Individual and combined effects of chemical and mechanical power on postoperative pulmonary complications: a secondary analysis of the REPEAT study

Introduction: Intra-operative supplemental oxygen and mechanical ventilation expose the lungs to potentially injurious energy. This can be quantified as 'chemical power' and 'mechanical power', respectively. In this study, we sought to determine if intra-operative chemical and mechanical power, individually and/or in combination, are associated with postoperative pulmonary complications. Methods: Using an individual patient data analysis of three randomised clinical trials of intra-operative ventilation, we summarised intra-operative chemical and mechanical power using time-weighted averages. We evaluated the association between intra-operative chemical and mechanical power and a collapsed composite of postoperative pulmonary complications using multivariable logistic regression to estimate the odds ratios related to the effect of 1 J.min-1 increase in chemical or mechanical power with adjustment for demographic and intra-operative characteristics. We also included an interaction term to assess for potential synergistic effects of chemical and mechanical power on postoperative pulmonary complications. Results: Of 3837 patients recruited to three individual trials, 2492 with full datasets were included in the analysis. Intra-operative time-weighted average (SD) chemical power was 10.2 (3.9) J.min-1 and mechanical power was 10.5 (4.4) J.min-1. An increase of 1 J.min-1 in chemical power was associated with 8% higher odds of postoperative pulmonary complications (OR 1.08, 95%CI 1.05-1.10, p < 0.001), while the same increase in mechanical power raised odds by 5% (OR 1.05, 95%CI 1.02-1.08, p = 0.003). We did not find evidence of a significant interaction between chemical and mechanical power (p = 0.40), suggestive of an additive rather than synergistic effect on postoperative pulmonary complications. Discussion: Both chemical and mechanical power are independently associated with postoperative pulmonary complications. Further work is required to determine causality

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Genetic mechanisms of critical illness in Covid-19.

Host-mediated lung inflammation is present,1 and drives mortality,2 in critical illness caused by Covid-19. Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development.3 Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study(GWAS) in 2244 critically ill Covid-19 patients from 208 UK intensive care units (ICUs). We identify and replicate novel genome-wide significant associations, on chr12q24.13 (rs10735079, p=1.65 [Formula: see text] 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), on chr19p13.2 (rs2109069, p=2.3 [Formula: see text] 10-12) near the gene encoding tyrosine kinase 2 (TYK2), on chr19p13.3 (rs2109069, p=3.98 [Formula: see text] 10-12) within the gene encoding dipeptidyl peptidase 9 (DPP9), and on chr21q22.1 (rs2236757, p=4.99 [Formula: see text] 10-8) in the interferon receptor gene IFNAR2. We identify potential targets for repurposing of licensed medications: using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease; transcriptome-wide association in lung tissue revealed that high expression of the monocyte/macrophage chemotactic receptor CCR2 is associated with severe Covid-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Best anaesthetic drug strategy for morbidly obese patients

Purpose of review: The purpose of this review is to describe an evidence-based drug strategy applicable to any obese patient, rather than to present one standard ideal' anaesthetic drug combination. The ultimate choice of specific drugs in any given situation will depend upon clinician experience, patient specifics, and drug availability. The fundamental principle in anaesthesia for the obese patient is to use the shortest acting, least fat soluble agents to ensure rapid recovery to safe levels of alertness and mobility. Recent findings: No new drugs have been introduced over the past few years, but we have seen an introduction of enhanced recovery after surgery-based protocols into bariatric surgery. Our understanding of how obesity affects pharmacokinetics/dynamics of our drugs is improving, with new and better use of established drugs. Allometric scaling is being tested in the different pharmacokinetic/dynamic models used in target controlled infusion devices, with improved performance as a result. Obstructive sleep apnoea has a significant impact upon outcome and utilization of clinical resources, including critical care beds. If an improved drug dosing strategy will reduce this impact, then this would be a step forward. Summary: This review introduces newer findings to help us use anaesthetic and analgesic drugs more safely in the morbidly obese. However, there remain many areas of uncertainty with a lack of consensus on many issues