Dyspnoea in patients receiving noninvasive ventilation for acute respiratory failure: prevalence, risk factors and prognostic impact: A prospective observational study

Dyspnoea is a frequent and intense symptom in intubated patients, but little attention has been paid to dyspnoea during noninvasive mechanical ventilation in the intensive care unit (ICU).The objectives of this study were to quantify the prevalence, intensity and prognostic impact of dyspnoea in patients receiving noninvasive ventilation (NIV) for acute respiratory failure (ARF) based on secondary analysis of a prospective observational cohort study in patients who received ventilatory support for ARF in 54 ICUs in France and Belgium. Dyspnoea was measured by a modified Borg scale.Among the 426 patients included, the median (interquartile range) dyspnoea score was 4 (3-5) on admission and 3 (2-4) after the first NIV session (p=0.001). Dyspnoea intensity ≥4 after the first NIV session was associated with the Sequential Organ Failure Assessment Score (odds ratio (OR) 1.12, p=0.001), respiratory rate (OR 1.03, p=0.032), anxiety (OR 1.92, p=0.006), leaks (OR 2.5, p=0.002) and arterial carbon dioxide tension (OR 0.98, p=0.025). Dyspnoea intensity ≥4 was independently associated with NIV failure (OR 2.41, p=0.001) and mortality (OR 2.11, p=0.009), but not with higher post-ICU burden and altered quality of life.Dyspnoea is frequent and intense in patients receiving NIV for ARF and is associated with a higher risk of NIV failure and poorer outcome

Predicting the functional impact of protein mutations: application to cancer genomics

As large-scale re-sequencing of genomes reveals many protein mutations, especially in human cancer tissues, prediction of their likely functional impact becomes important practical goal. Here, we introduce a new functional impact score (FIS) for amino acid residue changes using evolutionary conservation patterns. The information in these patterns is derived from aligned families and sub-families of sequence homologs within and between species using combinatorial entropy formalism. The score performs well on a large set of human protein mutations in separating disease-associated variants (∼19 200), assumed to be strongly functional, from common polymorphisms (∼35 600), assumed to be weakly functional (area under the receiver operating characteristic curve of ∼0.86). In cancer, using recurrence, multiplicity and annotation for ∼10 000 mutations in the COSMIC database, the method does well in assigning higher scores to more likely functional mutations (‘drivers’). To guide experimental prioritization, we report a list of about 1000 top human cancer genes frequently mutated in one or more cancer types ranked by likely functional impact; and, an additional 1000 candidate cancer genes with rare but likely functional mutations. In addition, we estimate that at least 5% of cancer-relevant mutations involve switch of function, rather than simply loss or gain of function

High-flow nasal cannula oxygen therapy alone or with non-invasive ventilation during the weaning period after extubation in ICU: the prospective randomised controlled HIGH-WEAN protocol

INTRODUCTION: Recent practice guidelines suggest applying non-invasive ventilation (NIV) to prevent postextubation respiratory failure in patients at high risk of extubation failure in intensive care unit (ICU). However, such prophylactic NIV has been only a conditional recommendation given the low certainty of evidence. Likewise, high-flow nasal cannula (HFNC) oxygen therapy has been shown to reduce reintubation rates as compared with standard oxygen and to be as efficient as NIV in patients at high risk. Whereas HFNC may be considered as an optimal therapy during the postextubation period, HFNC associated with NIV could be an additional means of preventing postextubation respiratory failure. We are hypothesising that treatment associating NIV with HFNC between NIV sessions may be more effective than HFNC alone and may reduce the reintubation rate in patients at high risk. METHODS AND ANALYSIS: This study is an investigator-initiated, multicentre randomised controlled trial comparing HFNC alone or with NIV sessions during the postextubation period in patients at high risk of extubation failure in the ICU. Six hundred patients will be randomised with a 1:1 ratio in two groups according to the strategy of oxygenation after extubation. The primary outcome is the reintubation rate within the 7 days following planned extubation. Secondary outcomes include the number of patients who meet the criteria for moderate/severe respiratory failure, ICU length of stay and mortality up to day 90. ETHICS AND DISSEMINATION: The study has been approved by the ethics committee and patients will be included after informed consent. The results will be submitted for publication in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT03121482

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Sex difference in the risk of extubation failure in ICUs

Abstract Background Little attention has been paid to potential differences in prognosis between mechanically ventilated males and females in intensive care units (ICUs). We hypothesized that a sex gap in the risk of extubation failure in ICUs may exist. Methods Post hoc analysis of a large-scale clinical trial including patients at high risk of extubation failure in ICUs, with the aim of assessing the risk of extubation failure according to sex. The primary outcome was reintubation within the 7 days following extubation. Results Out of 641 patients, 425 (66%) were males and 216 (34%) were females. Males were more likely to be admitted for cardiac arrest and to have underlying ischemic heart disease whereas females were more likely to be admitted for coma and to have obesity. Whereas the rate of reintubation at 48 h was significantly higher in males than in females (11.0% vs. 6.0%; difference, + 5.0 [95% CI, 0.2 to 9.2]; P = 0.038), the rate of reintubation at day 7 did not significantly differ between males and females (16.7% vs. 11.1%; difference, + 5.6% [95%CI, − 0.3 to 10.8], P = 0.059). Using multivariable logistic regression analysis, male sex was independently associated with reintubation within the 7 days following extubation (adjusted OR 1.70 [95% CI, 1.01 to 2.89]; P = 0.048), even after adjustment on reason for admission, body-mass index, severity score, respiratory rate before extubation, and noninvasive ventilation after extubation. Conclusion In this post hoc analysis of a clinical trial including a homogeneous subset of patients at high risk of extubation failure, sex was independently associated with reintubation. The role of sex on outcomes should be systematically examined in future studies of critically ill patients

OncodriveFM

OncodriveFM depends on Python 3 and some external libraries, numpy, scipy, pandas and statsmodels./nThe easiest way to install all this software stack is using the well known Anaconda Python distribution./nThen to get OncodriveFM installed run the following command:/n(env) $pip install oncodrivefm/nAnd that's all. The following command will allow you to check that is correctly installed by showing the command help:/n(env)$ oncodrivefm --help/nusage: oncodrivefm [-h] [-o PATH] [-n NAME] [--output-format FORMAT]/n [-N NUMBER] [-e ESTIMATOR] [--gt THRESHOLD]/n [--pt THRESHOLD] [-s SLICES] [-m PATH] [--save-data]/n [--save-analysis] [-j CORES] [-D KEY=VALUE] [-L LEVEL]/n DATA/nCompute the FM bias for genes and pathways/npositional arguments:/n DATA File containing the data matrix in TDM format/noptional arguments:/n -h, --help show this help message and exit/n -o PATH, --output-path PATH/n Directory where output files will be written/n -n NAME Analysis name/n --output-format FORMAT/n The FORMAT for the output file/n -N NUMBER, --samplings NUMBER/n Number of samplings to compute the FM bias pvalue/n -e ESTIMATOR, --estimator ESTIMATOR/n Test estimator for computation./n --gt THRESHOLD, --gene-threshold THRESHOLD/n Minimum number of mutations per gene to compute the FM/n bias/n --pt THRESHOLD, --pathway-threshold THRESHOLD/n Minimum number of mutations per pathway to compute the/n FM bias/n -s SLICES, --slices SLICES/n Slices to process separated by commas/n -m PATH, --mapping PATH/n File with mappings between genes and pathways to be/n analysed/n --save-data The input data matrix will be saved/n --save-analysis The analysis results will be saved/n -j CORES, --cores CORES/n Number of cores to use for calculations. Default is 0/n that means all the available cores/n -D KEY=VALUE Define external parameters to be saved in the results/n -L LEVEL, --log-level LEVEL/n Define log level: debug, info, warn, error, critical,/n notsetOncodriveFM detects candidate cancer driver genes and pathways from catalogs of somatic mutations in a cohort of tumors by computing the bias towards the accumulation of functional mutations (FM bias).This novel approach avoids some known limitations of recurrence-based approaches, such as the difficulty to estimate background mutation rate, and the fact that they usually fail to identify lowly recurrently mutated driver genes