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Premorbid metformin exposure was not significantly associated with initial lactate levels (mean difference, 0.39 [-0.50 to 1.28]; i 2 = 72%; p = 0.39). Conclusions The meta-analysis suggests that premorbid metformin exposure is associated with decreased mortality in sepsis but not with hyperlactatemia. What are the potential mechanisms and whether there is any effect on organ dysfunction remain unclear. Copyright (c) 2019 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.To describe a case of atypical hemolytic uremic syndrome induced by influenza A infection with the p.Ile1157Thr C3 mutation. Data Sources Clinical observations of a patient. Study Selection Case reports. Data Extraction Data extracted from medical records, after patient's consent. Data Synthesis Four days prior to presentation to our hospital, a 16-year-old adolescent had a fever and arthralgia with hematuria. He was found to be positive for type A influenza and prescribed oseltamivir and acetaminophen by a primary-care physician. A bleeding tendency and purpura in the extremities and on the trunk developed; therefore, he was transferred to Chiba University Hospital. Hematology revealed severe thrombocytopenia, hyperbilirubinemia, and acute kidney injury. Aspartate aminotransferase, lactate dehydrogenase, and potassium could not be determined because of severe hemolysis. BIBR 1532 chemical structure Highly elevated blood urea nitrogen and creatinine levels indicated acute kidney injury. A platelet count of 24,000/μL indicated thrombocytolysis identified a mutation in C3 (p.Ile1157Thr), confirming the diagnosis of atypical hemolytic uremic syndrome. Conclusions Although managing thrombocytopenia secondary to infection, inclusion of atypical hemolytic uremic syndrome in the differential diagnosis at an early stage is important in clinical practice. Copyright (c) 2019 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.Acute stroke has a high morbidity and mortality in elderly population. Baseline confounding illnesses, initial clinical examination, and basic laboratory tests may impact prognostics. In this study, we aimed to establish a model for predicting in-hospital mortality based on clinical data available within 12 hours of hospital admission in elderly (≥ 65 age) patients who experienced stroke. Design Retrospective observational cohort study. Setting Academic comprehensive stroke center. Patients Elderly acute stroke patients-2005-2009 (n = 462), 2010-2012 (n = 122), and 2016-2017 (n = 123). Interventions None. Measurements and Main Results After institutional review board approval, we retrospectively queried elderly stroke patients' data from 2005 to 2009 (training dataset) to build a model to predict mortality. We designed a multivariable logistic regression model as a function of baseline severity of illness and laboratory tests, developed a nomogram, and applied it to patients from 2010 to 2012. Due to updated o 2012, the nomogram accurately predicted mortality with area under the curve of 0.79 (0.71-0.87) and scaled Brier's score of 0.17. Revalidation of the same model in the recent dataset from 2016 to 2017 confirmed accurate prediction with area under the curve of 0.83 (0.75-0.91) and scaled Brier's score of 0.27. Conclusions Baseline medical problems, clinical severity, and basic laboratory tests available within the first 12 hours of admission provided strong independent predictors of in-hospital mortality in elderly acute stroke patients. Our nomogram may guide interventions to improve acute care of stroke. Copyright (c) 2019 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.To identify actionable processes of care, quality indicators, or performance measures and their evidence base relevant to patients with persistent or chronic critical illness and their family members including themes relating to patient/family experience. Data Sources Two authors independently searched electronic, systemic review, and trial registration databases (inception to November 2016). Study Selection We included studies with an ICU length of stay of greater than or equal to 7 days as an inclusion criterion and reported actionable processes of care; quality improvement indicators, measures, or tools; or patient/family experience. We excluded case series/reports of less than 10 patients. Data Extraction Paired authors independently extracted data and performed risk of bias assessment. Data Synthesis We screened 13,130 references identifying 114 primary studies and 102 relevant reviews. Primary studies reported data on 24,252 participants; median (interquartile range) sample size of 70 (32-182). We identdistressing symptoms as well as enabling patient communication. Our findings are informative for clinicians and decision-makers when planning high-quality patient and family-focused care. Copyright (c) 2019 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.To use experience-based co-design to identify the key design requirements of a peer support model for critical care survivors; understand the use of the experience-based co-design method from clinician, patients, and family perspectives. Design Using experience-based co-design, qualitative data about participants' preferences for a peer support model were generated via workshops. Participants' perspectives of experience-based co-design were evaluated with focus groups. Setting University-affiliated hospital in Melbourne, Australia. Subjects Snowball sampling was used to recruit clinicians from across the care spectrum (ICU-community); critical care survivors and nominated family members were recruited using convenience sampling. Measurements and Main Results Consensus on a peer support model was reached through the experience-based co-design process, with the following key themes 1) socialization and group cohesion; 2) management of potential risks; and 3) individualized needs of patients and families. Evaluation of participants' perspectives of the experience-based co-design method identified five key themes 1) participation as a positive experience; 2) emotional engagement in the process; 3) learning from patients and family members; 4) feeling heard; and 5) practical challenges of experience-based co-design and readiness to participate. Conclusions Experience-based co-design was a feasible approach to developing a peer support model for use with critical care survivors and was well received by participants. Future testing of the co-designed peer support model in a pilot randomized controlled trial will enhance understanding of peer support in critical care and the use of experience-based co-design as a design methodology. Copyright (c) 2019 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine.