Pro/con debate: Is intensive insulin therapy targeting tight blood glucose control of benefit in critically ill patients?

You have decided to develop a protocol for insulin therapy in your intensive care unit (ICU). You wonder about the merit of using intensive insulin therapy (IIT) to maintain tight blood glucose control in your patients

Resource use and outcome in critically ill patients with hematological malignancy: a retrospective cohort study

INTRODUCTION: The paucity of data on resource use in critically ill patients with hematological malignancy and on these patients' perceived poor outcome can lead to uncertainty over the extent to which intensive care treatment is appropriate. The aim of the present study was to assess the amount of intensive care resources needed for, and the effect of treatment of, hemato-oncological patients in the intensive care unit (ICU) in comparison with a nononcological patient population with a similar degree of organ dysfunction. METHODS: A retrospective cohort study of 101 ICU admissions of 84 consecutive hemato-oncological patients and 3,808 ICU admissions of 3,478 nononcological patients over a period of 4 years was performed. RESULTS: As assessed by Therapeutic Intervention Scoring System points, resource use was higher in hemato-oncological patients than in nononcological patients (median (interquartile range), 214 (102 to 642) versus 95 (54 to 224), P < 0.0001). Severity of disease at ICU admission was a less important predictor of ICU resource use than necessity for specific treatment modalities. Hemato-oncological patients and nononcological patients with similar admission Simplified Acute Physiology Score scores had the same ICU mortality. In hemato-oncological patients, improvement of organ function within the first 48 hours of the ICU stay was the best predictor of 28-day survival. CONCLUSION: The presence of a hemato-oncological disease per se is associated with higher ICU resource use, but not with increased mortality. If withdrawal of treatment is considered, this decision should not be based on admission parameters but rather on the evolutional changes in organ dysfunctions

The prevalence of cardiac complications and their impact on outcomes in patients with non-traumatic subarachnoid hemorrhage.

Subarachnoid hemorrhage (SAH) is a serious condition, and a myocardial injury or dysfunction could contribute to the outcome. We assessed the prevalence and prognostic impact of cardiac involvement in a cohort with SAH. This is a prospective observational multicenter study. We included 192 patients treated for non-traumatic subarachnoid hemorrhage. We performed ECG recordings, echocardiographic examinations, and blood sampling within 24 h of admission and on days 3 and 7 and at 90 days. The primary endpoint was the evidence of cardiac involvement at 90 days, and the secondary endpoint was to examine the prevalence of a myocardial injury or dysfunction. The median age was 54.5 (interquartile range [IQR] 48.0-64.0) years, 44.3% were male and the median World Federation of Neurological Surgeons (WFNS) score was 2 (IQR 1-4). At day 90, 22/125 patients (17.6%) had left ventricular ejection fractions ≤ 50%, and 2/121 patients (1.7%) had evidence of a diastolic dysfunction as defined by mitral peak E-wave velocity by peak e' velocity (E/e') > 14. There was no prognostic impact from echocardiographic evidence of cardiac complications on neurological outcomes. The overall prevalence of cardiac dysfunction was modest. We found no demographic or SAH-related factors associated with 90 days cardiac dysfunction

Quantum Chemistry Calculations for Metabolomics

A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials (“standards”), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for “standards-free” identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples.A primary goal of metabolomics studies is to fully characterize the small-molecule composition of complex biological and environmental samples. However, despite advances in analytical technologies over the past two decades, the majority of small molecules in complex samples are not readily identifiable due to the immense structural and chemical diversity present within the metabolome. Current gold-standard identification methods rely on reference libraries built using authentic chemical materials (“standards”), which are not available for most molecules. Computational quantum chemistry methods, which can be used to calculate chemical properties that are then measured by analytical platforms, offer an alternative route for building reference libraries, i.e., in silico libraries for “standards-free” identification. In this review, we cover the major roadblocks currently facing metabolomics and discuss applications where quantum chemistry calculations offer a solution. Several successful examples for nuclear magnetic resonance spectroscopy, ion mobility spectrometry, infrared spectroscopy, and mass spectrometry methods are reviewed. Finally, we consider current best practices, sources of error, and provide an outlook for quantum chemistry calculations in metabolomics studies. We expect this review will inspire researchers in the field of small-molecule identification to accelerate adoption of in silico methods for generation of reference libraries and to add quantum chemistry calculations as another tool at their disposal to characterize complex samples

Targeted tissue perfusion versus macrocirculation-guided standard care in patients with septic shock (TARTARE-2S) : study protocol and statistical analysis plan for a randomized controlled trial

Background: Septic shock has a 90-day mortality risk of up to 50 %. The hemodynamic targets, including mean arterial pressure (MAP) are not based on robust clinical data. Both severe hypotension and high doses of vasopressors may be harmful. Hence, re-evaluation of hemodynamic targets in septic shock is relevant. Methods/design: The targeted tissue perfusion versus macrocirculation-guided standard care in patients with septic shock (TARTARE-2S) trial is a prospective, two-parallel-group, randomized, open-label, multicenter trial with assessor-blinded outcome evaluation. We will randomize at least 200 patients with septic shock in four European intensive care units (ICUs) to test whether a tissue perfusion-guided treatment strategy based on capillary refill time, peripheral temperature, arterial lactate concentrations, and accepting lower MAP levels, leads to a faster resolution of shock than macrocirculation target-guided standard care. The primary outcome measure is days alive in 30 days with normal arterial blood lactate (first value of Discussion: The TARTARE-2S trial will provide important clinical data on treatment targets in septic shock, evaluating the impact of clinical tissue perfusion-guided hemodynamic treatment on a surrogate outcome combining resolution of shock (hyperlactatemia and vasopressors/inotropes), and 30-day mortality.Peer reviewe

Delayed Appearance of High Altitude Retinal Hemorrhages

When closely examined, a very large amount of climbers exhibit retinal hemorrhages during exposure to high altitudes. The incidence of retinal hemorrhages may be greater than previously appreciated as a definite time lag was observed between highest altitude reached and development of retinal bleeding. Retinal hemorrhages should not be considered warning signs of impending severe altitude illness due to their delayed appearance

Molecular Dynamics Simulations of Lipid Bilayers: Major Artifacts due to Truncating Electrostatic Interactions

We study the influence of truncating the electrostatic interactions in a fully hydrated pure dipalmitoylphosphatidylcholine (DPPC) bilayer through 20 ns molecular dynamics simulations. The computations in which the electrostatic interactions were truncated are compared to similar simulations using the Particle-Mesh Ewald (PME) technique. All examined truncation distances (1.8 to 2.5 nm) lead to major effects on the bilayer properties, such as enhanced order of acyl chains together with decreased areas per lipid. The results obtained using PME, on the other hand, are consistent with experiments. These artifacts are interpreted in terms of radial distribution functions $g(r)$ of molecules and molecular groups in the bilayer plane. Pronounced maxima or minima in g(r) appear exactly at the cutoff distance indicating that the truncation gives rise to artificial ordering between the polar phosphatidyl and choline groups of the DPPC molecules. In systems described using PME, such artificial ordering is not present