The Age-AST-D Dimer (AAD) Regression Model Predicts Severe COVID-19 Disease

Aim. Coronavirus disease (COVID-19) ranges from mild clinical phenotypes to life-threatening conditions like severe acute respiratory syndrome (SARS). It has been suggested that early liver injury in these patients could be a risk factor for poor outcome. We aimed to identify early biochemical predictive factors related to severe disease development with intensive care requirements in patients with COVID-19. Methods. Data from COVID-19 patients were collected at admission time to our hospital. Differential biochemical factors were identified between seriously ill patients requiring intensive care unit (ICU) admission (ICU patients) versus stable patients without the need for ICU admission (non-ICU patients). Multiple linear regression was applied, then a predictive model of severity called Age-AST-D dimer (AAD) was constructed (n=166) and validated (n=170). Results. Derivation cohort: from 166 patients included, there were 27 (16.3%) ICU patients that showed higher levels of liver injury markers (P<0.01) compared with non-ICU patients: alanine aminotrasnferase (ALT) 225.4±341.2 vs. 41.3±41.1, aspartate aminotransferase (AST) 325.3±382.4 vs. 52.8±47.1, lactic dehydrogenase (LDH) 764.6±401.9 vs. 461.0±185.6, D-dimer (DD) 7765±9109 vs. 1871±4146, and age 58.6±12.7 vs. 49.1±12.8. With these finding, a model called Age-AST-DD (AAD), with a cut-point of <2.75 (sensitivity=0.797 and specificity=0.391, c−statistic=0.74; 95%IC: 0.62-0.86, P<0.001), to predict the risk of need admission to ICU (OR=5.8; 95% CI: 2.2-15.4, P=0.001), was constructed. Validation cohort: in 170 different patients, the AAD model<2.75 (c−statistic=0.80 (95% CI: 0.70-0.91, P<0.001) adequately predicted the risk (OR=8.8, 95% CI: 3.4-22.6, P<0.001) to be admitted in the ICU (27 patients, 15.95%). Conclusions. The elevation of AST (a possible marker of early liver injury) along with DD and age efficiently predict early (at admission time) probability of ICU admission during the clinical course of COVID-19. The AAD model can improve the comprehensive management of COVID-19 patients, and it could be useful as a triage tool to early classify patients with a high risk of developing a severe clinical course of the disease

Diagnosis and treatment in chronic pancreatitis: an international survey and case vignette study

Background The aim of the study was to evaluate the current opinion and clinical decision-making process of international pancreatologists, and to systematically identify key study questions regarding the diagnosis and treatment of chronic pancreatitis (CP) for future research. Methods An online survey, including questions regarding the diagnosis and treatment of CP and several controversial clinical case vignettes, was send by e-mail to members of various international pancreatic associations: IHPBA, APA, EPC, ESGE and DPSG. Results A total of 288 pancreatologists, 56% surgeons and 44% gastroenterologists, from at least 47 countries, participated in the survey. About half (48%) of the specialists used a classification tool for the diagnosis of CP, including the Mayo Clinic (28%), Mannheim (25%), or Büchler (25%) tools. Overall, CT was the preferred imaging modality for evaluation of an enlarged pancreatic head (59%), pseudocyst (55%), calcifications (75%), and peripancreatic fat infiltration (68%). MRI was preferred for assessment of main pancreatic duct (MPD) abnormalities (60%). Total pancreatectomy with auto-islet transplantation was the preferred treatment in patients with parenchymal calcifications without MPD abnormalities and in patients with refractory pain despite maximal medical, endoscopic, and surgical treatment. In patients with an enlarged pancreatic head, 58% preferred initial surgery (PPPD) versus 42% initial endoscopy. In patients with a dilated MPD and intraductal stones 56% preferred initial endoscopic ± ESWL treatment and 29% preferred initial surgical treatment. Conclusion Worldwide, clinical decision-making in CP is largely based on local expertise, beliefs and disbeliefs. Further development of evidence-based guidelines based on well designed (randomized) studies is strongly encouraged