Fluid resuscitation practice patterns in intensive care units of the USA: a cross-sectional survey of critical care physicians.

BACKGROUND: Fluid resuscitation is a cornerstone of intensive care treatment, yet there is a lack of agreement on how various types of fluids should be used in critically ill patients with different disease states. Therefore, our goal was to investigate the practice patterns of fluid utilization for resuscitation of adult patients in intensive care units (ICUs) within the USA. METHODS: We conducted a cross-sectional online survey of 502 physicians practicing in medical and surgical ICUs. Survey questions were designed to assess clinical decision-making processes for 3 types of patients who need volume expansion: (1) not bleeding and not septic, (2) bleeding but not septic, (3) requiring resuscitation for sepsis. First-choice fluid used in fluid boluses for these 3 patient types was requested from the respondents. Descriptive statistics were performed using a Kruskal-Wallis test to evaluate differences among the physician groups. Follow-up tests, including t tests, were conducted to evaluate differences between ICU types, hospital settings, and bolus volume. RESULTS: Fluid resuscitation varied with respect to preferences for the factors to determine volume status and preferences for fluid types. The 3 most frequently preferred volume indicators were blood pressure, urine output, and central venous pressure. Regardless of the patient type, the most preferred fluid type was crystalloid, followed by 5 % albumin and then 6 % hydroxyethyl starches (HES) 450/0.70 and 6 % HES 600/0.75. Surprisingly, up to 10 % of physicians still chose HES as the first choice of fluid for resuscitation in sepsis. The clinical specialty and the practice setting of the treating physicians also influenced fluid choices. CONCLUSIONS: Practice patterns of fluid resuscitation varied in the USA, depending on patient characteristics, clinical specialties, and practice settings of the treating physicians.

Genetic Studies Identify Critical Biomarkers and Refine the Classification of Malignant Gliomas

Gliomagenesis is driven by a complex network of genetic alterations and while the glioma genome has been a focus of investigation for many years; critical gaps in our knowledge of this disease remain. The identification of novel molecular biomarkers remains a focus of the greater cancer community as a method to improve the consistency and accuracy of pathological diagnosis. In addition, novel molecular biomarkers are drastically needed for the identification of targets that may ultimately result in novel therapeutics aimed at improving glioma treatment. Through the identification of new biomarkers, laboratories will focus future studies on the molecular mechanisms that underlie glioma development. Here, we report a series of genomic analyses identifying novel molecular biomarkers in multiple histopathological subtypes of glioma and refine the classification of malignant gliomas. We have completed a large scale analysis of the WHO grade II-III astrocytoma exome and report frequent mutations in the chromatin modifier, alpha thalassemia mental retardation x-linked (ATRX), isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2), and mutations in tumor protein 53 (TP53) as the most frequent genetic mutations in low grade astrocytomas. Furthermore, by analyzing the status of recurrently mutated genes in 363 brain tumors, we establish that highly recurrent gene mutational signatures are an effective tool in stratifying homogeneous patient populations into distinct groups with varying outcomes, thereby capable of predicting prognosis. Next, we have established mutations in the promoter of telomerase reverse transcriptase (TERT) as a frequent genetic event in gliomas and in tissues with low rates of self renewal. We identify TERT promoter mutations as the most frequently mutated gene in primary glioblastoma. Additionally, we show that TERT promoter mutations in combination with IDH1 and IDH2 mutations are able to delineate distinct clinical tumor cohorts and are capable of predicting median overall survival more effectively than standard histopathological diagnosis alone. Taken together, these data advance our understanding of the genetic alterations that underlie the transformation of glial cells into neoplasms and we provide novel genetic biomarkers and multi – gene mutational signatures that can be utilized to refine the classification of malignant gliomas and provide opportunity for improved diagnosis.