Prospective derivation and validation of early dynamic model for predicting outcome in patients with acute liver failure R1 김형오 / Prof. 심재준

Introduction Acute liver failure Rapid development of hepatocellular dysfunction Coagulopathy Mental status changes (encephalopathy) High mortality without liver transplantation The prognostic models to select liver transplantation candidate To select appropriate candidate for liver transplantation Liver transplantation is an expensive treatment Requires lifelong immunosuppression To prevent avoidable liver transplantation

Introduction Prognostic models King’s College Hospital Criteria Model for End stage Liver Disease (MELD) Clichy criteria Serum group-specific component protein levels Liver volume on CT scanning Blood lactate levels Hyperphosphatemia Acute physiology and chronic health evaluation II score Unfortunately, none of these models has consistently demonstrated a reliable accuracy in predicting outcome In general, these prognostic markers have high specificity but unacceptably low sensitivity

Aim To develop a prognostic model based on early changes in levels of variables which predicted outcome independently at admission in a cohort of patients with acute liver failure Unfortunately, none of these models has consistently demonstrated a reliable accuracy in predicting outcome In general, these prognostic markers have high specificity but unacceptably low sensitivity

Patients And Methods January 2004~ June 2011, prospective evaluation 405 consecutive patients with acute liver failure All institute of Medical Sciences Patients died on or before day 2 after admission excluded (n=25) 380 patients 244 patients of derivation cohort 136 patients of validation cohort The study was approved by the ethics committee of our institute and consent was obtained from the nearest relative of the patient at the time of enrolment.

Definitions of variables Acute liver failure The occurrence of encephalopathy within 4 weeks of symptoms of absence of pre-existing liver disease Cerebral edema Presence of spontaneous or inducible decerebrate posturing Or any two of the followings Hypertension BP >150/90mmHg Bradycardia <60/min Pupillary change Neurogenic hyperventilation Hepatic encephalopathy grading Grade 1 : Loss of sleep rhythm, drowsiness, confusion, flapping tremor Grade 2 : Grade 1 + loss of sphincter control Grade 3 : Unconsciousness with no response to oral commands Grade 4 : Deep unconscious state with no response to pain The study was approved by the ethics committee of our institute and consent was obtained from the nearest relative of the patient at the time of enrolment.

Management protocol Managed in the intensive care unit Stress ulcer prophylaxis Monitoring and correction of blood sugar levels Mean arterial pressure >60 mmHg maintenance Elective ventilation for patients Grade 4 encephalopathy Grade 3 encephalopathy with cerebral edema Intravenous mannitol was used to control cerebral edema Daily microbiological surveillance to detect infection Prophylactic antibiotics given in all cases The study was approved by the ethics committee of our institute and consent was obtained from the nearest relative of the patient at the time of enrolment. Ammonia : No lactulose, probiotics, prebiotics, non-absorbable antibiotics

Patient characteristic Derivation cohort값이 의미있게 감소…

Prognostic model development 4-variable model AUROC 0.67 Hosmer-Lemeshow test discriminative ability modest ALFED model : early changes of significant variable AUROC 0.91 (0.92 in validative cohort) Hosmer-Lemeshow test Excellent discrimination, good calibration Hosmer Lemeshow goodness of fit test 4-variable model : modest ROC : false positive change, true positive rate로 model의 변별력을 측정 AUROC : model의 설명력을 평가

Risk stratification by ALFED score 88.5% of patients in the high risk category died (77/87) 2.6% of patients in the low risk category died (2/78) Hosmer Lemeshow goodness of fit test 4-variable model : modest ROC : false positive change, true positive rate로 model의 변별력을 측정 AUROC : model의 설명력을 평가

Comparison with other predictive models ALFED AUROC derivation cohort 0.91, validation cohort 0.92 MELD Score = (0.957 * ln(Serum Cr) + 0.378 * ln(Serum Bilirubin) + 1.120 * ln(INR) + 0.643 ) * 10 AAP Arterial pH < 7.3 (taken by sampling of blood from an artery) All three of an international normalized ratio (INR) of greater than 6.5,  serum creatinine of greater than 300 micromoles per litre and the presence of encephalopathy (of grade III or IV). These three are markers ofcoagulopathy, kidney function and mental status.[2] Non AAP INR greater than 6.5; or, Three of the following five criteria: Patient age of less than 11 or greater than 40; Serum bilirubin of greater than 300 micromoles per litre; Time from onset of jaundice to the development of coma of greater than seven days; INR greater than 3.5; or, Drug toxicity, regardless of whether it was the cause of the acute liver failure. MELD at 3 days Best cut-off score 35 AUROC 0.72 in the derivation, 0.76 in the validation cohort KCH criteria at 3 days AUROC 0.70 in the derivation, 0.62 in the validation cohort

Discordance between predictive models KCH(-), 140 patients ALFED high risk : 31 patients(22%) 25 patients died MELD < 35, 130 patients ALFED high risk : 26 patients(20%) 21 patients died ALFED low-risk, 78 patients KCH(+), 18 patients (17 survived) MELD >35, 20 patients (18 survived) In derivative cohort

In summary ALFED Prospectively derived, validated Simple, reliable, accurate This model might be very useful in risk stratification and clinical decision making