Low eosinophil count predicts in-hospital mortality in cirrhosis with systemic inflammatory response syndrome

Identification of multiple complications as independent risk factors associated with 1-, 3-, and 5-year mortality in hepatitis B-associated cirrhosis patients

BACKGROUND

Hepatitis B-associated cirrhosis (HBC) is associated with severe complications and adverse clinical outcomes. This study aimed to develop and validate a predictive model for the occurrence of multiple complications (three or more) in patients with HBC and to explore the effects of multiple complications on HBC prognosis.

METHODS

In this retrospective cohort study, data from 121 HBC patients treated at Nanjing Second Hospital from February 2009 to November 2019 were analysed. The maximum follow-up period was 10.75 years, with a median of 5.75 years. Eight machine learning techniques were employed to construct predictive models, including C5.0, linear discriminant analysis (LDA), least absolute shrinkage and selection operator (LASSO), k-nearest neighbour (KNN), gradient boosting decision tree (GBDT), support vector machine (SVM), generalised linear model (GLM) and naive Bayes (NB), utilising variables such as medical history, demographics, clinical signs, and laboratory test results. Model performance was evaluated via receiver operating characteristic (ROC) curve analysis, residual analysis, calibration curve analysis, and decision curve analysis (DCA). The influence of multiple complications on HBC survival time was assessed via Kaplan‒Meier curve analysis. Furthermore, LASSO and univariable and multivariable Cox regression analyses were conducted to identify independent prognostic factors for overall survival (OS) in patients with HBC, followed by ROC, C-index, calibration curve, and DCA curve analyses of the constructed prognostic nomogram model. This study utilized bootstrap resampling for internal validation and employed the Medical Information Mart for Intensive Care IV (MIMIC-IV) database for external validation.

RESULTS

The GBDT model exhibited the highest area under the curve (AUC) and emerged as the optimal model for predicting the occurrence of multiple complications. The key predictive factors included posthospitalisation fever (PHF), body mass index (BMI), retinol binding protein (RBP), total bilirubin (TB) levels, and eosinophils (EOS). Kaplan-Meier analysis revealed that patients with multiple complications had significantly worse OS than those with fewer complications. Additionally, multivariable Cox regression analysis, informed by least absolute shrinkage and LASSO selection, identified hepatocellular carcinoma (HCC), multiple complications, and lactate dehydrogenase (LDH) levels as independent prognostic factors for OS. The prognostic model demonstrated 1-year, 3-year, and 5-year OS ROC AUCs of 0.802, 0.793, and 0.817, respectively. For the internal validation cohort, the corresponding AUC values were 0.797, 0.832, and 0.835. In contrast, the external validation cohort yielded a 1-year ROC AUC of 0.707. Calibration curves indicated good consistency of the model, and DCA demonstrated the model's clinical utility, showing high net benefits within certain threshold ranges. Compared with the univariable models, the multivariable ROC curves indicated higher AUC values for this prognostic model, and the model also possessed the best c-index.

CONCLUSION

The GBDT prediction model provides a reliable tool for the early identification of high-risk HBC patients prone to developing multiple complications. The concurrent occurrence of multiple complications is an independent prognostic factor for OS in patients with HBC. The constructed prognostic model demonstrated remarkable predictive performance and clinical applicability, indicating its crucial role in enhancing patient outcomes through timely and targeted interventions.

The role of eosinophils in sepsis and acute respiratory distress syndrome: a scoping review

PURPOSE

Septic shock and acute respiratory distress syndrome (ARDS) are characterized by a dysregulated immune host response that may respond to steroid therapy. Eosinophils contribute to type 2 inflammation that often responds to steroid therapy; their role in immune dysregulation and outcomes in sepsis and ARDS is unclear.

SOURCE

A systematic search of Cochrane Library, MEDLINE, and EMBASE was performed from inception to 9 September 2020. The search comprised the following terms: eosinophils, sepsis, septic shock, and ARDS. Two reviewers independently screened abstracts and texts and extracted data on disease severity and clinical outcomes.

PRINCIPAL FINDINGS

Thirty-nine studies were identified: 30 evaluated serum eosinophil count in sepsis, one evaluated eosinophil activity in sepsis, three assessed bronchoalveolar lavage (BAL) eosinophil count in ARDS, four assessed eosinophil activity in ARDS, and one assessed peripheral eosinophil count in ARDS. Eleven studies showed an association between eosinopenia and sepsis, and eight studies found persistent eosinopenia at > 48 hr of intensive care unit admission to predict mortality and readmission in septic patients. Three studies found BAL eosinophil count to be low in ARDS, although one found that levels rose in late-phase ARDS. Three studies found eosinophil activity markers in BAL to be high in ARDS and correlate with ARDS severity.

CONCLUSION

Persistent peripheral eosinopenia is a marker of bacterial sepsis and is independently associated with poor outcomes. Bronchoalveolar lavage eosinophil counts are low in early-phase ARDS, but increase in late-phase ARDS, while elevated markers of eosinophil activity correlate with ARDS severity. Further studies understanding the mechanisms leading to eosinopenia in sepsis and increased eosinophil activity in ARDS are needed.

Low Absolute Eosinophil Count Predicts In-Hospital Mortality in Cirrhosis With Systemic Inflammatory Response Syndrome

Introduction

Chronic liver disease (CLD) or Cirrhosis is one of the most common causes of morbidity as well as mortality. Child-Turcotte-Pugh (CTP) score and the model for end-stage liver disease (MELD) are useful to assess the long-term prognosis of a patient with CLD. When a patient with CLD is admitted with an acute illness leading to systemic inflammatory response syndrome (SIRS), these scores may not be reliable to predict the short-term prognosis and survival. Absolute eosinophils count (AEC) allows the rapid identification of patients at increased risk for sepsis-related mortality in patients.

Methods

This was a cross-sectional study conducted among patients in a tertiary care hospital in South India during a period of one and a half years between October 2018 and April 2020. Cirrhotic patients with SIRS aged between 16 years and 80 years were included in the study. AEC was measured as a part of automated complete blood counts. Patient demographics, lab parameters, and outcomes in terms of mortality were studied. Continuous variables were expressed as mean ± SD/median and categorical variables were expressed in frequency. Receiver operating characteristic (ROC) curve analysis was used to find an ideal cutoff for AEC in predicting hospital mortality. Multi-variate Cox regression analysis was performed to find predictors of mortality.

Results

A total of 100 patients who fit the pre-determined criteria for cirrhosis with SIRS were enrolled in the study. Sixteen (16%) patients died at the end of the study while 84 (84%) were alive. Using a ROC curve, the area under the curve (AUC) was 0.716 with 95% CI of AUC (0.564-0.867), the p-value was found to 0.006, a cut-off of eosinophil count of 198.5 cells/uL was found to be the cut-off for the prediction of in-hospital mortality in this subset of patients with cirrhosis and sepsis with SIRS, with a sensitivity of 75% and specificity of 38.1%. In a multi-variate Cox regression analysis, only age (hazard ratio {HR}: 1.175, 95%CI, 1.084 to 1.275, p<0.001) , CRP (HR : 1.008, 95%CI, 1.00 to 1.015, p=0.042) values, total leukocyte counts (TLC) (HR: 1.226, 95%CI, 1.116 to 1.346, p<0.001) and AEC (HR: 0.993, 95%CI, 0.987 to 0.999, p=0.016) were found to be statistically significant independent predictors of mortality.

Conclusions

The presence of eosinopenia may be considered as an in-expensive warning biomarker for poorer clinical outcomes in the form of in-hospital mortality in hospitalized cirrhotic patients. Other biomarkers such as CRP and TLC could also play a role both independently and in conjunction with AEC to predict outcomes and mortality in cirrhotic patients with sepsis and SIRS.

Presepsin teardown - pitfalls of biomarkers in the diagnosis and prognosis of bacterial infection in cirrhosis

AIM

To evaluate the diagnostic and prognostic value of presepsin in cirrhosis-associated bacterial infections.

METHODS

Two hundred and sixteen patients with cirrhosis were enrolled. At admission, the presence of bacterial infections and level of plasma presepsin, serum C-reactive protein (CRP) and procalcitonin (PCT) were evaluated. Patients were followed for three months to assess the possible association between presepsin level and short-term mortality.

RESULTS

Present 34.7 of patients had bacterial infection. Presepsin levels were significantly higher in patients with infection than without (median, 1002 pg/mL vs 477 pg/mL, P < 0.001), increasing with the severity of infection [organ failure (OF): Yes vs No, 2358 pg/mL vs 710 pg/mL, P < 0.001]. Diagnostic accuracy of presepsin for severe infections was similar to PCT and superior to CRP (AUC-ROC: 0.85, 0.85 and 0.66, respectively, P = NS for presepsin vs PCT and P < 0.01 for presepsin vs CRP). At the optimal cut-off value of presepsin > 1206 pg/mL sensitivity, specificity, positive predictive values and negative predictive values were as follows: 87.5%, 74.5%, 61.8% and 92.7%. The accuracy of presepsin, however, decreased in advanced stage of the disease or in the presence of renal failure, most probably because of the significantly elevated presepsin levels in non-infected patients. 28-d mortality rate was higher among patients with > 1277 pg/mL compared to those with ≤ 1277 pg/mL (46.9% vs 11.6%, P < 0.001). In a binary logistic regression analysis, however, only PCT (OR = 1.81, 95%CI: 1.09-3.01, P = 0.022) but neither presepsin nor CRP were independent risk factor for 28-d mortality after adjusting with MELD score and leukocyte count.

CONCLUSION

Presepsin is a valuable new biomarker for defining severe infections in cirrhosis, proving same efficacy as PCT. However, it is not a useful marker of short-term mortality.

Role of systemic inflammation in cirrhosis: From pathogenesis to prognosis

The natural history of cirrhosis can be divided into an initial stage, known as compensated cirrhosis, and an advanced stage which encompasses both decompensated cirrhosis and acute-on-chronic liver failure (ACLF). The latter syndrome has been recently described as an acute deterioration of liver function in patients with cirrhosis, which is usually triggered by a precipitating event and results in the failure of one or more organs and high short-term mortality rates. Each stage is characterized by distinctive clinical manifestations and prognoses. One of the key elements involved in cirrhosis physiopathology is systemic inflammation, recently described as one of the components in the cirrhosis-associated immune dysfunction syndrome. This syndrome refers to the combination of immune deficiency and exacerbated inflammation that coexist during the course of cirrhosis and relates to the appearance of clinical complications. Since systemic inflammation is often difficult to assess in cirrhosis patients, new objective, reproducible and readily-available markers are needed in order to optimize prognosis and lengthen survival. Thus, surrogate serum markers and clinical parameters of systemic inflammation have been sought to improve disease follow-up and management, especially in decompensated cirrhosis and ACLF. Leukocyte counts (evaluated as total leukocytes, total eosinophils or neutrophil:lymphocyte ratio) and plasma levels of procalcitonin or C-reactive protein have been proposed as prognostic markers, each with advantages and shortcomings. Research and prospective randomized studies that validate these and other markers are clearly warranted.

Genotype 3 and higher low-density lipoprotein levels are predictors of good response to treatment of recurrent hepatitis C following living donor liver transplantation

BACKGROUND

Treatment of recurrent hepatitis C after liver transplantation is associated with poor sustained virological response (SVR) in genotype 1, and data on genotype 3 is limited to small numbers. We report one of the largest series of genotype 3 patients treated for recurrent hepatitis C following living donor liver transplantation (LDLT).

METHODS

From January 2002 to November 2013, of 1349 transplants, 359 patients had hepatitis C. Patients with histological recurrence were treated with pegylated interferon in escalating dose regimen for 48 weeks and weight-based ribavirin. Virological response was defined as rapid virological response (RVR-4 weeks), early virological response (EVR-12 weeks), end of treatment response (ETR-48 weeks), and SVR (24 weeks after end of treatment). SVR and no-SVR groups were compared for age, sex, body mass index (BMI), diabetes, total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, ferritin, genotype, and hepatitis C virus (HCV) RNA levels before initiation of treatment.

RESULTS

The study included 67 patients who had at least 18 months of follow up after treatment initiation (45 males), aged 51 ± 6.3 years. Treatment was started after 16 months (median); baseline median RNA was 2.7 × 10(6) IU/mL. There was no significant difference between the SVR and no-SVR groups regarding age, sex ratio, follow up period, total cholesterol, triglycerides, HDL, BMI, prevalence of diabetes, HCV RNA, and ferritin levels. Genotype 3, RVR, EVR, ETR, and higher LDL levels were significantly associated with SVR. Genotype 3 had a significantly higher SVR rate of 71 % as compared to an SVR rate of only 14 % in genotype 1, p = 0.0003. Absence of RVR and EVR predicted treatment failure with a specificity of 88 % and 92 %, respectively.

CONCLUSION

Genotype 3 and higher LDL levels predict SVR in patients treated for hepatitis C recurrence following LDLT, whereas absence of RVR and EVR strongly predict treatment failure.