Acute pancreatitis associated with severe hypertriglyceridaemia; A retrospective cohort study.

AIM: Acute Pancreatitis (AP) secondary to hypertriglyceridaemia (HTG) is a rare association of which little is known in the literature. This study investigates patient characteristics and outcomes (reoccurrence and mortality) in those presenting with AP secondary to HTG in one of the largest reported British cohorts. METHODS: A retrospective observational case note review of all patients treated at our institution between 2004 and 2012. Data are expressed as mean and standard deviation if parametric and as median and range if non-parametric. Full fasting lipid profiles and patient demographics were recorded to elucidate further the cause of the severe hypertriglyceridaemia (>10 mmol/L fasting). RESULTS: There were 784 patients admitted with AP admitted to our institution within the study period. APHTG was present in 18 patients (2.3%). Peak serum triglyceride concentration was 43.9 mmol/L, SD 18.9 mmol/L. Serum amylase activity was 'falsely' low (with raised urine amylase) in about 10% of the patients with acute pancreatitis and hypertriglyceridaemia. 67% of our patients had type 2 diabetes mellitus or impaired glucose tolerance, 28% had a fatty liver and 50% displayed alcohol excess all these conditions are known to be associated with HTG There was a 94.5% reduction in serum triglyceride between presentation and last follow-up visit. There were also no deaths or recurrent episodes of AP during the study period. CONCLUSIONS: APHTG was present in 2.3% of patients presenting with AP. The reoccurrence and mortality rates were zero in this cohort. This may in part be due to aggressive serum triglyceride lowering by a multi-disciplinary team. Early clinical recognition is vital to provide targeted treatment and to try and reduce further episodes of AP.

Early cholecystectomy after acute admission with cholecystitis: how much work?

BACKGROUND: This study was designed to determine the number of cases and amount of operating room time required, for a population of 600,000, to provide definitive treatment in the form of cholecystectomy for all patients admitted as an emergency with cholecystitis. METHODS: The total number of patients admitted to a single NHS trust in South East Wales with the diagnosis of cholecystitis during a 1-year period was assessed. The number of laparoscopic cholecystectomies performed and the time taken was investigated with the conversion rates. RESULTS: There were a total of 787 individual emergency admissions attributed to cholecystitis, and 224 patients (36%) underwent cholecystectomy on the same admission. The median operative time was 77 (range, 23-238) min, and the median operating room time was 108 (range, 37-278) min. To treat all patients definitively would necessitate 12 cholecystectomies per week, requiring 1,296 min or 5.4 sessions of operating room time. CONCLUSIONS: A population of 600,000 could be expected to generate enough emergency cholecystectomies to require more than one operating session per day. A significant increase in emergency operating room availability would be necessary to allow the provision of definitive treatment for all emergency admissions with cholelithiasis.

Mortality control charts for comparing performance of surgical units: validation study using hospital mortality data.

OBJECTIVE: To design and validate a statistical method for evaluating the performance of surgical units that adjusts for case volume and case mix. DESIGN: Validation study using routinely collected data on in-hospital mortality. DATA SOURCES: Two UK databases, the ASCOT prospective database and the risk scoring collaborative (RISC) database, covering 1042 patients undergoing surgery in 29 hospitals for gastro-oesophageal cancer between 1995 and 2000. STATISTICAL ANALYSIS: A two level hierarchical logistic regression model was used to adjust each unit's operative mortality for case mix. Crude or adjusted operative mortality was plotted on mortality control charts (a graphical representation of surgical performance) as a function of number of operations. Control limits defined as 90%, 95%, and 99% confidence intervals identified units whose performance diverged significantly from the mean. RESULTS: The mean in-hospital mortality was 12% (range 0% to 50%). The case volume of the units ranged from one to 55 cases a year. When crude figures were plotted on the mortality control chart, four units lay outside the 90% control limit, including two outside the 95% limit. When operative mortality was adjusted for risk, three units lay outside the 90% limit and one outside the 95% limit. The model fitted the data well and had adequate discrimination (area under the receiver operating characteristics curve 0.78). CONCLUSIONS: The mortality control chart is an accurate, risk adjusted means of identifying units whose surgical performance, in terms of operative mortality, diverges significantly from the population mean. It gives an early warning of divergent performance. It could be adapted to monitor performance across various specialties.