Acute mesenteric ischemia in ICU patients was associated with a 58 % ICU death rate. Age and SOFA severity score at diagnosis were risk factors for mortality. Plasma lactate concentration over 2.7 mmol/l was also an independent risk factor, but values in the normal range did not exclude the diagnosis of AMI.

Purulent pericarditis (PP) is a potentially life-threatening disease. Reported mortality rates are between 20 and 30%. Constrictive pericarditis occurs over the course of PP in at least 3.5% of cases. The frequency of persistent PP (chronic or recurrent purulent pericardial effusion occurring despite drainage and adequate antibiotherapy) is unknown because this entity was not previously classified as a complication of PP. No consensus exists on the optimal management of PP. Nevertheless, the cornerstone of PP management is complete eradication of the focus of infection. In retrospective studies, compared to simple drainage, systematic pericardiectomy provided a prevention of constrictive pericarditis with better clinical outcome. Because of potential morbidity associated with pericardiectomy, intrapericardial fibrinolysis has been proposed as a less invasive method for prevention of persistent PP and constrictive pericarditis. Experimental data demonstrate that fibrin formation, which occurs during the first week of the disease, is an essential step in the evolution to constrictive pericarditis and persistent PP. We reviewed the literature using the MEDLINE database. We evaluated the clinical efficacy, outcome, and complications of pericardial fibrinolysis. Seventy-four cases of fibrinolysis in PP were analysed. Pericarditis of tuberculous origin were excluded. Among the 40 included cases, only two treated by late fibrinolysis encountered failure requiring pericardiectomy. No patient encountered clinical or echocardiographic features of constriction during follow-up. Only one serious complication was described. Despite the lack of definitive evidence, potential benefits of fibrinolysis as a less invasive alternative to surgery in the management of PP seem promising. Early consideration should be given to fibrinolysis in order to prevent both constrictive and persistent PP. Nevertheless, in case of failure of fibrinolysis, pericardiectomy remains the primary option for complete eradication of infection.

BackgroundThe benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate prediction models.Methods and findingWe conducted a retrospective cohort study using a prospective collected database from December 2005 to December 2012, from a cardiac surgical center at University Hospital. The different models of prediction of mortality in-hospital after elective cardiac surgery, including EuroSCORE II, a logistic regression model and a machine learning model, were compared by ROC and DCA. Of the 6,520 patients having elective cardiac surgery with cardiopulmonary bypass, 6.3% died. Mean age was 63.4 years old (standard deviation 14.4), and mean EuroSCORE II was 3.7 (4.8) %. The area under ROC curve (IC95%) for the machine learning model (0.795 (0.755–0.834)) was significantly higher than EuroSCORE II or the logistic regression model (respectively, 0.737 (0.691–0.783) and 0.742 (0.698–0.785), p < 0.0001). Decision Curve Analysis showed that the machine learning model, in this monocentric study, has a greater benefit whatever the probability threshold.ConclusionsAccording to ROC and DCA, machine learning model is more accurate in predicting mortality after elective cardiac surgery than EuroSCORE II. These results confirm the use of machine learning methods in the field of medical prediction.