Rapid automatic assessment of microvascular density in sidestream dark field images

The purpose of this study was to develop a rapid and fully automatic method for the assessment of microvascular density and perfusion in sidestream dark field (SDF) images. We modified algorithms previously developed by our group for microvascular density assessment and introduced a new method for microvascular perfusion assessment. To validate the new algorithm for microvascular density assessment, we reanalyzed a selection of SDF video clips (n = 325) from a study in intensive care patients and compared the results to (semi-)manually found microvascular densities. The method for microvascular perfusion assessment (temporal SDF image contrast analysis, tSICA) was tested in several video simulations and in one high quality SDF video clip where the microcirculation was imaged before and during circulatory arrest in a cardiac surgery patient. We found that the new method for microvascular density assessment was very rapid (<30 s/clip) and correlated excellently with (semi-)manually measured microvascular density. The new method for microvascular perfusion assessment (tSICA) was shown to be limited by high cell densities and velocities, which severely impedes the applicability of this method in real SDF images. Hence, here we present a validated method for rapid and fully automatic assessment of microvascular density in SDF images. The new method was shown to be much faster than the conventional (semi-)manual method. Due to current SDF imaging hardware limitations, we were not able to automatically detect microvascular perfusion

Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy

Abstract: Purpose: Early clinical recognition of sepsis can be challenging. With the advancement of machine learning, promising real-time models to predict sepsis have emerged. We assessed their performance by carrying out a systematic review and meta-analysis. Methods: A systematic search was performed in PubMed, Embase.com and Scopus. Studies targeting sepsis, severe sepsis or septic shock in any hospital setting were eligible for inclusion. The index test was any supervised machine learning model for real-time prediction of these conditions. Quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology, with a tailored Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) checklist to evaluate risk of bias. Models with a reported area under the curve of the receiver operating characteristic (AUROC) metric were meta-analyzed to identify strongest contributors to model performance. Results: After screening, a total of 28 papers were eligible for synthesis, from which 130 models were extracted. The majority of papers were developed in the intensive care unit (ICU, n = 15; 54%), followed by hospital wards (n = 7; 25%), the emergency department (ED, n = 4; 14%) and all of these settings (n = 2; 7%). For the prediction of sepsis, diagnostic test accuracy assessed by the AUROC ranged from 0.68–0.99 in the ICU, to 0.96–0.98 in-hospital and 0.87 to 0.97 in the ED. Varying sepsis definitions limit pooling of the performance across studies. Only three papers clinically implemented models with mixed results. In the multivariate analysis, temperature, lab values, and model type contributed most to model performance. Conclusion: This systematic review and meta-analysis show that on retrospective data, individual machine learning models can accurately predict sepsis onset ahead of time. Although they present alternatives to traditional scoring systems, between-study heterogeneity limits the assessment of pooled results. Systematic reporting and clinical implementation studies are needed to bridge the gap between bytes and bedside

Sex differences in patients with out-of-hospital cardiac arrest without ST-segment elevation:A COACT trial substudy

Background: Whether sex is associated with outcomes of out-of-hospital cardiac arrest (OHCA) is unclear. Objectives: This study examined sex differences in survival in patients with OHCA without ST-segment elevation myocardial infarction (STEMI). Methods: Using data from the randomized controlled Coronary Angiography after Cardiac Arrest (COACT) trial, the primary point of interest was sex differences in OHCA-related one-year survival. Secondary points of interest included the benefit of immediate coronary angiography compared to delayed angiography until after neurologic recovery, angiographic and clinical outcomes. Results: In total, 522 patients (79.1% men) were included. Overall one-year survival was 59.6% in women and 63.4% in men (HR 1.18; 95% CI: 0.761.81;p = 0.47). No cardiovascular risk factors were found that modified survival. Women less often had significant coronary artery disease (CAD) (37.0% vs. 71.3%; p < 0.001), but when present, they had a worse prognosis than women without CAD (HR 3.06; 95% CI 1.31-7.19; p = 0.01). This was not the case for men (HR 1.05; 95% CI 0.67-1.65; p = 0.83). In both sexes, immediate coronary angiography did not improve one-year survival compared to delayed angiography (women, odds ratio (OR) 0.87; 95% CI 0.58-1.30;p = 0.49; vs. men, OR 0.97; 95% CI 0.45-2.09; p = 0.93). Conclusion: In OHCA patients without STEMI, we found no sex differences in overall one-year survival. Women less often had significant CAD, but when CAD was present they had worse survival than women without CAD. This was not the case for men. Both sexes did not benefit from a strategy of immediate coronary angiography as compared to delayed strategy with respect to one-year survival

Data on sex differences in one-year outcomes of out-of-hospital cardiac arrest patients without ST-segment elevation

Sex differences in out-of-hospital cardiac arrest (OHCA) patients are increasingly recognized. Although it has been found that post-resuscitated women are less likely to have significant coronary artery disease (CAD) than men, data on follow-up in these patients are limited. Data for this data in brief article was obtained as a part of the randomized controlled Coronary Angiography after Cardiac Arrest without ST-segment elevation (COACT) trial. The data supplements the manuscript "Sex differences in out-of-hospital cardiac arrest patients without ST-segment elevation: A COACT trial substudy" were it was found that women were less likely to have significant CAD including chronic total occlusions, and had worse survival when CAD was present. The dataset presented in this paper describes sex differences on interventions, implantable-cardioverter defibrillator (ICD) shocks and hospitalizations due to heart failure during one-year follow-up in patients successfully resuscitated after OHCA. Data was derived through a telephone interview at one year with the patient or general practitioner. Patients in this randomized dataset reflects a homogenous study population, which can be valuable to further build on research regarding long-term sex differences and to further improve cardiac care. (C) 2020 The Authors. Published by Elsevier Inc

Coronary Angiography After Cardiac Arrest Without ST Segment Elevation:One-Year Outcomes of the COACT Randomized Clinical Trial

Importance: Ischemic heart disease is a common cause of cardiac arrest. However, randomized data on long-term clinical outcomes of immediate coronary angiography and percutaneous coronary intervention (PCI) in patients successfully resuscitated from cardiac arrest in the absence of ST segment elevation myocardial infarction (STEMI) are lacking. Objective: To determine whether immediate coronary angiography improves clinical outcomes at 1 year in patients after cardiac arrest without signs of STEMI, compared with a delayed coronary angiography strategy. Design, Setting, and Participants: A prespecified analysis of a multicenter, open-label, randomized clinical trial evaluated 552 patients who were enrolled in 19 Dutch centers between January 8, 2015, and July 17, 2018. The study included patients who experienced out-of-hospital cardiac arrest with a shockable rhythm who were successfully resuscitated without signs of STEMI. Follow-up was performed at 1 year. Data were analyzed, using the intention-to-treat principle, between August 29 and October 10, 2019. Interventions: Immediate coronary angiography and PCI if indicated or coronary angiography and PCI if indicated, delayed until after neurologic recovery. Main Outcomes and Measures: Survival, myocardial infarction, revascularization, implantable cardiac defibrillator shock, quality of life, hospitalization for heart failure, and the composite of death or myocardial infarction or revascularization after 1 year. Results: At 1 year, data on 522 of 552 patients (94.6%) were available for analysis. Of these patients, 413 were men (79.1%); mean (SD) age was 65.4 (12.3) years. A total of 162 of 264 patients (61.4%) in the immediate angiography group and 165 of 258 patients (64.0%) in the delayed angiography group were alive (odds ratio, 0.90; 95% CI, 0.63-1.28). The composite end point of death, myocardial infarction, or repeated revascularization since the index hospitalization was met in 112 patients (42.9%) in the immediate group and 104 patients (40.6%) in the delayed group (odds ratio, 1.10; 95% CI, 0.77-1.56). No significant differences between the groups were observed for the other outcomes at 1-year follow-up. For example, the rate of ICD shocks was 20.4% in the immediate group and 16.2% in the delayed group (odds ratio, 1.32; 95% CI, 0.66-2.64). Conclusions and Relevance: In this trial of patients successfully resuscitated after out-of-hospital cardiac arrest and without signs of STEMI, a strategy of immediate angiography was not found to be superior to a strategy of delayed angiography with respect to clinical outcomes at 1 year. Coronary angiography in this patient group can therefore be delayed until after neurologic recovery without affecting outcomes

The Genome of the Netherlands:design, and project goals

Within the Netherlands a national network of biobanks has been established (Biobanking and Biomolecular Research Infrastructure-Netherlands (BBMRI-NL)) as a national node of the European BBMRI. One of the aims of BBMRI-NL is to enrich biobanks with different types of molecular and phenotype data. Here, we describe the Genome of the Netherlands (GoNL), one of the projects within BBMRI-NL. GoNL is a whole-genome-sequencing project in a representative sample consisting of 250 trio-families from all provinces in the Netherlands, which aims to characterize DNA sequence variation in the Dutch population. The parent-offspring trios include adult individuals ranging in age from 19 to 87 years (mean = 53 years; SD = 16 years) from birth cohorts 1910-1994. Sequencing was done on blood-derived DNA from uncultured cells and accomplished coverage was 14-15x. The family-based design represents a unique resource to assess the frequency of regional variants, accurately reconstruct haplotypes by family-based phasing, characterize short indels and complex structural variants, and establish the rate of de novo mutational events. GoNL will also serve as a reference panel for imputation in the available genome-wide association studies in Dutch and other cohorts to refine association signals and uncover population-specific variants. GoNL will create a catalog of human genetic variation in this sample that is uniquely characterized with respect to micro-geographic location and a wide range of phenotypes. The resource will be made available to the research and medical community to guide the interpretation of sequencing projects. The present paper summarizes the global characteristics of the project.</p

Loci influencing blood pressure identified using a cardiovascular gene-centric array

Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped 50 000 single-nucleotide polymorphisms (SNPs) that capture variation in 2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P 2.4 10(6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.</p

WGS-based telomere length analysis in Dutch family trios implicates stronger maternal inheritance and a role for RRM1 gene

Telomere length (TL) regulation is an important factor in ageing, reproduction and cancer development. Genetic, hereditary and environmental factors regulating TL are currently widely investigated, however, their relative contribution to TL variability is still understudied. We have used whole genome sequencing data of 250 family trios from the Genome of the Netherlands project to perform computational measurement of TL and a series of regression and genome-wide association analyses to reveal TL inheritance patterns and associated genetic factors. Our results confirm that TL is a largely heritable trait, primarily with mother’s, and, to a lesser extent, with father’s TL having the strongest influence on the offspring. In this cohort, mother’s, but not father’s age at conception was positively linked to offspring TL. Age-related TL attrition of 40 bp/year had relatively small influence on TL variability. Finally, we have identified TL-associated variations in ribonuclease reductase catalytic subunit M1 (RRM1 gene), which is known to regulate telomere maintenance in yeast. We also highlight the importance of multivariate approach and the limitations of existing tools for the analysis of TL as a polygenic heritable quantitative trait

Large-Scale Gene-Centric Meta-Analysis across 39 Studies Identifies Type 2 Diabetes Loci

To identify genetic factors contributing to type 2 diabetes (T2D), we performed large-scale meta-analyses by using a custom similar to 50,000 SNP genotyping array (the ITMAT-Broad-CARe array) with similar to 2000 candidate genes in 39 multiethnic population-based studies, case-control studies, and clinical trials totaling 17,418 cases and 70,298 controls. First, meta-analysis of 25 studies comprising 14,073 cases and 57,489 controls of European descent confirmed eight established T2D loci at genome-wide significance. In silico follow-up analysis of putative association signals found in independent genome-wide association studies (including 8,130 cases and 38,987 controls) performed by the DIAGRAM consortium identified a T2D locus at genome-wide significance (GATAD2A/CILP2/PBX4; p = 5.7 x 10(-9)) and two loci exceeding study-wide significance (SREBF1, and TH/INS; p <2.4 x 10(-6)). Second, meta-analyses of 1,986 cases and 7,695 controls from eight African-American studies identified study-wide-significant (p = 2.4 x 10(-7)) variants in HMGA2 and replicated variants in TCF7L2 (p = 5.1 x 10(-15)). Third, conditional analysis revealed multiple known and novel independent signals within five T2D-associated genes in samples of European ancestry and within HMGA2 in African-American samples. Fourth, a multiethnic meta-analysis of all 39 studies identified T2D-associated variants in BCL2 (p = 2.1 x 10(-8)). Finally, a composite genetic score of SNPs from new and established T2D signals was significantly associated with increased risk of diabetes in African-American, Hispanic, and Asian populations. In summary, large-scale meta-analysis involving a dense gene-centric approach has uncovered additional loci and variants that contribute to T2D risk and suggests substantial overlap of T2D association signals across multiple ethnic groups