Pei-Chun Fan

Scoring systems for 6-month mortality in critically ill cirrhotic patients: a prospective analysis of chronic liver failure - sequential organ failure assessment score (CLIF-SOFA).

Cirrhotic patients admitted to intensive care units (ICUs) have high mortality rates. The Chronic Liver Failure–Sequential Organ Failure Assessment (CLIF‐SOFA) score, a modified Sequential Organ Failure Assessment (SOFA) score, is a newly developed scoring system exclusively for patients with end‐stage liver disease.

Risk Models and Scoring Systems for Predicting the Prognosis in Critically Ill Cirrhotic Patients with Acute Kidney Injury: A Prospective Validation Study

Background Cirrhotic patients with acute kidney injury (AKI) admitted to intensive care units (ICUs) show extremely high mortality rates. We have proposed the MBRS scoring system, which can be used for assessing patients on the day of admission to the ICU; this new system involves determination of mean arterial pressure (MAP) and bilirubin level and assessment of respiratory failure and sepsis. We had used this scoring system to analyze the prognosis of ICU cirrhotic patients with AKI in 2008, and the current study was an external validation of this scoring system. Methods A total of 190 cirrhotic patients with AKI were admitted to the ICU between March 2008 and February 2011. We prospectively analyzed and recorded the data for 31 demographic parameters and some clinical characteristic variables on day 1 of admission to the ICU; these variables were considered as predictors of mortality. Results The overall in-hospital mortality rate was 73.2% (139/190), and the 6-month mortality rate was 83.2% (158/190). Hepatitis B viral infection (43%) was observed to be the cause of liver disease in most of the patients. Multiple logistic regression analysis indicated that the MBRS and Acute Physiology and Chronic Health Evaluation III (ACPACHE III) scores determined on the first day of admission to the ICU were independent predictors of in-hospital mortality in patients. In the analysis of the area under the receiver operating characteristic (AUROC) curves, the MBRS scores showed good discrimination (AUROC: 0.863±0.032, p<0.001) in predicting in-hospital mortality. Conclusion On the basis of the results of this external validation, we conclude that the MBRS scoring system is a reproducible, simple, easy-to-apply evaluation tool that can increase the prediction accuracy of short-term prognosis in critically ill cirrhotic patients with AKI.

Combination of Urinary Biomarkers Improves Early Detection of Acute Kidney Injury in Patients With Heart Failure

BACKGROUND Acute kidney injury (AKI) is associated with morality and repeated hospitalization, and is frequently encountered in patients with acute decompensated heart failure (ADHF). However, few effective tools exist for early AKI identification and risk stratification. METHODSANDRESULTS This was a prospective observational study conducted in the coronary care unit (CCU) of a tertiary care university hospital. Patients with a diagnosis of ADHF and who were using diuretics were enrolled.Samples collected between December 2013 and February 2015 were tested for serum cystatin C (Cys-C), urinary neutrophil gelatinase-associated lipocalin, and kidney injury molecule-1 (KIM-1). Demographic, clinical, and laboratory data were evaluated. A total of 103 adult patients with a mean age of 68 years were investigated. AKI was diagnosed in 49 patients (47.6%). For predicting intrinsic AKI on the first day of CCU admission, a combination of Cys-C and urine KIM-1 yielded an excellent area under the receiver operating characteristic curve of 0.828, a sensitivity of 71.0%, and specificity of 43.0%, for an overall accuracy of 78%. CONCLUSIONS In this study, we found that combinations of the biomarker (Cys-C and KIM-1) were an effective clinical model for predicting AKI in patients with ADHF. The biomarker was also useful for differentiating subclinical AKI in patients with ADHF.

Acute Kidney Injury Classification for Critically Ill Cirrhotic Patients: A Comparison of the KDIGO, AKIN, and RIFLE Classifications.

Critically ill cirrhotic patients have high mortality rates, particularly when they present with acute kidney injury (AKI) on admission. The Kidney Disease: Improving Global Outcomes (KDIGO) group aimed to standardize the definition of AKI and recently published a new AKI classification. However, the efficacy of the KDIGO classification for predicting outcomes of critically ill cirrhotic patients is unclear. We prospectively enrolled 242 cirrhotic patients from a 10-bed specialized hepatogastroenterology intensive care unit (ICU) in a 2000-bed tertiary-care referral hospital. Demographic parameters and clinical variables on day 1 of admission were prospectively recorded. The overall in-hospital mortality rate was 62.8%. Liver diseases were usually attributed to hepatitis B viral infection (26.9%). The major cause of ICU admission was upper gastrointestinal bleeding (38.0%). Our result showed that the KDIGO classification had better discriminatory power than RIFLE and AKIN criteria in predicting in-hospital mortality. Cumulative survival rates at the 6-month after hospital discharge differed significantly between patients with and without AKI on ICU admission day. In summary, we identified that the outcome prediction performance of KDIGO classification is superior to that of AKIN or RIFLE classification in critically ill cirrhotic patients.

Acute Respiratory Distress Syndrome With and Without Extracorporeal Membrane Oxygenation: A Score Matched Study.

BACKGROUND Acute respiratory distress syndrome (ARDS) is a life-threatening medical condition. Extracorporeal membrane oxygenation (ECMO) is a salvage therapy for patients with ARDS and refractory hypoxia. This study compared the characteristics and outcomes of ARDS patients who did or did not receive ECMO matched with Acute Physiology and Chronic Health Evaluation II (APACHE II) score and age. METHODS This retrospective, case-control study enrolled patients with ARDS admitted to the intensive care unit of a tertiary referral hospital between January 2007 and December 2012. Overall, 216 patients with ARDS-81 receiving ECMO (ECMO group) and 135 not receiving ECMO (non-ECMO group)-were enrolled in this study. Patients were paired when the difference in their APACHE II scores was within 3 points and their age difference was 3 years. In total, 126 patients could not be matched and were thus excluded. Eventually, of the 90 patients with ARDS enrolled in this study, 45 ECMO group patients were matched with 45 non-ECMO group patients. The demographic data, reasons for intensive care unit admission, and laboratory variables were evaluated. RESULTS The primary etiology of ARDS was infection (72.2%). The APACHE II score and age-matched group receiving ECMO therapy had higher inhospital survival rates. Moreover, the patients receiving ECMO therapy had significantly lower 6-month mortality rates than did the non-ECMO group. CONCLUSIONS Patients with ARDS who received ECMO treatment had higher inhospital survival rates than did those with a similar disease severity and at a similar age who did not receive ECMO.

Scoring Systems for Predicting Mortality after Liver Transplantation

Background Liver transplantation can prolong survival in patients with end-stage liver disease. We have proposed that the Sequential Organ Failure Assessment (SOFA) score calculated on post-transplant day 7 has a great discriminative power for predicting 1-year mortality after liver transplantation. The Chronic Liver Failure - Sequential Organ Failure Assessment (CLIF-SOFA) score, a modified SOFA score, is a newly developed scoring system exclusively for patients with end-stage liver disease. This study was designed to compare the CLIF-SOFA score with other main scoring systems in outcome prediction for liver transplant patients. Methods We retrospectively reviewed medical records of 323 patients who had received liver transplants in a tertiary care university hospital from October 2002 to December 2010. Demographic parameters and clinical characteristic variables were recorded on the first day of admission before transplantation and on post-transplantation days 1, 3, 7, and 14. Results The overall 1-year survival rate was 78.3% (253/323). Liver diseases were mostly attributed to hepatitis B virus infection (34%). The CLIF-SOFA score had better discriminatory power than the Child-Pugh points, Model for End-Stage Liver Disease (MELD) score, RIFLE (risk of renal dysfunction, injury to the kidney, failure of the kidney, loss of kidney function, and end-stage kidney disease) criteria, and SOFA score. The AUROC curves were highest for CLIF-SOFA score on post-liver transplant day 7 for predicting 1-year mortality. The cumulative survival rates differed significantly for patients with a CLIF-SOFA score ≤8 and those with a CLIF-SOFA score >8 on post-liver transplant day 7. Conclusion The CLIF-SOFA score can increase the prediction accuracy of prognosis after transplantation. Moreover, the CLIF-SOFA score on post-transplantation day 7 had the best discriminative power for predicting 1-year mortality after liver transplantation.

Acute Kidney Injury Enhances Outcome Prediction Ability of Sequential Organ Failure Assessment Score in Critically Ill Patients

Introduction Acute kidney injury (AKI) is a common and serious complication in intensive care unit (ICU) patients and also often part of a multiple organ failure syndrome. The sequential organ failure assessment (SOFA) score is an excellent tool for assessing the extent of organ dysfunction in critically ill patients. This study aimed to evaluate the outcome prediction ability of SOFA and Acute Physiology and Chronic Health Evaluation (APACHE) III score in ICU patients with AKI. Methods A total of 543 critically ill patients were admitted to the medical ICU of a tertiary-care hospital from July 2007 to June 2008. Demographic, clinical and laboratory variables were prospectively recorded for post hoc analysis as predictors of survival on the first day of ICU admission. Results One hundred and eighty-seven (34.4%) patients presented with AKI on the first day of ICU admission based on the risk of renal failure, injury to kidney, failure of kidney function, loss of kidney function, and end-stage renal failure (RIFLE) classification. Major causes of the ICU admissions involved respiratory failure (58%). Overall in-ICU mortality was 37.9% and the hospital mortality was 44.7%. The predictive accuracy for ICU mortality of SOFA (areas under the receiver operating characteristic curves: 0.815±0.032) was as good as APACHE III in the AKI group. However, cumulative survival rates at 6-month follow-up following hospital discharge differed significantly (p<0.001) for SOFA score ≤10 vs. ≥11 in these ICU patients with AKI. Conclusions For patients coexisting with AKI admitted to ICU, this work recommends application of SOFA by physicians to assess ICU mortality because of its practicality and low cost. A SOFA score of ≥ “11” on ICU day 1 should be considered an indicator of negative short-term outcome.

Predicting Acute Kidney Injury Following Mitral Valve Repair

Background: Acute kidney injury (AKI) after cardiac surgery is associated with short-term and long-term adverse outcomes. Novel biomarkers have been identified for the early detection of AKI; however, examining these in every patient who undergoes cardiac surgery is prohibitively expensive. Society of Thoracic Surgeons (STS) and Age, Creatinine, and Ejection Fraction (ACEF) scores have been proven to predict mortality in bypass surgery. The aim of this study was to determine whether these scores can be used to predict AKI after mitral valve repair. Materials and Methods: Between January 2010 and December 2013, 196 patients who underwent mitral valve repair were enrolled. The clinical characteristics, outcomes, and scores of prognostic models were collected. The primary outcome was postoperative AKI, defined using the Kidney Disease Improving Global Outcome 2012 clinical practice guidelines for AKI. Results: A total of 76 patients (38.7%) developed postoperative AKI. The STS renal failure (AUROC: 0.797, P < .001) and ACEF scores (AUROC: 0.758, P < .001) are both satisfactory tools for predicting all AKI. The STS renal failure score exhibited superior accuracy compared with the ACEF score in predicting AKI stage 2 and 3. The overall accuracy of both scores was similar for all AKI and AKI stage 2 and 3 when the cut-off points of the STS renal failure and ACEF scores were 2.2 and 1.1, respectively. Conclusion: In conclusion, the STS renal failure score can be used to accurately predict stage 2 and 3 AKI after mitral valve repair. The ACEF score is a simple tool with satisfactory power in screening patients at risk of all AKI stages. Additional studies can aim to determine the clinical implications of combining preoperative risk stratification and novel biomarkers.

Predictive Value of Acute Kidney Injury in Medical Intensive Care Patients With Sepsis Originating From Different Infection Sites

Introduction: Sepsis is the most common noncoronary cause of mortality in intensive care units (ICUs). This study compared different systems for predicting outcomes in a population of critically ill patients with sepsis originating from different infection sites, including intra-abdominal and pulmonary infections. Methods: This post hoc analysis of an accumulated database enrolled 161 heterogeneous critically ill patients diagnosed as severe sepsis and septic shock patients admitted to medical ICUs from June 2005 to May 2007. Demographic characteristics, clinical and laboratory variables, comorbidities and infection source were prospectively recorded on the first day of ICU admission. Patient evaluations included acute physiology and chronic health evaluation (APACHE) II, APACHE III, sequential organ failure assessment scores, organ system failure and risk of renal failure, injury to kidney, failure of kidney function, loss of kidney function and end-stage renal failure (RIFLE) classification. Results: Regarding the different originating sites of severe sepsis, intra-abdominal infections and pulmonary infections had the highest mortality rates (83.3% and 48.5%, respectively; P < 0.001). The APACHE III was the best mortality predictor for the overall sepsis population [areas under the receiver operating characteristic curve (AUROC) 0.800], whereas RIFLE classification was the best predictor in those with intra-abdominal infection (AUROC 0.856). The AUROC analyses verified that RIFLE classification had significantly (P < 0.05) better discriminatory power for predicting hospital mortality in patients with intra-abdominal infections than in those with pulmonary infections (AUROC 0.545). Conclusions: This investigation confirms that different infection sites have different outcomes. In terms of mortality prediction, outcome scoring systems are significantly more accurate in patients with intra-abdominal infections than in those with pulmonary infections.

Comparison of contemporary preoperative risk models at predicting acute kidney injury after isolated coronary artery bypass grafting: a retrospective cohort study

Objectives Acute kidney injury (AKI) after coronary artery bypass grafting (CABG) is associated with short-term and long-term adverse outcomes. The European System for Cardiac Operative Risk Evaluation (EuroSCORE), EuroSCORE II, the Society of Thoracic Surgeons (STS) score and Age, Creatinine and Ejection Fraction (ACEF) score, have been widely used for predicting the operative risk of cardiac surgery. The aim of this study is to investigate the discriminant ability among current available models in predicting postoperative AKI. Methods From January 2010 to December 2012, 353 patients who underwent isolated CABG were enrolled. The clinical characteristics, outcomes and scores of prognostic models were collected. The primary outcome was postoperative AKI, defined based on the Kidney Disease Improving Global Outcome (KDIGO) Clinical Practice Guideline for AKI, in 2012. Results 102 patients (28.9%) developed postoperative AKI. For AKI prediction, EuroSCORE II, STS score and ACEF score were all good tools for stage-3 AKI. The ACEF score was shown to have satisfied discriminant ability to predict postoperative AKI with area under a receiver operating characteristic curve: 0.781±0.027, (95% CI 0.729 to 0.834, p value <0.001). Multivariate logistic analysis identified that lower ejection fraction and higher serum creatinine were independent risk factors for AKI. Conclusions The simple and extremely user-friendly ACEF score can accurately identify the risk of postoperative AKI and has shown satisfactory discriminant ability when compared with other systems. The ACEF score might be the easiest tool for predicting postoperative AKI.