Glycaemic variability, infections and mortality in a medical-surgical intensive care unit.

In critically ill patients, glycaemic variability (GV) was reported as a better predictor of mortality than mean blood glucose level (BGL). We compared the ability of different GV indices and mean BGLs to predict mortality and intensive care unit-acquired infections in a population of ICU patients.Retrospective study on adult ICU patients with ≥ three BGL measurements. GV was assessed by SD, coefficient of variation (CV) and mean amplitude of glycaemic excursion (MAGE), and by one timeweighted index, the glycaemic lability index (GLI), and compared with mean BGL. We studied 2782 patients admitted to the 12-bed medical-surgical ICU of a teaching hospital from January 2004 until December 2010.Logistic regression analyses were performed to assess the association between GV and ICU mortality and ICU-acquired infections. The areas under receiver operating characteristic curves were calculated to compare the discriminatory ability of GV and mean BGL for infections and mortality.Mortality was 16.6%, and 30% of patients had at least one infection. Patients with infections or diabetes or who were treated with insulin had a higher mean BGL and GV than other patients. GLI, SD, CV and MAGE were significantly associated with infections and mortality; mean BGL was not. Quartiles of increasing GLI were independently associated with higher mortality and an increased infection rate. Patients in the upper quartile of mean BGL and GLI had the strongest association with infections (odds ratio, 5.044 [95% CI, 1.695-15.007]; P = 0.004).High GV is associated with higher risk of ICUCrit acquired infection and mortality

Algorithm and performance of a clinical IMRT beam-angle optimization system

This paper describes the algorithm and examines the performance of an IMRT beam-angle optimization (BAO) system. In this algorithm successive sets of beam angles are selected from a set of predefined directions using a fast simulated annealing (FSA) algorithm. An IMRT beam-profile optimization is performed on each generated set of beams. The IMRT optimization is accelerated by using a fast dose calculation method that utilizes a precomputed dose kernel. A compact kernel is constructed for each of the predefined beams prior to starting the FSA algorithm. The IMRT optimizations during the BAO are then performed using these kernels in a fast dose calculation engine. This technique allows the IMRT optimization to be performed more than two orders of magnitude faster than a similar optimization that uses a convolution dose calculation engine.Comment: Final version that appeared in Phys. Med. Biol. 48 (2003) 3191-3212. Original EPS figures have been converted to PNG files due to size limi

Bright spots: seeds of a good Anthropocene

The scale, rate, and intensity of humans’ environmental impact has engendered broad discussion about how to find plausible pathways of development that hold the most promise for fostering a better future in the Anthropocene. However, the dominance of dystopian visions of irreversible environmental degradation and societal collapse, along with overly optimistic utopias and business‐as‐usual scenarios that lack insight and innovation, frustrate progress. Here, we present a novel approach to thinking about the future that builds on experiences drawn from a diversity of practices, worldviews, values, and regions that could accelerate the adoption of pathways to transformative change (change that goes beyond incremental improvements). Using an analysis of 100 initiatives, or “seeds of a good Anthropocene”, we find that emphasizing hopeful elements of existing practice offers the opportunity to: (1) understand the values and features that constitute a good Anthropocene, (2) determine the processes that lead to the emergence and growth of initiatives that fundamentally change human–environmental relationships, and (3) generate creative, bottom‐up scenarios that feature well‐articulated pathways toward a more positive future

Identification of a novel coronavirus in patients with severe acute respiratory syndrome

BACKGROUND: The severe acute respiratory syndrome (SARS) has recently been identified as a new clinical entity. SARS is thought to be caused by an unknown infectious agent. METHODS: Clinical specimens from patients with SARS were searched for unknown viruses with the use of cell cultures and molecular techniques. RESULTS: A novel coronavirus was identified in patients with SARS. The virus was isolated in cell culture, and a sequence 300 nucleotides in length was obtained by a polymerase-chain-reaction (PCR)-based random-amplification procedure. Genetic characterization indicated that the virus is only distantly related to known coronaviruses (identical in 50 to 60 percent of the nucleotide sequence). On the basis of the obtained sequence, conventional and real-time PCR assays for specific and sensitive detection of the novel virus were established. Virus was detected in a variety of clinical specimens from patients with SARS but not in controls. High concentrations of viral RNA of up to 100 million molecules per milliliter were found in sputum. Viral RNA was also detected at extremely low concentrations in plasma during the acute phase and in feces during the late convalescent phase. Infected patients showed seroconversion on the Vero cells in which the virus was isolated. CONCLUSIONS: The novel coronavirus might have a role

Does high-dose metformin cause lactic acidosis in type 2 diabetic patients after CABG surgery? A double blind randomized clinical trial

Metformin is a dimethyl biguanide oral anti-hyperglycemic agent. Lactic acidosis due to metformin is a fatal metabolic condition that limits its use in patients in poor clinical condition, consequently reducing the number of patients who benefit from this medication. In a double blind randomized clinical trial, we investigated 200 type 2 diabetic patients after coronary artery bypass surgery in the open heart ICU of the Mazandaran Heart Center, and randomly assigned them to equal intervention and control groups. The intervention group received regular insulin infusion along with 2 metformin 500 mg tablets every twelve hours, while the control group received only intravenous insulin with 2 placebo tablets every twelve hours. Lactate level, pH, base excess, blood glucose and serum creatinine were measured over five 12 h periods, with data averaged for each period. The primary outcome in this study was high lactate levels. Comparison between the 2 groups was made by independent Student’s t-test. To compare changes in multiple measures in each group and analysis of group interaction, a repeated measurement ANOVA test was used

Haematogenous Staphylococcus aureus meningitis. A 10-year nationwide study of 96 consecutive cases

BACKGROUND: Haematogenous Staphylococcus aureus meningitis is rare but associated with high mortality. Knowledge about the disease is still limited. The objective of this study was to evaluate demographic and clinical prognostic features of bacteraemic S. aureus meningitis. METHODS: Nationwide surveillance in Denmark from 1991 to 2000 with clinical and bacteriological data. Risks of death were estimated by Cox proportional hazards regression analysis. RESULTS: Among 12480 cases of S. aureus bacteraemia/sepsis, we identified 96 cases of non-surgical bacteraemic S. aureus meningitis (0.8%). Incidence rates were 0.24 (95% confidence interval [CI], 0.18 to 0.30)/100 000 population between 1991–1995 and 0.13 (CI, 0.08 to 0.17)/100 000 population between 1996–2000. Mortality was 56%. After adjustment, only co morbidity (hazard ratio [HR], 3.45; CI, 1.15 to 10.30) and critical illness (Pitt score ≥ 4) (HR, 2.14; CI, 1.09 to 4.19) remained independent predictors of mortality. CONCLUSION: The incidence, but not mortality of bacteraemic S. aureus meningitis decreased during the study period. Co morbidity and critical illness were independent predictors of a poor outcome

The Plasmodium falciparum STEVOR Multigene Family Mediates Antigenic Variation of the Infected Erythrocyte

Modifications of the Plasmodium falciparum–infected red blood cell (iRBC) surface have been linked to parasite-associated pathology. Such modifications enable the parasite to establish long-lasting chronic infection by evading antibody mediate immune recognition and splenic clearance. With the exception of the well-demonstrated roles of var-encoded PfEMP1 in virulence and immune evasion, the biological significance of other variant surface antigens (rif and stevor) is largely unknown. While PfEMP1 and RIFIN have been located on the iRBC surface, recent studies have located STEVOR at the iRBC membrane where it may be exposed on the erythrocyte surface. To investigate the role of STEVOR in more detail, we have developed antibodies against two putative STEVOR proteins and used a combination of indirect immunofluorescence assays (IFA), live IFA, flow cytometry, as well as agglutination assays, which enable us to demonstrate that STEVOR is clonally variant at the surface of schizont stage parasites. Crucially, expression of different STEVOR on the surface of the iRBC changes the antigenic property of the parasite. Taken together, our data for the first time demonstrate that STEVOR plays a role in creating antigenic diversity of schizont stage parasites, thereby adding additional complexity to the immunogenic properties of the iRBC. Furthermore, it clearly demonstrates that to obtain a complete understanding of how parasite-induced pathology is linked to variation on the surface of the iRBC, focusing the interactions of multiple multigene families needs to be considered

Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization

Do human societies from around the world exhibit similarities in the way that they are structured, and show commonalities in the ways that they have evolved? These are long-standing questions that have proven difficult to answer. To test between competing hypotheses, we constructed a massive repository of historical and archaeological information known as "Seshat: Global History Databank." We systematically coded data on 414 societies from 30 regions around the world spanning the last 10,000 years. We were able to capture information on 51 variables reflecting nine characteristics of human societies, such as social scale, economy, features of governance, and information systems. Our analyses revealed that these different characteristics show strong relationships with each other and that a single principal component captures around three-quarters of the observed variation. Furthermore, we found that different characteristics of social complexity are highly predictable across different world regions. These results suggest that key aspects of social organization are functionally related and do indeed coevolve in predictable ways. Our findings highlight the power of the sciences and humanities working together to rigorously test hypotheses about general rules that may have shaped human history