Abnormal vortex formation in the right pulmonary artery after the arterial switch operation

Cardiovascular Aspects of Radiolog

4D flow cardiovascular magnetic resonance derived energetics in the Fontan circulation correlate with exercise capacity and CMR-derived liver fibrosis/congestion

Aim This study explores the relationship between in vivo 4D flow cardiovascular magnetic resonance (CMR) derived blood flow energetics in the total cavopulmonary connection (TCPC), exercise capacity and CMR-derived liver fibrosis/congestion. Background The Fontan circulation, in which both caval veins are directly connected with the pulmonary arteries (i.e. the TCPC) is the palliative approach for single ventricle patients. Blood flow efficiency in the TCPC has been associated with exercise capacity and liver fibrosis using computational fluid dynamic modelling. 4D flow CMR allows for assessment of in vivo blood flow energetics, including kinetic energy (KE) and viscous energy loss rate (EL). Methods Fontan patients were prospectively evaluated between 2018 and 2021 using a comprehensive cardiovascular and liver CMR protocol, including 4D flow imaging of the TCPC. Peak oxygen consumption (VO2) was determined using cardiopulmonary exercise testing (CPET). Iron-corrected whole liver T1 (cT1) mapping was performed as a marker of liver fibrosis/congestion. KE and EL in the TCPC were computed from 4D flow CMR and normalized for inflow. Furthermore, blood flow energetics were compared between standardized segments of the TCPC. Results Sixty-two Fontan patients were included (53% male, 17.3 +/- 5.1 years). Maximal effort CPET was obtained in 50 patients (peak VO2 27.1 +/- 6.2 ml/kg/min, 56 +/- 12% of predicted). Both KE and EL in the entire TCPC (n = 28) were significantly correlated with cT1 (r = 0.50, p = 0.006 and r = 0.39, p = 0.04, respectively), peak VO2 (r = - 0.61, p = 0.003 and r = - 0.54, p = 0.009, respectively) and % predicted peak VO2 (r = - 0.44, p = 0.04 and r = - 0.46, p = 0.03, respectively). Segmental analysis indicated that the most adverse flow energetics were found in the Fontan tunnel and left pulmonary artery. Conclusions Adverse 4D flow CMR derived KE and EL in the TCPC correlate with decreased exercise capacity and increased levels of liver fibrosis/congestion. 4D flow CMR is promising as a non-invasive screening tool for identification of patients with adverse TCPC flow efficiency.Cardiovascular Aspects of Radiolog

Reduced scan time and superior image quality with 3D flow MRI compared to 4D flow MRI for hemodynamic evaluation of the Fontan pathway

Long scan times prohibit a widespread clinical applicability of 4D flow MRI in Fontan patients. As pulsatility in the Fontan pathway is minimal during the cardiac cycle, acquiring non-ECG gated 3D flow MRI may result in a reduction of scan time while accurately obtaining time-averaged clinical parameters in comparison with 2D and 4D flow MRI. Thirty-two Fontan patients prospectively underwent 2D (reference), 3D and 4D flow MRI of the Fontan pathway. Multiple clinical parameters were assessed from time-averaged flow rates, including the right-to-left pulmonary flow distribution (main endpoint) and systemic-to-pulmonary collateral flow (SPCF). A ten-fold reduction in scan time was achieved [4D flow 15.9 min (SD 2.7 min) and 3D flow 1.6 min (SD 7.8 s), p<0.001] with a superior signal-to-noise ratio [mean ratio of SNRs 1.7 (0.8), p<0.001] and vessel sharpness [mean ratio 1.2 (0.4), p=0.01] with 3D flow. Compared to 2D flow, good-excellent agreement was shown for mean flow rates (ICC 0.82-0.96) and right-to-left pulmonary flow distribution (ICC 0.97). SPCF derived from 3D flow showed good agreement with that from 4D flow (ICC 0.86). 3D flow MRI allows for obtaining time-averaged flow rates and derived clinical parameters in the Fontan pathway with good-excellent agreement with 2D and 4D flow, but with a tenfold reduction in scan time and significantly improved image quality compared to 4D flow.Developmen

Dutch Oncology COVID-19 consortium:Outcome of COVID-19 in patients with cancer in a nationwide cohort study

Aim of the study: Patients with cancer might have an increased risk for severe outcome of coronavirus disease 2019 (COVID-19). To identify risk factors associated with a worse outcome of COVID-19, a nationwide registry was developed for patients with cancer and COVID-19. Methods: This observational cohort study has been designed as a quality of care registry and is executed by the Dutch Oncology COVID-19 Consortium (DOCC), a nationwide collaboration of oncology physicians in the Netherlands. A questionnaire has been developed to collect pseudonymised patient data on patients' characteristics, cancer diagnosis and treatment. All patients with COVID-19 and a cancer diagnosis or treatment in the past 5 years are eligible. Results: Between March 27th and May 4th, 442 patients were registered. For this first analysis, 351 patients were included of whom 114 patients died. In multivariable analyses, age ≥65 years (p < 0.001), male gender (p = 0.035), prior or other malignancy (p = 0.045) and active diagnosis of haematological malignancy (p = 0.046) or lung cancer (p = 0.003) were independent risk factors for a fatal outcome of COVID-19. In a subgroup analysis of patients with active malignancy, the risk for a fatal outcome was mainly determined by tumour type (haematological malignancy or lung cancer) and age (≥65 years). Conclusion: The findings in this registry indicate that patients with a haematological malignancy or lung cancer have an increased risk of a worse outcome of COVID-19. During the ongoing COVID-19 pandemic, these vulnerable patients should avoid exposure to severe acute respiratory syndrome coronavirus 2, whereas treatment adjustments and prioritising vaccination, when available, should also be considered

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

Percutaneous Pulmonary Valve Implantation: Current Status and Future Perspectives

Item does not contain fulltextPatients with congenital heart disease (CHD) with right ventricle outflow tract (RVOT) dysfunction need sequential pulmonary valve replacements throughout their life in the majority of cases. Since their introduction in 2000, the number of percutaneous pulmonary valve implantations (PPVI) has grown and reached over 10,000 procedures worldwide. Overall, PPVI has been proven safe and effective, but some anatomical variations can limit procedural success. This review discusses the current status and future perspectives of the procedure

Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data

Background: Internet cognitive behavioural therapy (iCBT) is a viable delivery format of CBT for depression. However, iCBT programmes include training in a wide array of cognitive and behavioural skills via different delivery methods, and it remains unclear which of these components are more efficacious and for whom. Methods: We did a systematic review and individual participant data component network meta-analysis (cNMA) of iCBT trials for depression. We searched PubMed, PsycINFO, Embase, and the Cochrane Library for randomised controlled trials (RCTs) published from database inception to Jan 1, 2019, that compared any form of iCBT against another or a control condition in the acute treatment of adults (aged ≥18 years) with depression. Studies with inpatients or patients with bipolar depression were excluded. We sought individual participant data from the original authors. When these data were unavailable, we used aggregate data. Two independent researchers identified the included components. The primary outcome was depression severity, expressed as incremental mean difference (iMD) in the Patient Health Questionnaire-9 (PHQ-9) scores when a component is added to a treatment. We developed a web app that estimates relative efficacies between any two combinations of components, given baseline patient characteristics. This study is registered in PROSPERO, CRD42018104683. Findings: We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42·0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD −1·83 [95% credible interval (CrI) −2·90 to −0·80]) and that relaxation might be harmful (1·20 [95% CrI 0·17 to 2·27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduced dropouts from treatment (incremental odds ratio, 0·32 [95% CrI 0·13 to 0·93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. Interpretation: The individual patient data cNMA revealed potentially helpful, less helpful, or harmful components and delivery formats for iCBT packages. iCBT packages aiming to be effective and efficient might choose to include beneficial components and exclude ones that are potentially detrimental. Our web app can facilitate shared decision making by therapist and patient in choosing their preferred iCBT package. Funding: Japan Society for the Promotion of Science

Dismantling, optimising, and personalising internet cognitive behavioural therapy for depression: a systematic review and component network meta-analysis using individual participant data

Background: Internet cognitive behavioural therapy (iCBT) is a viable delivery format of CBT for depression. However, iCBT programmes include training in a wide array of cognitive and behavioural skills via different delivery methods, and it remains unclear which of these components are more efficacious and for whom. Methods: We did a systematic review and individual participant data component network meta-analysis (cNMA) of iCBT trials for depression. We searched PubMed, PsycINFO, Embase, and the Cochrane Library for randomised controlled trials (RCTs) published from database inception to Jan 1, 2019, that compared any form of iCBT against another or a control condition in the acute treatment of adults (aged ≥18 years) with depression. Studies with inpatients or patients with bipolar depression were excluded. We sought individual participant data from the original authors. When these data were unavailable, we used aggregate data. Two independent researchers identified the included components. The primary outcome was depression severity, expressed as incremental mean difference (iMD) in the Patient Health Questionnaire-9 (PHQ-9) scores when a component is added to a treatment. We developed a web app that estimates relative efficacies between any two combinations of components, given baseline patient characteristics. This study is registered in PROSPERO, CRD42018104683. Findings: We identified 76 RCTs, including 48 trials contributing individual participant data (11 704 participants) and 28 trials with aggregate data (6474 participants). The participants' weighted mean age was 42·0 years and 12 406 (71%) of 17 521 reported were women. There was suggestive evidence that behavioural activation might be beneficial (iMD −1·83 [95% credible interval (CrI) −2·90 to −0·80]) and that relaxation might be harmful (1·20 [95% CrI 0·17 to 2·27]). Baseline severity emerged as the strongest prognostic factor for endpoint depression. Combining human and automated encouragement reduced dropouts from treatment (incremental odds ratio, 0·32 [95% CrI 0·13 to 0·93]). The risk of bias was low for the randomisation process, missing outcome data, or selection of reported results in most of the included studies, uncertain for deviation from intended interventions, and high for measurement of outcomes. There was moderate to high heterogeneity among the studies and their components. Interpretation: The individual patient data cNMA revealed potentially helpful, less helpful, or harmful components and delivery formats for iCBT packages. iCBT packages aiming to be effective and efficient might choose to include beneficial components and exclude ones that are potentially detrimental. Our web app can facilitate shared decision making by therapist and patient in choosing their preferred iCBT package. Funding: Japan Society for the Promotion of Science

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

Altres ajuts: Department of Health and Social Care (DHSC); Illumina; LifeArc; Medical Research Council (MRC); UKRI; Sepsis Research (the Fiona Elizabeth Agnew Trust); the Intensive Care Society, Wellcome Trust Senior Research Fellowship (223164/Z/21/Z); BBSRC Institute Program Support Grant to the Roslin Institute (BBS/E/D/20002172, BBS/E/D/10002070, BBS/E/D/30002275); UKRI grants (MC_PC_20004, MC_PC_19025, MC_PC_1905, MRNO2995X/1); UK Research and Innovation (MC_PC_20029); the Wellcome PhD training fellowship for clinicians (204979/Z/16/Z); the Edinburgh Clinical Academic Track (ECAT) programme; the National Institute for Health Research, the Wellcome Trust; the MRC; Cancer Research UK; the DHSC; NHS England; the Smilow family; the National Center for Advancing Translational Sciences of the National Institutes of Health (CTSA award number UL1TR001878); the Perelman School of Medicine at the University of Pennsylvania; National Institute on Aging (NIA U01AG009740); the National Institute on Aging (RC2 AG036495, RC4 AG039029); the Common Fund of the Office of the Director of the National Institutes of Health; NCI; NHGRI; NHLBI; NIDA; NIMH; NINDS.Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care or hospitalization 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