Systemic Inflammatory Response Syndrome in Patients Hospitalized for Acute Decompensation of Cirrhosis

Novel predictors of response to therapy with terlipressin and albumin in hepatorenal syndrome-acute kidney injury

Background

A combination of terlipressin and albumin is the first-line pharmacologic treatment for hepatorenal syndrome-acute kidney injury (HRS-AKI). We assessed the response rates to terlipressin-albumin therapy in patients with HRS-AKI and determined early predictors of treatment response and survival.

Methods

A total of 84 patients with HRS-AKI (International Club of Ascites definition 2015) treated with terlipressin-albumin were included. Predictors of HRS reversal were identified by logistic regression analysis. Survival analysis was performed using the Kaplan-Meier method, and Cox regression models were used to determine independent predictors of mortality.

Results

Complete response to therapy was observed in 54.8%, partial response in 14.3%, and no response in 31% of patients. The factors associated with complete treatment response were the presence of systemic inflammatory response syndrome (SIRS), baseline serum creatinine, a rise in mean arterial pressure by day 3, and a reduction in the renal resistive index (ΔRRI) by day 3 of treatment. Independent predictors of HRS reversal were the presence of SIRS at baseline (P=0.022; odds ratio [OR] 15.74, 95% confidence interval [CI] 1.47-167.82) and ΔRRI ≥5% by day 3 of treatment (P=0.048; OR 6.67, 95%CI 1.021-43.62). Mean transplant-free survival at 6 months was significantly better in treatment responders (148 vs. 90 days, P<0.001). Independent predictors of 6-month mortality were response to treatment (P=0.004) and model for end-stage liver disease-sodium >23 (P=0.018).

Conclusions

SIRS and ΔRRI are simple parameters to predict treatment response in HRS-AKI. Non-responders have higher mortality and should be identified early to expedite liver transplantation.

Is the SIRS Criteria a Good Predictor of Blood stream Infection in Cirrhosis? A Single-Center Retrospective Analysis

Introduction

Cirrhosis-associated immune dysfunction (CAID) is a chronic vasodilatory state with hyperdynamic circulation and alterations in thermoregulation that may make patients more susceptible to and mask underlying infection. This study aims to determine whether SIRS criteria are an accurate tool for predicting bloodstream infection (BSI) in cirrhosis.

Methods

In our retrospective chart review, study population included patients with cirrhosis that were 18 years or older. For all study patients, model for end-stage liver disease (MELD) scores and values for each SIRS variable at the time of admission and blood culture data were recorded. Univariable and multivariable logistic regression analysis was performed to identify any associations between dichotomized SIRS variables that fulfill SIRS positivity and BSI.

Results

Significantly more patients without BSI met positivity criteria for WBC counts (30% vs 13% p < .001). In the analysis of the SIRS variables as continuous variables in prediction of BSI, the AUC curves generated were all unsatisfactory with the temperature (36-38°C) and WBC count (4 × 103 to 12 × 103 mcL) at the time of admission having the highest areas under the ROC curve (0.52 and 0.55, respectively). Looking at the SIRS variables dichotomized (according to whether fulfilling SIRS criteria or not) in univariable logistic regression, only WBC counts meeting SIRS criteria were significantly associated with BSI OR 0.37 (0.18-0.77); p = .008, but this was an inverse association. This association was true even in the multivariable model OR 0.38 (0.18-0.80); p = .01.

Conclusion

Our study shows that SIRS criteria are a poor predictor of BSI among patients with cirrhosis.

Scoring system for predicting 90-day mortality of in-hospital liver cirrhosis patients at Cipto Mangunkusumo Hospital

BACKGROUND

Liver cirrhosis is the final stage of chronic liver disease. Complications due to progression of liver disease may deteriorate the liver function and worsen prognosis. Previous studies have shown that patients with liver cirrhosis are at increased risk of death within 90-day after hospitalization. It is necessary to identify patients who are at higher risk of early mortality. This study aims to develop a scoring system to predict the 90-day mortality among hospitalized patients with liver cirrhosis that could be used for modification of treatment plan according to the scores that have been obtained. By using this scoring system, crucial care of plans can be taken to reduce the risk of mortality.

METHOD

This prospective cohort study was conducted on hospitalized cirrhotic patients at Cipto Mangunkusumo National General Hospital, Jakarta. Demographic, clinical, and laboratory data were recorded. Patients were monitored for up to 90-day after hospitalization to determine their condition. Cox regression analysis was performed to obtain predictor factors contributing to mortality in liver cirrhosis patients. The scoring system that resulted from this study categorized patients into low, moderate, and high-risk categories based on their predicted mortality rates. The sensitivity and specificity of the scoring system were evaluated using the AUC (area under the curve) metric.

RESULT

The study revealed that liver cirrhosis patients who were hospitalized had a 90-day mortality rate of 42.2%, with contributing factors including Child-Pugh, MELD, and leukocyte levels. The combination of these variables had a good discriminative value with an AUC of 0.921 (95% CI: 0.876-0.967). The scoring system resulted in three risk categories: low risk (score of 0-3) with a 4.1-18.4% probability of death, moderate risk (score of 5-6) with a 40.5-54.2% probability of death, and high risk (score of 8-11) with a 78.1-94.9% probability of death.

CONCLUSION

The scoring system has shown great accuracy in predicting 90-day mortality in hospitalized cirrhosis patients, making it a valuable tool for identifying the necessary care and interventions needed for these patients upon admission.

Prognostic performance of the REDS score, SOFA score, NEWS2 score, and the red-flag, NICE high-risk, and SIRS criteria to predict survival at 180 days, in emergency department patients admitted with suspected sepsis – An observational cohort study

Background

Patients admitted to hospital with sepsis are at persistent risk of poor outcome after discharge. Many tools are available to risk-stratify sepsis patients for in-hospital mortality. This study aimed to identify the best risk-stratification tool to prognosticate outcome 180 days after admission via the emergency department (ED) with suspected sepsis.

Methods

A retrospective observational cohort study was performed of adult ED patients who were admitted after receiving intravenous antibiotics for the treatment of a suspected sepsis, between 1st March and 31st August 2019. The Risk-stratification of ED suspected Sepsis (REDS) score, SOFA score, Red-flag sepsis criteria met, NICE high-risk criteria met, the NEWS2 score and the SIRS criteria, were calculated for each patient. Death and survival at 180 days were noted. Patients were stratified in to high and low-risk groups as per accepted criteria for each risk-stratification tool. Kaplan–Meier curves were plotted for each tool and the log-rank test performed. The tools were compared using Cox-proportional hazard regression (CPHR). The tools were studied further in those without the following specified co-morbidities: Dementia, malignancy, Rockwood Frailty score of 6 or more, long-term oxygen therapy and previous do-not-resuscitate orders.

Results

Of the 1,057 patients studied 146 (13.8%) died at hospital discharge and 284 were known to have died within 180 days. Overall survival proportion was 74.4% at 180 days and 8.6% of the population was censored before 180 days. Only the REDS and SOFA scores identified less than 50% of the population as high-risk. All tools except the SIRS criteria, prognosticated for outcome at 180 days; Log-rank tests between high and low-risk groups were: REDS score p &lt; 0.0001, SOFA score p &lt; 0.0001, Red-flag criteria p = 0.001, NICE high-risk criteria p = 0.0001, NEWS2 score p = 0.003 and SIRS criteria p = 0.98. On CPHR, the REDS [Hazard ratio (HR) 2.54 (1.92–3.35)] and SOFA [HR 1.58 (1.24–2.03)] scores out-performed the other risk-stratification tools. In patients without the specified co-morbidities, only the REDS score and the SOFA score risk-stratified for outcome at 180 days.

Conclusion

In this study, all the risk-stratification tools studied were found to prognosticate for outcome at 180 days, except the SIRS criteria. The REDS and SOFA scores outperformed the other tools.

Early Diagnosis and Prevention of Infections in Cirrhosis

Strategies to prevent infection and improve outcomes in patients with cirrhosis. HAV, hepatitis A virus; HBV, hepatitis B virus; COVID-19, novel coronavirus disease 2019; NSBB, nonselective β-blocker; PPI, proton pump inhibitors.Cirrhosis is a risk factor for infections. Majority of hospital admissions in patients with cirrhosis are due to infections. Sepsis is an immunological response to an infectious process that leads to end-organ dysfunction and death. Preventing infections may avoid the downstream complications, and early diagnosis of infections may improve the outcomes. In this review, we discuss the pathogenesis, diagnosis, and biomarkers of infection; the incremental preventive strategies for infections and sepsi; and the consequent organ failures in cirrhosis. Strategies for primary prevention include reducing gut translocation by selective intestinal decontamination, avoiding unnecessary proton pump inhibitors' use, appropriate use of β-blockers, and vaccinations for viral diseases including novel coronavirus disease 2019. Secondary prevention includes early diagnosis and a timely and judicious use of antibiotics to prevent organ dysfunction. Organ failure support constitutes tertiary intervention in cirrhosis. In conclusion, infections in cirrhosis are potentially preventable with appropriate care strategies to then enable improved outcomes.