Annals of translational medicine
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We previously used a pig model to demonstrate that noninvasive positive pressure ventilation (NPPV) may be a safe alternative to endotracheal intubation (ET). We sought to validate our model by quantifying the pressure threshold of esophageal anastomoses in human cadavers as a step before a clinical trial. ⋯ We created a human cadaveric model that in conjunction with our porcine data demonstrates that a human esophageal anastomosis can tolerate manifold higher pressures than are delivered to the esophagus by NPPV. This is the final step before a trial of NPPV in patients following esophagectomy.
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On June 14, 2015, Ladha and colleagues published an article in the BMJ entitled "Intraoperative protective mechanical ventilation and risk of postoperative respiratory complications: hospital based registry study", which investigated the effects of intraoperative protective ventilation on major postoperative respiratory complications. This study used data of over 69,265 patients in order to investigate patients over the age of 18 who underwent a non-cardiac surgical procedure between January 2007 and August 2014 and required general anesthesia with endotracheal intubation. The investigators found that intraoperative protective ventilation was associated with a decreased risk of postoperative respiratory complications. This study raises important questions about the ventilatory management of surgical patients.
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Electronic medical record (EMR) system has been widely used in clinical practice. Instead of traditional record system by hand writing and recording, the EMR makes big data clinical research feasible. The most important feature of big data research is its real-world setting. ⋯ To make ends meet, a series of articles introducing data management techniques are put forward to guide clinicians to big data clinical research. The present educational article firstly introduces some basic knowledge on R language, followed by some data management skills on creating new variables, recoding variables and renaming variables. These are very basic skills and may be used in every project of big data research.
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On April 23, 2015, Kaukonen and colleagues published an article in the New England Journal of Medicine entitled "Systemic inflammatory response syndrome criteria in defining severe sepsis", which investigated the sensitivity and validity of using SIRS criteria to define intensive care unit (ICU) patients with severe sepsis. This study used admission data of over 100,000 patients in order to investigate patients with severe sepsis who either met or didn't meet SIRS criteria. The investigators found that in-hospital mortality increased linearly with the number of SIRS criteria met; raising concern that SIRS criterion is not sensitive enough. This study of SIRS criteria raises important questions about the recognition and diagnosis of severe sepsis.