An ML prediction model based on clinical parameters and automated CT scan features for COVID-19 patients.

Outcome prediction for individual patient groups is of paramount importance in terms of selection of appropriate therapeutic options, risk communication to patients and families, and allocating resource through optimum triage. This has become even more necessary in the context of the current COVID-19 pandemic. Widening the spectrum of predictor variables by including radiological parameters alongside the usually utilized demographic, clinical and biochemical ones can facilitate building a comprehensive prediction model.

Safety and efficacy of polymyxin B in multidrug resistant Gram-negative severe sepsis and septic shock.

Background And Aims: The emergence of multidrug resistant strains of Gram-negative bacteria, especially the lactose nonfermenters like Pseudomonas and Acinetobacter, in the intensive care units have prompted renewed worldwide interest in the polymyxins. However, perceived nephrotoxicity has been a major vexation limiting their early and regular use in severe sepsis. This study was conducted to assess the safety and efficacy of polymyxin B in patients with severe sepsis and septic shock.