Methods: Retrospective medical record and database review of adult inpatients with a hospital stay greater than 24 h.

Results: 198 (15.7%) of 1258 patients with a RRT call, had a pre-existing NFR order. Patients with, compared to those without a pre-existing NFR, were older (median years, 81 vs 70, p < 0.01), similar gender

(males, 56.6% vs 54.3%, p = 0.55), the trigger be the worried criterion (48.5% vs 33.9%, p < 0.01) and have had a prior RRT call (30.8% vs 18.0%, p < 0.01). At time of RRT attendance, NFR patients had a higher respiratory rate (24 vs 20, p < 0.01), lower SaO(2) (93% vs 97%, p = 0.02) and just as likely to receive a critical care (24.2% vs 25.8%, p = 0.63) or ward type (88.9% vs 90.1%, p = 0.61) intervention. NFR patients were less likely to be admitted LY2090314 to an ICU (2.0% vs 9.4%, p < 0.01), more likely to be left on the ward (92.4% vs 80.3%, p < 0.01), and be documented not for further RRT calls (2.5% vs 0.9%, p = 0.06), but have a similar mortality (5.6% Anlotinib cell line vs 3.5%, p = 0.16), at time of RRT call.

Conclusions: RRT calls to patients with pre-existing NFR orders are not uncommon. The worried criterion is more often the trigger, they have abnormal respiratory observations at time of

call, a similar level of intervention, less likely to be admitted to the ICU and more likely to be documented not for further RRT calls. Crown Copyright (C) 2013 Published by Elsevier Ireland Ltd. All rights reserved.”
“Human diseases can be caused by complex mechanisms involving aberrations in numerous proteins and pathways. With recent advances in genomics, elucidating the molecular basis of disease on a personalized level has become an attainable goal. In many cases, relevant molecular targets will be identified for which approved drugs learn more already exist, and the potential repositioning of these drugs to a new indication can be investigated. Repositioning is an accelerated route

for drug discovery because existing drugs have established clinical and pharmacokinetic data. Personalized medicine and repositioning both aim to improve the productivity of current drug discovery pipelines, which expend enormous time and cost to develop new drugs, only to have them fail in clinical trials because of lack of efficacy or toxicity. Here, we discuss the current state of research in these two fields, focusing on recent large-scale efforts to systematically find repositioning candidates and elucidate individual disease mechanisms in cancer. We also discuss scenarios in which personalized drug repositioning could be particularly rewarding, such as for diseases that are rare or have specific mutations, as well as current challenges in this field. With an increasing number of drugs being approved for rare cancer subtypes, personalized medicine and repositioning approaches are poised to significantly alter the way we diagnose diseases, infer treatments and develop new drugs.