Revisiting left atrial volumetry by magnetic resonance imaging : the role of atrial shape and 3D angle between left ventricular and left atrial axis

Background Accurate measurement of left atrial (LA) volumes is needed in cardiac diagnostics and the follow up of heart and valvular diseases. Geometrical assumptions with 2D methods for LA volume estimation contribute to volume misestimation. In this study, we test agreement of 3D and 2D methods of LA volume detection and explore contribution of 3D LA axis orientation and LA shape in introducing error in 2D methods by cardiovascular magnetic resonance imaging. Methods 30 patients with prior first-ever ischemic stroke and no known heart disease, and 30 healthy controls were enrolled (age 18-49) in a substudy of a prospective case-control study. All study subjects underwent cardiac magnetic resonance imaging and were pooled for this methodological study. LA volumes were calculated by biplane area-length method from both conventional long axis (LAV(AL-LV)) and LA long axis-oriented images (LAV(AL-LA)) and were compared to 3D segmented LA volume (LAV(SAX)) to assess accuracy of volume detection. 3D orientation of LA long axis to left ventricular (LV) long axis and to four-chamber plane were determined, and LA 3D sphericity indices were calculated to assess sources of error in LA volume calculation. Shapiro-Wilk test, Bland-Altman analysis, intraclass and Pearson correlation, and Spearman's rho were used for statistical analysis. Results Biases were - 9.9 mL (- 12.5 to - 7.2) for LAV(AL-LV) and 13.4 (10.0-16.9) for LAV(AL-LA) [mean difference to LAV(SAX) (95% confidence interval)]. End-diastolic LA long axis 3D deviation angle to LV long axis was 28.3 +/- 6.2 degrees [mean +/- SD] and LA long axis 3D rotation angle to four-chamber plane 20.5 +/- 18.0 degrees. 3D orientation of LA axis or 3D sphericity were not correlated to error in LA volume calculation. Conclusions Calculated LA volume accuracy did not improve by using LA long axis-oriented images for volume calculation in comparison to conventional method. We present novel data on LA axis orientation and a novel metric of LA sphericity and conclude that these measures cannot be utilized to assess error in LA volume calculation.Peer reviewe

100 years of atmospheric and marine observations at the Finnish Utö Island in the Baltic Sea

The Utö Atmospheric and Marine Research Station introduced in this paper is located on Utö Island (59°46.84′ N, 21°22.13′ E) at the outer edge of the Archipelago Sea, by the Baltic Sea towards the Baltic Proper. Meteorological observations at the island started in 1881 and vertical profiling of seawater temperature and salinity in 1900. Since 1980, the number of observations at Utö has rapidly increased, with a large number of new meteorological, air quality, aerosol, optical and greenhouse gas parameters, and recently, a variety of marine observations. In this study, we analyze long-term changes of atmospheric temperature, cloudiness, sea salinity, temperature and ice cover. Our main dataset consists of 248 367 atmospheric temperature observations, 1632 quality-assured vertical seawater temperature and salinity profiles and 8565 ice maps, partly digitized for this project. We also use North Atlantic Oscillation (NAO), major Baltic inflow (MBI) and Baltic Sea river runoff data from the literature as reference variables to our data. Our analysis is based on a statistical method utilizing a dynamic linear model. The results show an increase in the atmospheric temperature at Utö, but the increase is significantly smaller than on land areas and has taken place only since the early 1980s, with a rate of 0.4 °C decade−1 during the last 35 years. We also see an increase in seawater temperatures, especially on the surface, with an increase of 0.3 °C decade−1 for the last 100 years. In deeper water layers, the increase is smaller and influenced by vertical mixing, which is modulated by inflow of saline water from the North Sea and freshwater inflow from rivers and by wind-driven processes influenced by the local bathymetry. The date when air temperature in the spring exceeds +5 °C became 5 days earlier from the period 1951–1980 to the period 1981–2010 and the date when sea surface water temperature exceeds +4 °C changed to 9 days earlier. Sea ice cover duration at Utö shows a decrease of approximately 50 % during the last 35 years. Based on the combined results, it is possible that the climate at Utö has changed into a new phase, in which the sea ice no longer reduces the local temperature increase caused by the global warming.</p

Informed consent procedures in patients with an acute inability to provide informed consent : Policy and practice in the CENTER-TBI study

Purpose: Enrolling traumatic brain injury (731) patients with an inability to provide informed consent in research is challenging. Alternatives to patient consent are not sufficiently embedded in European and national legislation, which allows procedural variation and bias. We aimed to quantify variations in informed consent policy and practice. Methods: Variation was explored in the CENTER-TBI study. Policies were reported by using a questionnaire and national legislation. Data on used informed consent procedures were available for 4498 patients from 57 centres across 17 European countries. Results: Variation in the use of informed consent procedures was found between and within EU member states. Proxy informed consent (N = 1377;64%) was the most frequently used type of consent in the ICU, followed by patient informed consent (N 426;20%) and deferred consent (N 334;16%). Deferred consent was only actively used in 15 centres (26%), although it was considered valid in 47 centres (82%). Conclusions: Alternatives to patient consent are essential for TBI research. While there seems to be concordance amongst national legislations, there is regional variability in institutional practices with respect to the use of different informed consent procedures. Variation could be caused by several reasons, including inconsistencies in clear legislation or knowledge of such legislation amongst researchers. (C) 2020 Published by Elsevier Inc.Peer reviewe

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations. (C) 2020 The Authors. Published by Elsevier Inc.Peer reviewe

Nuclear factor E2-related factor 2 deficiency impairs atherosclerotic lesion development but promotes features of plaque instability in hypercholesterolaemic mice

Aims Oxidative stress and inflammation play an important role in the progression of atherosclerosis. Transcription factor NF-E2-related factor 2 (Nrf2) has antioxidant and anti-inflammatory effects in the vessel wall, but paradoxically, global loss of Nrf2 in apoE deficient mice alleviates atherosclerosis. In this study, we investigated the effect of global Nrf2 deficiency on early and advanced atherogenesis in alternative models of atherosclerosis, LDL receptor deficient mice (LDLR-/-), and LDLR-/- mice expressing apoB-100 only (LDLR-/- ApoB(100/100)) having a humanized lipoprotein profile. Methods and results LDLR-/- mice were fed a high-fat diet (HFD) for 6 or 12weeks and LDLR(-/-)ApoB(100/100) mice a regular chow diet for 6 or 12months. Nrf2 deficiency significantly reduced early and more advanced atherosclerosis assessed by lesion size and coverage in the aorta in both models. Nrf2 deficiency in LDLR-/- mice reduced total plasma cholesterol after 6weeks of HFD and triglycerides in LDLR(-/-)ApoB(100/100) mice on a chow diet. Nrf2 deficiency aggravated aortic plaque maturation in aged LDLR(-/-)ApoB(100/100) mice as it increased plaque calcification. Moreover, approximate to 36% of Nrf2(-/-)LDLR(-/-)ApoB(100/100) females developed spontaneous myocardial infarction (MI) or sudden death at 5 to 12months of age. Interestingly, Nrf2 deficiency increased plaque instability index, enhanced plaque inflammation and calcification, and reduced fibrous cap thickness in brachiocephalic arteries of LDLR(-/-)ApoB(100/100) female mice at age of 12months. Conclusions Absence of Nrf2 reduced atherosclerotic lesion size in both atherosclerosis models, likely via systemic effects on lipid metabolism. However, Nrf2 deficiency in aged LDLR(-/-)ApoB(100/100) mice led to an enhanced atherosclerotic plaque instability likely via increased plaque inflammation and oxidative stress, which possibly predisposed to MI and sudden death.Peer reviewe

Functionally informed fine-mapping and polygenic localization of complex trait heritability

Fine-mapping aims to identify causal variants impacting complex traits. We propose PolyFun, a computationally scalable framework to improve fine-mapping accuracy by leveraging functional annotations across the entire genome-not just genome-wide-significant loci-to specify prior probabilities for fine-mapping methods such as SuSiE or FINEMAP. In simulations, PolyFun + SuSiE and PolyFun + FINEMAP were well calibrated and identified >20% more variants with a posterior causal probability >0.95 than identified in their nonfunctionally informed counterparts. In analyses of 49 UK Biobank traits (average n = 318,000), PolyFun + SuSiE identified 3,025 fine-mapped variant-trait pairs with posterior causal probability >0.95, a >32% improvement versus SuSiE. We used posterior mean per-SNP heritabilities from PolyFun + SuSiE to perform polygenic localization, constructing minimal sets of common SNPs causally explaining 50% of common SNP heritability; these sets ranged in size from 28 (hair color) to 3,400 (height) to 2 million (number of children). In conclusion, PolyFun prioritizes variants for functional follow-up and provides insights into complex trait architectures. PolyFun is a computationally scalable framework for functionally informed fine-mapping that makes full use of genome-wide data. It prioritizes more variants than previous methods when applied to 49 complex traits from UK Biobank.Peer reviewe