Background and objective The Atlanta classification of acute pancreatitis enabled standardised reporting of research and aided communication between clinicians. Deficiencies identified and improved understanding of the disease make a revision necessary. Methods A web-based consultation was undertaken in 2007 to ensure wide participation of pancreatologists. After an initial meeting, the Working Group sent a draft document to 11 national and international pancreatic associations. This working draft was forwarded to all members. Revisions were made in response to comments, and the web-based consultation was repeated three times. The final consensus was reviewed, and only statements based on published evidence were retained. Results The revised classification of acute pancreatitis identified two phases of the disease: early and late. Severity is classified as mild, moderate or severe. Mild acute pancreatitis, the most common form, has no organ failure, local or systemic complications and usually resolves in the first week. Moderately severe acute pancreatitis is defined by the presence of transient organ failure, local complications or exacerbation of co-morbid disease. Severe acute pancreatitis is defined by persistent organ failure, that is, organ failure >48 h. Local complications are peripancreatic fluid collections, pancreatic and peripancreatic necrosis (sterile or infected), pseudocyst and walled-off necrosis (sterile or infected). We present a standardised template for reporting CT images. Conclusions This international, web-based consensus provides clear definitions to classify acute pancreatitis using easily identified clinical and radiologic criteria. The wide consultation among pancreatologists to reach this consensus should encourage widespread adoption.

/pdf/classification-of-acute-pancreatitis-2012-revision-of-the-608d2rjeud.pdf

Classification of acute pancreatitis—2012: revision of the Atlanta classification and definitions by international consensus

Background The magnitude and scope of Clostridium difficile infection in the United States continue to evolve. Methods In 2011, we performed active population- and laboratory-based surveillance across 10 geographic areas in the United States to identify cases of C. difficile infection (stool specimens positive for C. difficile on either toxin or molecular assay in residents ≥1 year of age). Cases were classified as community-associated or health care–associated. In a sample of cases of C. difficile infection, specimens were cultured and isolates underwent molecular typing. We used regression models to calculate estimates of national incidence and total number of infections, first recurrences, and deaths within 30 days after the diagnosis of C. difficile infection. Results A total of 15,461 cases of C. difficile infection were identified in the 10 geographic areas; 65.8% were health care–associated, but only 24.2% had onset during hospitalization. After adjustment for predictors of disease incidence, the estimated number of incident C. difficile infections in the United States was 453,000 (95% confidence interval [CI], 397,100 to 508,500). The incidence was estimated to be higher among females (rate ratio, 1.26; 95% CI, 1.25 to 1.27), whites (rate ratio, 1.72; 95% CI, 1.56 to 2.0), and persons 65 years of age or older (rate ratio, 8.65; 95% CI, 8.16 to 9.31). The estimated number of first recurrences of C. difficile infection was 83,000 (95% CI, 57,000 to 108,900), and the estimated number of deaths was 29,300 (95% CI, 16,500 to 42,100). The North American pulsed-field gel electrophoresis type 1 (NAP1) strain was more prevalent among health care–associated infections than among community-associated infections (30.7% vs. 18.8%, P<0.001) Conclusions C. difficile was responsible for almost half a million infections and was associated with approximately 29,000 deaths in 2011. (Funded by the Centers for Disease Control and Prevention.)

/pdf/burden-of-clostridium-difficile-infection-in-the-united-rzdw95jlaf.pdf

Burden of Clostridium difficile Infection in the United States

A panel of experts was convened by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA) to update the 2010 clinical practice guideline on Clostridium difficile infection (CDI) in adults. The update, which has incorporated recommendations for children (following the adult recommendations for epidemiology, diagnosis, and treatment), includes significant changes in the management of this infection and reflects the evolving controversy over best methods for diagnosis. Clostridium difficile remains the most important cause of healthcare-associated diarrhea and has become the most commonly identified cause of healthcare-associated infection in adults in the United States. Moreover, C. difficile has established itself as an important community pathogen. Although the prevalence of the epidemic and virulent ribotype 027 strain has declined markedly along with overall CDI rates in parts of Europe, it remains one of the most commonly identified strains in the United States where it causes a sizable minority of CDIs, especially healthcare-associated CDIs. This guideline updates recommendations regarding epidemiology, diagnosis, treatment, infection prevention, and environmental management.

/pdf/clinical-practice-guidelines-for-clostridium-difficile-4hs0j01jnf.pdf

Clinical Practice Guidelines for Clostridium difficile Infection in Adults and Children: 2017 Update by the Infectious Diseases Society of America (IDSA) and Society for Healthcare Epidemiology of America (SHEA)

https://www.spg.pt/wp-content/uploads/2015/11/2013-ACG_Guideline_AcutePancreatitis_September_2013.pdf

American College of Gastroenterology guideline: management of acute pancreatitis.

https://www.themedlab.com/wp-content/uploads/2014/01/ACG_Guideline_Cdifficile_April_2013.pdf

Guidelines for Diagnosis, Treatment, and Prevention of Clostridium difficile Infections

Background: Identification of patients at risk for mortality early in the course of acute pancreatitis (AP) is an important step in improving outcome. Methods: Using Classification and Regression Tree (CART) analysis, a clinical scoring system was developed for prediction of in-hospital mortality in AP. The scoring system was derived on data collected from 17 992 cases of AP from 212 hospitals in 2000–2001. The new scoring system was validated on data collected from 18 256 AP cases from 177 hospitals in 2004–2005. The accuracy of the scoring system for prediction of mortality was measured by the area under the receiver operating characteristic curve (AUC). The performance of the new scoring system was further validated by comparing its predictive accuracy with that of Acute Physiology and Chronic Health Examination (APACHE) II. Results: CART analysis identified five variables for prediction of in-hospital mortality. One point is assigned for the presence of each of the following during the first 24 h: blood urea nitrogen (BUN) >25 mg/dl; impaired mental status; systemic inflammatory response syndrome (SIRS); age >60 years; or the presence of a pleural effusion (BISAP). Mortality ranged from >20% in the highest risk group to Conclusions: A new mortality-based prognostic scoring system for use in AP has been derived and validated. The BISAP is a simple and accurate method for the early identification of patients at increased risk for in-hospital mortality.

https://gut.bmj.com/content/gutjnl/57/12/1698.full.pdf

The early prediction of mortality in acute pancreatitis: a large population-based study

https://www.giejournal.org/article/S0016-5107(11)01863-3/pdf

A simple risk score accurately predicts in-hospital mortality, length of stay, and cost in acute upper GI bleeding

https://www.gastrojournal.org/article/S0016-5085(09)00520-4/pdf

Early Changes in Blood Urea Nitrogen Predict Mortality in Acute Pancreatitis

Background: Identification of patients at risk for mortality early in the course of acute pancreatitis (AP) is an important step in improving outcome. Methods: Using Classification and Regression Tree (CART) analysis, a clinical scoring system was developed for prediction of in-hospital mortality in AP. The scoring system was derived on data collected from 17 992 cases of AP from 212 hospitals in 2000-2001. The new scoring system was validated on data collected from 18 256 AP cases from 177 hospitals in 2004-2005. The accuracy of the scoring system for prediction of mortality was measured by the area under the receiver operating characteristic curve (AUC). The performance of the new scoring system was further validated by comparing its predictive accuracy with that of Acute Physiology and Chronic Health Examination (APACHE) II. Results: CART analysis identified five variables for prediction of in-hospital mortality. One point is assigned for the presence of each of the following during the first 24 h: blood urea nitrogen (BUN) >25 mg/dl; impaired mental status; systemic inflammatory response syndrome (SIRS); age >60 years; or the presence of a pleural effusion (BISAP). Mortality ranged from >20% in the highest risk group to <1% in the lowest risk group. In the validation cohort, the BISAP AUC was 0.82 (95% Cl 0.79 to 0.84) versus APACHE II AUC of 0.83 (95% Cl 0.80 to 0.85). Conclusions: A new mortality-based prognostic scoring system for use in AP has been derived and validated. The BISAP is a simple and accurate method for the early identification of patients at increased risk for in-hospital mortality.

The early prediction of mortality in acute pancreatitis : a large population-based study. Commentary

https://dash.harvard.edu/bitstream/handle/1/12152985/3994855.pdf?sequence=1

Xiaowu Sun

Papers

The early prediction of mortality in acute pancreatitis: a large population-based study

A simple risk score accurately predicts in-hospital mortality, length of stay, and cost in acute upper GI bleeding

Early Changes in Blood Urea Nitrogen Predict Mortality in Acute Pancreatitis

The early prediction of mortality in acute pancreatitis : a large population-based study. Commentary

Using electronic health record data to develop inpatient mortality predictive model: Acute Laboratory Risk of Mortality Score (ALaRMS).