression of disease are therefore essential. We aimed to develop a nomogram-based model to predict advanced liver fibrosis in patients with AIH-PBC overlap syndrome.

Methods

A total of 121 patients with AIH-PBC overlap syndrome were retrospectively included and randomly assigned to a development set and a validation set. Backward stepwise regression's best model with the lowest AIC was employed to create a nomogram. Diagnose accuracy was evaluated using the area under the receiver operator characteristic curve (AUROC), calibration analysis, and decision curve analysis (DCA) and was compared with aspartate aminotransferase-to-platelet ratio (APRI) and fibrosis index based on four factors-4 (FIB-4) score.

Results

The median age of patients was 53.0 years (IQR: 46.0-63.0), and female patients accounted for 95.0 %. Platelets, globulin, total bilirubin, and prothrombin time were associated with advanced fibrosis (≥S3) and used to construct an AIH-PBC overlap syndrome fibrosis (APOSF)-nomogram (available online at https://ndth-zzy.shinyapps.io/APOSF-nomogram/). The AUROCs of APOSF-nomogram were 0.845 (95 % CI: 0.754-0.936) and 0.843 (95 % CI: 0.705-0.982) in development set and validation set respectively, which was significantly better than APRI and FIB-4. Calibration revealed that the estimated risk fits well with biopsy-proven observation. DCA outperformed APRI and FIB4 in terms of net benefit, demonstrating clinical utility.

Conclusion

This novel non-invasive web-based online APOSF-nomogram provided a convenient tool for identifying advanced fibrosis in patients with AIH-PBC overlap syndrome. Further prospective, multicenter studies with large sample size are necessary to validate the applicability of APOSF-nomogram.

Diagnostic role of transient elastography in patients with autoimmune liver diseases: A systematic review and meta-analysis

BACKGROUND

Noninvasive methods have been developed to detect fibrosis in many liver diseases due to the limits of liver biopsy. However, previous studies have focused primarily on chronic viral hepatitis and nonalcoholic fatty liver disease. The diagnostic value of transient elastography for autoimmune liver diseases (AILDs) is worth studying.

AIM

To compare the diagnostic accuracy of imaging techniques with serum biomarkers of fibrosis in AILD.

METHODS

The PubMed, Cochrane Library and EMBASE databases were searched. Studies evaluating the efficacy of noninvasive methods in the diagnosis of AILDs [autoimmune hepatitis (AIH), primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC)] were included. The summary area under the receiver operating characteristic curve (AUROC), diagnostic odds ratio, sensitivity and specificity were used to assess the accuracy of these noninvasive methods for staging fibrosis.

RESULTS

A total of 60 articles were included in this study, and the number of patients with AIH, PBC and PSC was 1594, 3126 and 501, respectively. The summary AUROC of transient elastography in the diagnosis of significant fibrosis, advanced fibrosis and cirrhosis in patients with AIH were 0.84, 0.88 and 0.90, respectively, while those in patients with PBC were 0.93, 0.93 and 0.91, respectively. The AUROC of cirrhosis for patients with PSC was 0.95. However, other noninvasive indices (aspartate aminotransferase to platelet ratio index, aspartate aminotransferase/alanine aminotransferase ratio, fibrosis-4 index) had corresponding AUROCs less than 0.80.

CONCLUSION

Transient elastography exerts better diagnostic accuracy in AILD patients, especially in PBC patients. The appropriate cutoff values for staging advanced fibrosis and cirrhosis ranged from 9.6 to 10.7 and 14.4 to 16.9 KPa for PBC patients.

An easy-to-use AIHF-nomogram to predict advanced liver fibrosis in patients with autoimmune hepatitis

Background

The evaluation of liver fibrosis is essential in the management of patients with autoimmune hepatitis (AIH). We aimed to establish and validate an easy-to-use nomogram to identify AIH patients with advanced liver fibrosis.

Methods

AIH patients who underwent liver biopsies were included and randomly divided into a training set and a validation set. The least absolute shrinkage and selection operator (LASSO) regression was used to select independent predictors of advanced liver fibrosis from the training set, which were utilized to establish a nomogram. The performance of the nomogram was evaluated using the receiver characteristic curve (ROC), calibration curve, and decision curve analysis (DCA).

Results

The median age of 235 patients with AIH was 54 years old, with 83.0% of them being female. Six independent factors associated with advanced fibrosis, including sex, age, red cell distribution width, platelets, alkaline phosphatase, and prothrombin time, were combined to construct a predictive AIH fibrosis (AIHF)-nomogram. The AIHF-nomogram showed good agreement with real observations in the training and validation sets, according to the calibration curve. The AIHF-nomogram performed significantly better than the fibrosis-4 and aminotransferase-to-platelet ratio scores in the training and validation sets, with an area under the ROCs for predicting advanced fibrosis of 0.804 in the training set and 0.781 in the validation set. DCA indicated that the AIHFI-nomogram was clinically useful. The nomogram will be available at http://ndth-zzy.shinyapps.io/AIHF-nomogram/as a web-based calculator.

Conclusions

The novel, easy-to-use web-based AIHF-nomogram model provides an insightful and applicable tool to identify AIH patients with advanced liver fibrosis.

The Usefulness of Extended Inflammation Parameters and Systemic Inflammatory Response Markers in the Diagnostics of Autoimmune Hepatitis

(1) Introduction: Autoimmune hepatitis (AIH) is a chronic disease. A persistent autoimmune reaction in the liver is significantly related to the systemic inflammatory response. Extended Inflammation Parameters (EIP) can be used to assess the activation of immune cells such as activated neutrophils (NEUT-RI and NEUT-GI) and activated lymphocytes (RE-LYMP and AS-LYMP) in the phase of active inflammation. The role of the systemic inflammatory response markers should also be emphasised, especially: NLR, PLR, and RLR, which have recently been widely studied as markers in autoimmune skin diseases or liver diseases. (2) Materials and Methods: The study included 30 patients with AIH and 30 healthy volunteers. The parameters of the EIP group (RE-LYMP, AS-LYMP, NEUT-RI, NEUT-GI), calculated haematological indices Red Blood Cell Distribution Width-to-Platelet Ratio (RPR), Mean Platelet Volume-to-Platelet Ratio (MPR), Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), Red Blood Cell Distribution Width-to-Lymphocyte Ratio (RLR), and selected blood morphological and biochemical indices were analysed. The aim of the study was to assess the usefulness of the EIP and systemic inflammatory response markers in the diagnostics of AIH. (3) Results: Compared to the controls, the patients with AIH showed significantly higher EIP values: NEUT-RI (48.05 vs. 43.30), NEUT-GI (152.65 vs. 147.40), RE-LYMP (0.07 vs. 0.03), and the inflammatory response markers: MPR (0.05 vs. 0.04), RPR (0.07 vs. 0.05), and NLR (2.81 vs. 1.42. Among the examined markers, EIP has significant diagnostic potential: NEUT-RI (AUC = 0.86), NEUT-GI (AUC = 0.80), and RE-LYMP (AUC = 0.78), and so do calculated haematological indices, i.e., MPR (AUC = 0.75), PLR (AUC = 1.00), and RLR (AUC = 1.00) Moreover, the importance of NEUT-GI (AUC = 0.89), MPR (AUC = 0.93), PLR (AUC = 0.86), RPR (AUC = 0.91), and FIB-4 (AUC = 0.83) in the detection of liver fibrosis in the course of AIH has also been proven. (4) Conclusions: EIP and systemic inflammatory response markers may turn out to be useful in detecting AIH and in looking for features of already developed liver cirrhosis in its course.

Aspartate Aminotransferase to Platelet Ratio Index and Fibrosis-4 Index for Detecting Liver Fibrosis in Patients With Autoimmune Hepatitis: A Meta-Analysis

Background

Aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 index (FIB-4) are the two most widely studied noninvasive markers of liver fibrosis. We aimed to assess the diagnostic accuracy of APRI and FIB-4 for liver fibrosis in patients with autoimmune hepatitis (AIH) using liver biopsy as the reference standard.

Methods

PubMed, EMBASE, Cochrane Library and Web of Science databases were searched for studies (published as of May 1st, 2021) that assessed the diagnostic performance of APRI and FIB-4 for liver fibrosis in AIH. The summary area under receiver operating characteristics curve (AUROC), sensitivity, specificity, diagnostic odds ratios were used to assess the diagnostic accuracy of APRI and FIB-4 for detecting liver fibrosis.

Results

Fourteen studies (including 1015 patients) were selected with 13 studies each evaluating the use of APRI and FIB-4 for detecting different stages of fibrosis in AIH. For prediction of significant fibrosis, advanced fibrosis, and cirrhosis, the summary AUROC value was 0.66 [95% confidence interval (CI): 0.61-0.70], 0.71 (95% CI: 0.67-0.75), and 0.75 (95% CI: 0.71-0.79) for APRI, and the summary AUROC value was 0.75 (95% CI: 0.71-0.79), 0.73 (95% CI: 0.69-0.77) and 0.79 (95% CI: 0.75-0.82) for FIB-4, respectively. The summary sensitivity and specificity for diagnosis of significant fibrosis, advanced fibrosis, and cirrhosis were 90% and 36%, 78% and 55%, and 77% and 61% for APRI, and 70% and 70%, 65% and 70%, and 78% and 65% for FIB-4, respectively.

Conclusions

APRI and FIB-4 showed suboptimal diagnostic performance for identifying liver fibrosis in AIH with mediocre sensitivity and specificity.

Association between red blood cell distribution width and in-hospital mortality in acute myocardial infarction

Previous studies have shown an independent association between increased red cell distribution width (RDW) and mortality after acute myocardial infarction (AMI). However, evidence regarding the predictive significance of repeated measures of RDW in patients with AMI remains scarce. We aimed to investigate the association between the dynamic profile of RDW and in-hospital mortality in patients with AMI.This was a cross-sectional study. We extracted clinical data from the Medical Information Mart for Intensive Care IIIV1.4 database. Demographic data, vital signs, laboratory test data, and comorbidities were collected from the database. The clinical endpoint was in-hospital mortality. Cox proportional hazards models were used to evaluate the prognostic values of basic RDW, and the Kaplan-Meier method was used to plot survival curves. Subgroup analyses were performed to measure mortality across various subgroups. The repeated-measures data were compared using a generalized additive mixed model.In total, 3101eligible patients were included. In multivariate analysis, adjusted for age, sex, and ethnicity, RDW was a significant risk predictor of in-hospital mortality. Furthermore, after adjusting for more confounding factors, RDW remained a significant predictor of in-hospital mortality (tertile 3 vs tertile 1: hazard ratio 2.3; 95% confidence interval 1.39-4.01; P for trend <.05). The Kaplan-Meier curve for tertiles of RDW indicated that survival rates were highest when RDW was ≤13.2% and lowest when RDW was ≥14.2% after adjustment for age, sex, and ethnicity. During the intensive care unit stay, the RDW of nonsurvivors progressively increased until death occurred.Our findings showed that a higher RDW was associated with an increased risk of in-hospital mortality in patients with AMI.