Bioimpedance as a measure of fluids in patients with septic shock. A prospective observational study

Background

Septic shock is often treated with aggressive fluid resuscitation leading to profound fluid overload. The assessment of fluid status relies on suboptimal measures making treatment difficult. Bioelectrical impedance analysis is an alternative but the validity is unclear. The aim of this study was to determine the validity of bioelectrical impedance analysis for fluid measures in patients with septic shock.

Methods

Single-center, prospective observational cohort study. We included adult ICU patients with septic shock. We evaluated the agreement between measures on the left and right side of the patient and measures 1 h apart by two bioelectrical impedance devices. Results are presented as Bland Altman plots with 95% Limits of Agreements (LoA) and as correlations between bioelectrical impedance analysis results and clinical markers of fluids.

Results

Forty-nine patients were included. The agreement between measures on the left and the right side of the patient and after 1 h was overall without bias, but with wide LoA's. Fluid overload 1 h apart showed the most narrow 95% LoA (−2.4–2.9 L). The same wide limits of agreements were observed when comparing devices. For example, total body water with 95% LoA of −14.8 –16.7 L. Correlations between bioelectrical impedance analysis and clinical measures were low but statistically significant.

Conclusions

In patients with septic shock bioelectrical impedance analysis had no systematic errors or bias, but wide limits of agreement, indicating that the devices have a large and uncorrectable random error. Fluid status by bioelectrical impedance analysis is not sufficiently accurate to guide treatment in this group of patients.     

Therapeutic augmentation of NO-sGC-cGMP signalling: lessons learned from pulmonary arterial hypertension and heart failure

Heart Failure Reviews - The nitric oxide (NO)–guanylate cyclase (GC)–cyclic guanosine monophosphate (cGMP) pathway plays an important role in cardiovascular, pulmonary and renal...     

Psychosocial outcomes of group prenatal care

Journal of Public Health - Group prenatal care provides an alternative model of prenatal care that allows for collaboration with peers, education, discussion, and self-management training in...     

Immunotherapy: A new standard in the treatment of metastatic clear cell renal cell carcinoma

Renal cell cancer (RCC) represents 2%-3% of all adulthood cancers and is the most common malignant neoplasm of the kidney (90%). In the mid-nineties of the last century, the standard of treatment for patients with metastatic RCC was cytokines. Sunititib and pazopanib were registered in 2007 and 2009, respectively, and have since been the standard first-line treatment for metastatic clear cell RCC (mccRCC). Renal cell cancer is a highly immunogenic tumor with tumor infiltrating cells, including CD8+ T lymphocytes, dendritic cells, natural killer cells (NK) and macrophages. This observation led to the design of new clinical trials in which patients were treated with immunotherapy. With the growing evidence that proangiogenic factors can have immunomodulatory effects on the host’s immune system, the idea of combining angiogenic drugs with immunotherapy has emerged, and new clinical trials have been designed. In the last few years, several therapeutic options have been approved [immunotherapy and immunotherapy/tyrosine kinase inhibitors (TKI)] for the first-line treatment of mccRCC. Nivolumab/ipilimumab is approved for the treatment of patients with intermediate and poor prognoses. Several checkpoint inhibitors (pembrolizumab, nivolumab, avelumab) in combination with TKI (axitinib, lenvatinib, cabozantinib) are approved for the treatment of patients regardless of their International mRCC Database Consortium prognostic group and PD-L1 expression. There is no specific and ideal biomarker that could help in selecting the ideal patient for the appropriate first-line treatment.     

Effects of Wenyang Zhenshuai Granules on the Expression of Key Mitochondrial Autophagy Proteins in the Doxorubicin-Induced Model of H9c2 Cardiomyocyte Injury

Bulletin of Experimental Biology and Medicine - This study aimed to explore the effects of Wenyang Zhenshuai granules (WZG) on the morphology of cardiomyocytes, cell viability, and the expression...     

RNA sequencing steps toward the first line

• DNA is the sequence that codes for proteins.
• Messenger RNA is transcribed from the DNA sequence of genes and translated into protein.
• It can be difficult to predict how a change in the DNA sequence will affect messenger RNA and protein quantity and quality.
• DNA translocation changes can cause the joining of sequences from two different genes or different parts of the same gene.
• DNA sequencing is often used clinically to predict how DNA changes might affect proteins.
• Alternatively, RNA sequencing can be used as a more direct measure of the effect of DNA changes on the protein products.
• This sequencing is important for identifying changes in cancer that may indicate response to targeted therapy, prognosis, or diagnosis.

     

Comprehensive interrogation of gene lists from genome-scale cancer screens with oncoEnrichR

Genome-scale screening experiments in cancer produce long lists of candidate genes that require extensive interpretation for biological insight and prioritization for follow-up studies. Interrogation of gene lists frequently represents a significant and time-consuming undertaking, in which experimental biologists typically combine results from a variety of bioinformatics resources in an attempt to portray and understand cancer relevance. As a means to simplify and strengthen the support for this endeavor, we have developed oncoEnrichR, a flexible bioinformatics tool that allows cancer researchers to comprehensively interrogate a given gene list along multiple facets of cancer relevance. oncoEnrichR differs from general gene set analysis frameworks through the integration of an extensive set of prior knowledge specifically relevant for cancer, including ranked gene-tumor type associations, literature-supported proto-oncogene and tumor suppressor gene annotations, target druggability data, regulatory interactions, synthetic lethality predictions, as well as prognostic associations, gene aberrations and co-expression patterns across tumor types. The software produces a structured and user-friendly analysis report as its main output, where versions of all underlying data resources are explicitly logged, the latter being a critical component for reproducible science. We demonstrate the usefulness of oncoEnrichR through interrogation of two candidate lists from proteomic and CRISPR screens. oncoEnrichR is freely available as a web-based service hosted by the Galaxy platform ( https://oncotools.elixir.no ), and can also be accessed as a stand-alone R package ( https://github.com/sigven/oncoEnrichR ).