OBJECTIVE: To develop and validate a nomogram model for predicting 30-day mortality among elderly patients with sepsis-associated liver dysfunction (SALD), to identify high-risk patients and improve prognosis. METHODS: A retrospective cohort study was conducted using data extracted from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database for elderly patients with SALD who were first admitted to the intensive care unit (ICU) of Beth Israel Deaconess Medical Center between 2008 and 2019, including basic characteristics, severity scores, underlying diseases, infection foci, 24-hour vital signs, initial laboratory indicators, 24-hour complications, and prognosis related indicators. Patients were randomly assigned to training group and validation group in a ratio of 7 : 3. The training group used the LASSO regression analysis, as well as multivariate Logistic regression analysis to screen for independent risk factors for 30-day mortality. A nomogram prediction model was constructed, and receiver operator characteristic curve (ROC curve), calibration curves, and decision curve analysis (DCA) were used to evaluate the model, and validate the model using the validation cohort. RESULTS: A total of 630 elderly patients with SLAD were included in the study, including 441 in the training group and 189 in the validation group. Oxford acute severity of illness score (OASIS) for training group [odds ratio (OR) = 1.060, 95% confidence interval (95%CI) was 1.034-1.086], 24-hour pulse oxygen saturation (SpO₂; OR = 0.876, 95%CI was 0.797-0.962), initial mean corpuscular volume (MCV; OR = 1.043, 95%CI was 1.009-1.077), initial red blood cell distribution width (RDW; OR = 1.237, 95%CI was 1.123-1.362), initial blood glucose (OR = 1.008, 95%CI was 1.004-1.013), and initial aspartate aminotransferase (AST; OR = 1.000, 95%CI was 1.000-1.001) were independent risk factors for 30-day mortality in patients (all P < 0.05). Based on the above variables, a nomogram model was constructed, and the ROC curve showed that the area under the curve (AUC) of the model in the training group was 0.757 (95%CI was 0.712-0.803), with a sensitivity of 65.05% and a specificity of 74.90%; the AUC of the model in the validation group was 0.712 (95%CI was 0.631-0.792), with a sensitivity of 58.67% and a specificity of 81.58%. The calibration curves of the training and validation groups show that both the fitted curves were close to the standard curves. The Hosmer-Lemeshow test: the training group (χ ² = 6.729, P = 0.566), the validation group (χ ² = 13.889, P = 0.085), indicating that the model can fit the observed data well. The DCA curve shows that when the threshold probability of the training group was 16% to 94% and the threshold probability of the validation group was 27% to 99%, the net benefit of the model was good. CONCLUSIONS OASIS, 24-hour SpO₂, initial MCV, initial RDW, initial blood glucose and initial AST are independent risk factors for 30-day mortality in elderly patients with SALD. The nomogram based on these six variables demonstrates good predictive performance.
Humans ; Sepsis/complications* ; Retrospective Studies ; Nomograms ; Aged ; Prognosis ; Risk Factors ; Liver Diseases/mortality* ; Intensive Care Units ; ROC Curve ; Male ; Female ; Logistic Models

Liver disease-associated thrombocytopenia syndrome refers to thrombocytopenia caused by liver disease or the treatment of liver disease, and its incidence rate is related to the duration and severity of liver disease. The direct effect of thrombocytopenia on clinical outcomes is an increased risk of bleeding in patients with liver disease, whereas the indirect effect involves delay or termination of treatment due to the potential risk of bleeding. Liver disease-associated thrombocytopenia pathophysiological mechanisms involve decreased platelet production, abnormal distribution, destruction, or increased consumption. Presently, treatment strategies targeting different mechanisms include platelet-stimulating drugs, surgery, immunosuppressive drugs, and platelet transfusion, but the clinical application needs to be standardized further. The National Clinical Research Center for Infectious Diseases organized experts to discuss and formulate consensus with reference to the latest evidence-based medical evidence in the field so as to improve the clinical management level of liver disease-associated thrombocytopenia syndrome in China in terms of diagnosis, typing, and reasonable selection of treatment schemes.
Humans ; Consensus ; Thrombocytopenia/complications* ; Liver Diseases/complications* ; Hemorrhage/etiology* ; Blood Platelets

Humans ; Child ; COVID-19/complications* ; Brain Diseases ; Myositis/complications* ; Kidney ; Liver Failure, Acute/complications* ; Acute Kidney Injury/complications*

Sarcopenia has attracted increasing attention with the study of nutrition in patients with liver disease. Sarcopenia is an independent risk factor for a poor prognosis of liver disease and is becoming increasingly common in patients with liver disease. Studies have shown that patients with liver disease and sarcopenic obesity have a worse prognosis than patients with liver disease and simple sarcopenia or obesity. In clinical practice, it is easy to recognize patients with malnutrition and decreased muscle mass, but we often ignore those patients with normal body weight or even obesity who will likewise experience muscle mass loss. Simply relying on the monitoring of body mass and body mass index to assess the nutritional and muscle status of patients with liver disease is not accurate. At present, our understanding of the relationship between chronic liver disease and sarcopenic obesity is still poorly understood. In this paper, the research progress on chronic liver disease, sarcopenia, and sarcopenic obesity in recent years is reviewed so as to provide a theoretical basis for improving the clinical prognosis of patients with liver disease.
Humans ; Sarcopenia/complications* ; Body Composition/physiology* ; Obesity/complications* ; Risk Factors ; Liver Diseases/complications* ; Muscle, Skeletal

Humans ; Non-alcoholic Fatty Liver Disease/complications* ; Cardiovascular Diseases/complications* ; Risk Factors ; Liver

What are the new contents of the guideline since 2010?A.Patients with primary and non-primary sclerosing cholangitis (PSC) are included in these guidelines for the diagnosis and management of cholangiocarcinoma.B.Define "related stricture" as any biliary or hepatic duct stricture accompanied by the signs or symptoms of obstructive cholestasis and/or bacterial cholangitis.C.Patients who have had an inconclusive report from MRI and cholangiopancreatography should be reexamined by high-quality MRI/cholangiopancreatography for diagnostic purposes. Endoscopic retrograde cholangiopancreatography should be avoided for the diagnosis of PSC.D. Patients with PSC and unknown inflammatory bowel disease (IBD) should undergo diagnostic colonoscopic histological sampling, with follow-up examination every five years until IBD is detected.E. PSC patients with IBD should begin colon cancer monitoring at 15 years of age.F. Individual incidence rates should be interpreted with caution when using the new clinical risk tool for PSC for risk stratification.G. All patients with PSC should be considered for clinical trials; however, if ursodeoxycholic acid (13-23 mg/kg/day) is well tolerated and after 12 months of treatment, alkaline phosphatase (γ- Glutamyltransferase in children) and/or symptoms are significantly improved, it can be considered to continue to be used.H. Endoscopic retrograde cholangiopancreatography with cholangiocytology brushing and fluorescence in situ hybridization analysis should be performed on all patients suspected of having hilar or distal cholangiocarcinoma.I.Patients with PSC and recurrent cholangitis are now included in the new unified network organ sharing policy for the end-stage liver disease model standard.J. Liver transplantation is recommended after neoadjuvant therapy for patients with unresectable hilar cholangiocarcinoma with diameter < 3 cm or combined with PSC and no intrahepatic (extrahepatic) metastases.
Child ; Humans ; Cholangitis, Sclerosing/diagnosis* ; Constriction, Pathologic/complications* ; In Situ Hybridization, Fluorescence ; Cholangiocarcinoma/therapy* ; Liver Diseases/complications* ; Cholestasis ; Inflammatory Bowel Diseases/therapy* ; Bile Ducts, Intrahepatic/pathology* ; Bile Duct Neoplasms/therapy*

Fontan-associated liver disease (FALD) is one of the main complications after the Fontan procedure, manifesting mostly as liver fibrosis and even cirrhosis, with a high incidence rate and a lack of typical clinical symptoms that seriously affect patient prognosis. The specific cause is unknown, although it is considered to be associated with long-term elevated central venous pressure, impaired hepatic artery blood flow, and other relevant factors. The absence of association between laboratory tests, imaging data, and the severity of liver fibrosis makes clinical diagnosis and monitoring difficult. A liver biopsy is the gold standard for diagnosing and staging liver fibrosis. The most important risk factor for FALD is time following the Fontan procedure; therefore, it is recommended to do a liver biopsy 10 years after the Fontan procedure and to be cautious for the presence of hepatocellular carcinoma. Combined heart-liver transplantation is a recommended choice with favorable outcomes for patients with Fontan circulatory failure and severe hepatic fibrosis.
Humans ; Liver Diseases/pathology* ; Liver Cirrhosis/pathology* ; Liver/pathology* ; Carcinoma, Hepatocellular/pathology* ; Liver Transplantation/adverse effects* ; Fontan Procedure/adverse effects* ; Postoperative Complications/pathology* ; Liver Neoplasms/pathology*

Biliary Tract Diseases ; Humans ; Liver Diseases ; Liver Transplantation/adverse effects* ; Postoperative Complications/etiology* ; Retrospective Studies

OBJECTIVE: To find the pathogenies and risk factors related to surgical intensive care unit (SICU) readmission for patients who underwent hepatobiliary-pancreatic surgery, and to develop a predictive model for determining patients who are likely to be readmitted to SICU. METHODS: The patients who admitted to SICU of the Affiliated Hospital of Qingdao University from January 2013 to August 2018; who first stayed in SICU after hepatobiliary-pancreatic surgery; who were assessed and discharged from SICU by surgeons and SICU physicians after treatment, and then transferred to SICU again because of the change of their condition were enrolled. The unintended return to SICU within 3 days and 7 days were recorded. Patients who returned to SICU within 7 days were studied for the pathogenies, risk factors and predictive model of returning to SICU, and non-returning patients were enrolled according to 1:1 as the controls. A total of 43 indicators were divided into five categories, including general clinical data, medical history, surgical indicators before first admission of SICU, length of first SICU stay, and other indicators on the day of first discharge from the SICU. Logistic regression was used to screen the risk factors associated with SICU readmission, then the Nomogram diagram was drawn by using the R 3.4.1 software for predicting SICU readmission, and the classification performance of Nomogram was evaluated by self-help sampling test. RESULTS: Of the 763 patients discharged from the SICU, 2.10% (16/763) of them were readmitted within 3 days and 3.28% (25/763) were readmitted within 7 days to the SICU unexpectedly. The pathogenies of SICU readmission within 7 days included infection [56.00% (14/25)], heart failure [16.00% (4/25)], infarction [12.00% (3/25)], bleeding [12.00% (3/25)], and sutures splitting [4.00% (1/25)]. The pathogenies of SICU readmission within 3 days included infection [56.25% (9/16)], heart failure [18.75% (3/16)], infarction [12.50% (2/16)], and bleeding [12.50% (2/16)]. Nomogram analysis showed that the risk factors associated with unplanned SICU readmission were length of first SICU stay, history of hypertension, and activity of daily living (ADL) score, white blood cell count (WBC), arterial partial pressure of oxygen (PaO₂), prothrombin time (PT), fibrinogen (FIB) on the day of first SICU discharge. Self-help sampling test was carried out on the Nomogram map, and the results showed that the coherence index (C-index) was 0.962 [95% confidence interval (95%CI) = 0.869-1.057]. The classification performance of the model was good. CONCLUSIONS The common pathogenies of SICU readmission for patients who underwent hepatobiliary-pancreatic surgery were infection, heart failure, infarction and bleeding. Risk factors of readmission after SICU discharge included the length of first SICU stay, history of hypertension, and ADL score, WBC, PaO₂, PT, FIB on the day of first SICU discharge. The model consisted of above risk factors showed a good performance in predicting the probability of readmission after SICU discharge for patients who underwent hepatobiliary-pancreatic surgery.
Biliary Tract Diseases/surgery* ; Digestive System Surgical Procedures/adverse effects* ; Humans ; Intensive Care Units ; Liver Diseases/surgery* ; Models, Statistical ; Pancreatic Diseases/surgery* ; Patient Readmission/statistics & numerical data* ; Postoperative Complications/therapy* ; Risk Factors

PURPOSE: With increasing life expectancy, the presence of comorbidities has become a major concern in elderly patients who require surgery. However, little is known about the impact of different comorbidities on the outcomes of laparoscopic total gastrectomy (LTG). In this study, we investigated the impact of comorbidities on postoperative complications in patients undergoing LTG for gastric carcinoma. MATERIALS AND METHODS: We retrospectively reviewed the cases of 303 consecutive patients who underwent LTG for gastric carcinoma between 2005 and 2016. The associations between each comorbidity and postoperative complications were assessed using univariate and multivariate analyses. RESULTS: A total of 189 patients (62.4%) had one or more comorbidities. Hypertension was the most common comorbidity (37.0%), followed by diabetes mellitus (17.8%), chronic viral hepatitis (2.6%), liver cirrhosis (2.6%), and pulmonary (27.1%), ischemic heart (3.3%), and cerebrovascular diseases (2.3%). The overall postoperative morbidity and mortality rates were 20.1% and 1.0%, respectively. Patients with pulmonary disease significantly showed higher complication rates than those without comorbidities (32.9% vs. 14.9%, respectively, P=0.003); patient with other comorbidities showed no significant difference in the incidence of LTG-related complications. During univariate and multivariate analyses, pulmonary disease was found to be an independent predictive factor for postoperative complications (odds ratio, 2.14; 95% confidence interval, 1.03–4.64), along with old age and intraoperative bleeding. CONCLUSIONS: Among the various comorbidities investigated, patients with pulmonary disease had a significantly higher risk of postoperative complications after LTG. Proper perioperative care for optimizing pulmonary function may be required for patients with pulmonary disease.
Aged ; Cerebrovascular Disorders ; Comorbidity* ; Diabetes Mellitus ; Gastrectomy* ; Heart ; Hemorrhage ; Hepatitis ; Humans ; Hypertension ; Incidence ; Laparoscopy ; Life Expectancy ; Liver Cirrhosis ; Lung Diseases ; Mortality ; Multivariate Analysis ; Perioperative Care ; Postoperative Complications ; Retrospective Studies ; Stomach Neoplasms