Validation of bioelectrical impedance analysis for body composition assessment in children with obesity aged 8-14y

BACKGROUND & AIMS: The aim was to generate a predictive equation to assess body composition (BC) in children with obesity using bioimpedance (BIA), and avoid bias produced by different density levels of fat free mass (FFM) in this population. METHODS: This was a cross-sectional validation study using baseline data from a randomized intervention trial to treat childhood obesity. Participants were 8 to 14y (n = 315), underwent assessments on anthropometry and BC through Air Displacement Plethysmography (ADP), Dual X-Ray Absorptiometry and BIA. They were divided into a training (n = 249) and a testing subset (n = 66). In addition, the testing subset underwent a total body water assessment using deuterium dilution, and thus obtained results for the 4-compartment model (4C). A new equation to estimate FFM was created from the BIA outputs by comparison to a validated model of ADP adjusted by FFM density in the training subset. The equation was validated against 4C in the testing subset. As reference, the outputs from the BIA device were also compared to 4C. RESULTS: The predictive equation reduced the bias from the BIA outputs from 14.1% (95%CI: 12.7, 15.4) to 4.6% (95%CI: 3.8, 5.4) for FFM and from 18.4% (95%CI: 16.9, 19.9) to 6.4% (95% CI: 5.3, 7.4) for FM. Bland-Altman plots revealed that the new equation significantly improved the agreement with 4C; furthermore, the observed trend to increase the degree of bias with increasing FM and FFM also disappeared. CONCLUSION: The new predictive equation increases the precision of BC assessment using BIA in children with obesity

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Implementation of the evidence for the improvement of nursing care to the critical patient's family: a participatory action research

Background: There are many descriptive studies regarding the needs of the family, as well as those regarding nursing care aimed directly at family members. However, there is no widespread application of such evidence in clinical practice. There has also been no analysis made of the evolution of patterns of knowing during the act of improving clinical practice. Therefore, the purpose of the study is to understand the change process aimed at improving care to critical patient's families, and to explore the evolution of patterns of knowing that nurses use in this process. Methods: Qualitative study with a Participatory Action Research method, in accordance with the Kemmis and McTaggart model. In this model, nurses can observe their practice, reflect upon it and compare it with scientific evidence, as well as define, deploy and evaluate improvement strategies adapted to the context. Simultaneously, the process of empowerment derived from the Participatory Action Research allows for the identification of patterns of knowing and their development over time. The research will take place in the Intensive Care Units of a tertiary hospital. The participants will be nurses who are part of the regular workforce of these units, with more than five years of experience in critical patients, and who are motivated to consider and critique their practice. Data collection will take place through participant observation, multi-level discussion group meetings and documentary analysis. A content analysis will be carried out, following a process of codification and categorisation, with the help of Nvivo10. The approval date and the beginning of the funding were December 2012 and 2013, respectively. Discussion: The definition, introduction and evaluation of care strategies for family members will allow for their real and immediate implementation in practice. The study of the patterns of knowing in the Participatory Action Research will be part of the theoretical and practical feedback process of a professional discipline. Also, the identification of the construction and evolution of knowledge will provide decision elements to managers and academics when choosing strategies for increased quality

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing

Chromothripsis is a mutational phenomenon characterized by massive, clustered genomic rearrangements that occurs in cancer and other diseases. Recent studies in selected cancer types have suggested that chromothripsis may be more common than initially inferred from low-resolution copy-number data. Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we analyze patterns of chromothripsis across 2,658 tumors from 38 cancer types using whole-genome sequencing data. We find that chromothripsis events are pervasive across cancers, with a frequency of more than 50% in several cancer types. Whereas canonical chromothripsis profiles display oscillations between two copy-number states, a considerable fraction of events involve multiple chromosomes and additional structural alterations. In addition to non-homologous end joining, we detect signatures of replication-associated processes and templated insertions. Chromothripsis contributes to oncogene amplification and to inactivation of genes such as mismatch-repair-related genes. These findings show that chromothripsis is a major process that drives genome evolution in human cancer

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Safety and efficacy of inulin and oligofructose supplementation in infant formula: Results from a randomized clinical trial

10.1016/j.clnu.2013.02.00

Influence of Feeding Types during the First Months of Life on Calciuria Levels in Healthy Infants: A Secondary Analysis from a Randomized Clinical Trial

Background/Aims: Dietary factors can modify calciuria. We aim to investigate urinary calcium excretion in healthy infants according to their protein. Methods: Secondary data analysis from a randomized clinical trial where healthy term infants were randomized after birth to a higher (HP) or lower (LP) protein content formula that was consumed until age 1 year. A non-randomized group of breastfed (BF) infants was used for reference. Anthropometry, dietary intakes and calciuria (calcium/creatinine ratios) from spot urine samples were assessed at ages 3 and 6 months. At 6 months, the kidney volumes were assessed using ultrasonography, and the serum urea and creatinine levels were determined. Results: BF infants showed the highest calciuria levels, followed by the HP and the LP groups (p < 0.001 for all comparisons). Either protein intakes or formula types modulated the calciuria in linear regression models adjusted for other influencing dietary factors. The usual cut-off values classified 37.8% (BF), 16.8% (HP) and 4.9% (LP) of the infants as hypercalciuric. Conclusions: Feeding types during the first months of life affect calciuria, with BF infants presenting the highest levels. We propose new cut-off values, based on feeding types, to prevent the overestimation in hypercalciuria diagnoses among BF infants

A novel approach to assess body composition in children with obesity from density of the fat-free mass

Background & aims: Assessment of Fat Mass (FM) and fat free mass (FFM) using Air-displacement plethysmography (ADP) technique assumes constant density of FFM (DFFM) by age and sex. It has been recently shown that DFFM further varies according to body mass index (BMI), meaning that ADP body composition assessments of children with obesity could be biased if DFFM is assumed to be constant. The aim of this study was to validate the use of the calculations of DFFM (rather than constant density of the FFM) to improve accuracy of body composition assessment in children with obesity. / Methods: cross-sectional validation study in 66 children with obesity (aged 8–14 years) where ADP assessments of body composition assuming constant density (FFMBODPOD and FMBODPOD) were compared to those where DFFM was adjusted in relation to BMI (FFMadjusted and FMadjusted), and both compared to the gold standard reference, the 4-component model (FFM4C and FM4C). / Results: FFMBODPOD was overestimated by 1.50 kg (95%CI -0.68 kg, 3.63 kg) while FFMadjusted was 0.71 kg (−1.08 kg, 2.51 kg) (percentage differences compared to FFM4C were 4.9% (±2.9%) and 2.8% (±2.1%), respectively (p < 0.001)). Consistently, FM was underestimated by both methods, representing a mean difference between methods of 4.0% (±2.9%) and 6.8% (±3.8%), respectively, when compared to the reference method. The agreement and reliability of body composition assessments were improved when adjusted using calculations (adjusted models) rather than assuming constant DFFM. / Conclusions: The use of constant values for fat-free mass properties may increase bias when assessing body composition (FM and FFM) in children with obesity by two-component techniques such as ADP. Using adjusted corrections as proposed in the present work may reduce the bias by half