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Controlling infection is crucial in treating patients with acute pancreatitis (AP). The infectious process in AP often predisposes to subsequent sepsis by damaging not only the pancreas, but retroperitoneal tissues as well. Among other AP-associated factors, are the rapidly developing immune imbalance, the poor penetration of antimicrobial agents into necrotic tissue, and the impossibility of a single surgical debridement. Antibacterial and antifungal therapy for patients with infected necrosis and AP-associated extra-pancreatic infections remains a complex and largely unresolved problem, partially due to the high occurrence of multiresistant pathogens. The preventive use of antimicrobial agents has been discussed in the literature; however, the lack of consistent results makes it difficult to develop a unified strategy and clinical guidelines on this specific issue. Recent meta-analyses provide no conclusive evidence that antibacterial prophylaxis reduces the infection rate, mortality, or the need for surgical treatment in patients with necrotizing pancreatitis. We found only two studies indicating the benefits of using carbapenems for prophylactic purposes and one meta-analysis indicating a reduction in mortality under antibiotic treatment started no later than 72 h after the onset of the attack. Selective bowel decontamination is considered as one of the preventive anti-infection measures, although the available data may not be fully reliable. The main indications for antibacterial therapy in patients with AP are confirmed infected necrosis or extra-pancreatic infection, as well as clinical symptoms of suspected infection. Intra-arterial administration or local treatment with antibiotics can increase the efficacy of antibacterial therapy. No randomized studies on antifungal prophylaxis in AP are available; some reports though recommend using such therapy among patients at high risk of invasive candidiasis.

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The aim of the study was to develop, evaluate, and validate an artificial neural network to predict coronary microvascular obstruction (CMVO) during percutaneous coronary interventions (PCI) in patients with myocardial infarctions (MI) based on the parameters, which are routinely available in an operating room when choosing a surgical approach.Materials and Methods. 5621 patients with MI and emergency PCI were retrospectively selected from the database of the City Clinical Hospital No.13 (Nizhny Novgorod, Russia); among them, there were 3935 men (70%) and 1686 women (30%), their mean age was 61.5±10.8 years. CMVO was recorded in 201 (4%) patients (the blood flow in the infarction-related artery after PCI was less than 3 points according to TIMI flow grade). The following input parameters were assessed: age, gender, past history of coronary artery disease, previous revascularization, presence of ST-segment elevation, a class of acute heart failure, a fact of systemic thrombolytic therapy administration and its effectiveness, symptom-to-balloon time, severity of coronary thrombosis and atherosclerosis, the number of stents and the number of operated coronary arteries. The sampling was divided into a training group (n=4060), a testing group (n=717), and an independent validation group (n=844).Results. We developed an artificial neural network by a fully connected multilayer perception with forward signal propagation and two hidden layers (the area under the ROC curve -0.69) to predict CMVO based on the subsampling for training and testing. The network model was tested on an independent subsampling (the area under the ROC curve -0.64, negative predictive value -97.4%, positive predictive value -14.6%). Conclusion.The developed artificial neural network enables to use the parameters routinely available in an operating room when choosing a surgical approach and predict CMVO development during PCI in MI patients with accuracy sufficient for practical use.

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