Sonia Yeh is professor of transport and energy systems at Chalmers University of Technology in Sweden and a globally recognized expert on the decarbonization of transport and energy systems. Her research spans energy economics, alternative fuels, mobility behavior, and sustainability policy. She has advised US federal and state agencies, as well as international governments and organizations, on climate strategies and system transitions. Dr. Yeh is a contributing author to the IPCC Sixth Assessment Report, a senior editor of Energy Policy, and recipient of the Ha & ring;kan Frisinger Award from the Volvo Research and Educational Foundations. Sergey Paltsev is deputy director of the Massachusetts Institute of Technology (MIT) Center for Sustainability Science and Strategy and senior research scientist at MIT Energy Initiative . He oversees the MIT Economic Projection and Policy Analysis (EPPA) model of the world economy. Dr. Paltsev is an author of more than 140 peer-reviewed publications in scientific journals and books on energy economics, climate policy, transport, advanced energy technologies, and international trade. Sergey is a recipient of the 2012 Pyke Johnson Award from the Transportation Research Board of the National Academies USA for the best paper in planning and environment. John Reilly is a senior lecturer at the Sloan School of Management at the MIT and a contributor to the Center for Sustainability Science and Strategy at MIT. His research focuses on the economics of energy, environment, and climate change and the interactions between human and natural earth systems. David Daniels is a senior researcher at the Swedish National Road and Transport Research Institute (VTI), where he conducts analyses at the intersection of transport electrification, energy system dynamics, and infrastructure resilience. His recent work focuses on energy transport integration in shipping and aviation, such as ports and airports as energy hubs. He previously served as chief energy modeler at the US Energy Information Administration and developed quantitative terrorism risk methods for the US Department of Homeland Security. Pedro Linares is professor of industrial engineering at Comillas Pontifical University-ICAI and affiliate researcher at the MIT CEEPR and the University of Cambridge EPRG. His research focuses on the assessment of energy, climate, transport, and industrial policies and the development of energy and economic models. He has been a consultant for several private and public firms and institutions in Spain, Europe, and Latin America.

Climate change, income and population growth, and changing diets are major drivers of the global food system with implications for land use change. Land use in the U.S. will be affected directly by local and regional forces and indirectly through international trade. In order to investigate the effects of several potential forces on land use changes in the U.S., we advanced capabilities in representing the interactions between natural and human systems by linking a multisectoral and multiregional socio‐economic model of the world economy to a model that downscales land use to a 0.5°grid scale. This enables us to translate regional projections of future land use into higher‐resolution representations of time‐evolving land cover (effectively spatially explicit land use transitions). We applied the framework over the U.S., with a particular interest in the Mississippi River Basin and its four sub‐basins, to consider how a range of global drivers affect land use and cover in the target regions. Our results show that under scenarios of high pressure on the world food system a comparative advantage in livestock production amplifies the recent trend toward less cropland and more pastures in the U.S. Under low pressures on the world food system agricultural land is used less intensively. However, there can be key differences among the various land‐use transitions at the sub‐ basin scale. Overall, these results highlighted the need for high resolution details to explicitly understand the implications of land use change on environmental impacts such as carbon storage, soil erosion, chemical use, hydrology, and water quality.

Information about the likelihood of various outcomes is needed to inform discussions about climate mitigation and adaptation. Here we provide integrated, probabilistic socio-economic and climate projections, using estimates of probability distributions for key parameters in both human and Earth system components of a coupled model. We find that policy lowers the upper tail of temperature change more than the median. We also find that while human system uncertainties dominate uncertainty of radiative forcing, Earth system uncertainties contribute more than twice as much to temperature uncertainty in scenarios without fixed emissions paths, reflecting the uncertainty of translating radiative forcing into temperature. The combination of human and Earth system uncertainty is less than additive, illustrating the value of integrated modeling. Further, we find that policy costs are more uncertain in low- and middle-income economies, and that renewables are robust investments across a wide range of policies and socio-economic uncertainties.

Consideration of different potential emissions futures is essential for understanding and preparing for future climate change. This chapter briefly reviews the contribution of socioeconomic scenario uncertainty to overall climate change uncertainty. It then addresses the key drivers of emissions of greenhouse gases and other pollutants and how uncertainty in those drivers affects projections of future emissions. It then reviews the history of emissions and concentration scenarios and various approaches that have been taken, including the traditional scenario development approach of the Intergovernmental Panel on Climate Change (IPCC) as well as formal uncertainty analysis techniques and methods that can connect probability distributions back to individual scenarios of interest. The chapter closes with lessons learned from more than 40 years of socioeconomic effort to create scenarios to support climate change research.

Assessments of the aggregate impacts of climate change on the global economy are widely varying and diverge depending on the method employed. It is essential to understand the mechanisms behind the differing estimates and identify a robust range. Only then could these estimates meaningfully inform and guide climate actions.

Rationale: The epidemiology, management, and outcomes of acute respiratory distress syndrome (ARDS) differ between children and adults, with lower mortality rates in children despite comparable severity of hypoxemia. However, the relationship between age and mortality is unclear.Objective: We aimed to define the association between age and mortality in ARDS, hypothesizing that it would be nonlinear.Methods: We performed a retrospective cohort study using data from two pediatric ARDS observational cohorts (n = 1,236), multiple adult ARDS trials (n = 5,547), and an adult observational ARDS cohort (n = 1,079). We aligned all datasets to meet Berlin criteria. We performed unadjusted and adjusted logistic regression using fractional polynomials to assess the potentially nonlinear relationship between age and 90-day mortality, adjusting for sex, PaO2/FiO2, immunosuppressed status, year of study, and observational versus randomized controlled trial, treating each individual study as a fixed effect.Measurements and Main Results: There were 7,862 subjects with median ages of 4 years in the pediatric cohorts, 52 years in the adult trials, and 61 years in the adult observational cohort. Most subjects (43%) had moderate ARDS by Berlin criteria. Ninety-day mortality was 19% in the pediatric cohorts, 33% in the adult trials, and 67% in the adult observational cohort. We found a nonlinear relationship between age and mortality, with mortality risk increasing at an accelerating rate between 11 and 65 years of age, after which mortality risk increased more slowly.Conclusions: There was a nonlinear relationship between age and mortality in pediatric and adult ARDS.

Agricultural soils play a dual role in regulating the Earth's climate by releasing or sequestering carbon dioxide (CO2) in soil organic carbon (SOC) and emitting non-CO2 greenhouse gases (GHGs) such as nitrous oxide (N2O) and methane (CH4). To understand how agricultural soils can play a role in climate solutions requires a comprehensive assessment of net soil GHG balance (i.e., sum of SOC-sequestered CO2 and non-CO2 GHG emissions) and the underlying controls. Herein, we used a model-data integration approach to understand and quantify how natural and anthropogenic factors have affected the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960-2018. Specifically, we used the dynamic land ecosystem model for regional simulations and used field observations of SOC sequestration rates and N2O and CH4 emissions to calibrate, validate, and corroborate model simulations. Results show that U.S. agricultural soils sequestered 13.2 +/- 1.16 Tg CO2-C year(-1) in SOC (at a depth of 3.5 m) during 1960-2018 and emitted 0.39 +/- 0.02 Tg N2O-N year(-1) and 0.21 +/- 0.01 Tg CH4-C year(-1), respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was 122.3 +/- 11.46 Tg CO2-eq year(-1), with the largest contribution from N2O emissions. The sequestered SOC offset similar to 28% of the climate-warming effects resulting from non-CO2 GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960-2018, explaining similar to 47% of total changes. In contrast, reduced cropland area, the adoption of agricultural conservation practices (e.g., reduced tillage), and rising atmospheric CO2 levels attenuated net GHG emissions from U.S. croplands. Improving management practices to mitigate N2O emissions represents the biggest opportunity for achieving net-zero emissions in U.S. croplands. Our study highlights the importance of concurrently quantifying SOC-sequestered CO2 and non-CO2 GHG emissions for developing effective agricultural climate change mitigation measures.

Future configurations of the power system in the central region of the USA are dependent on relative costs of alternative power generation technologies, energy and environmental policies, and multiple climate-induced stresses. Higher demand in the summer months combined with compounding supply shocks in several power generation technologies can potentially cause a “perfect storm” leading to failure of the power system. Potential future climate stress must be incorporated in investment decisions and energy system planning and operation. We assess how projected future climate impacts on the power system would affect alternative pathways for the electricity sector considering a broad range of generation technologies and changes in demand. We calculate a “potential supply gap” metric for each pathway, system component, and sub-region of the US Heartland due to climate-induced effects on electricity demand and power generation. Potential supply gaps range from 5% in the North Central region under mild changes in climate to 21% in the Lakes-Mid Atlantic region under more severe climate change. We find increases in electricity demand to be more important in determining the size of the potential supply gap than stresses on power generation, while larger shares of renewables in the power system contribute to lower supply gaps. Our results provide a first step toward considering systemic climate impacts that may require changes in managing the grid or on potential additional capacity/reserves that may be needed.

It is well recognized that natural land is of great importance, and measures of the value of natural lands are required when making data-driven policy decisions between land development and land preservation. One of the most important values of natural land areas is the recreational services provided. In this study, we estimate the recreation use value provided by the natural land in New England. Specifically, we apply the travel cost method to calculate the total consumer surplus for hunting, fishing, and wildlife-watching in the New England region. We also investigate whether and how people from households of different demographic backgrounds have different recreational habits. Using data from the National Survey of Fishing, Hunting, & Wildlife-Associated Recreation, we found that New England natural lands provide a remarkable amount of recreation use value—$88 billion per year to U.S. citizens who partake in wildlife-related activities. Our estimates can serve as input for economic projection and policy analysis models and allow more equitable and appropriate data-driven policy decisions.

BACKGROUND:Primary graft dysfunction (PGD) contributes substantially to both short- and long-term mortality after lung transplantation, but the mechanisms that lead to PGD are not well understood. Exposure to ambient air pollutants is associated with adverse events during waitlisting for lung transplantation and chronic lung allograft dysfunction, but its association with PGD has not been studied. We hypothesized that long-term exposure of the lung donor and recipient to high levels of ambient air pollutants would increase the risk of PGD in lung transplant recipients. METHODS:Using data from 1428 lung transplant recipients and their donors enrolled in the Lung Transplant Outcomes Group observational cohort study, we evaluated the association between the development of PGD and zip-code-based estimates of long-term exposure to 6 major air pollutants (ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, particulate matter 2.5, and particulate matter 10) in both the lung donor and the lung recipient. Exposure estimates used daily EPA air pollutant monitoring data and were based on the geographic centroid of each subject's residential zip code. Associations were tested in both univariable and multivariable models controlling for known PGD risk factors. RESULTS:We did not find strong associations between air pollutant exposures in either the donor or the recipient and PGD. CONCLUSIONS:Exposure to ambient air pollutants, at the levels observed in this study, may not be sufficiently harmful to prime the donor lung or the recipient to develop PGD, particularly when considering the robust associations with other established PGD risk factors.

The open-source fully-automated Surface Energy Balance Algorithm for Land-Improved (SEBALI) Google Earth Engine (SEBALIGEE) estimates 30-m actual evapotranspiration (ET) at a monthly rate, a much needed parameter in many hydrological and agricultural applications. An improved version of the basin-based SEBALIGEE v1 is proposed in this paper. The improvement of SEBALIGEE v1, designated as v2, focuses primarily on incorporating advanced machine learning approaches which have enabled for the first time to implement SEBALIGEE over any scale application and enhance its overall performance. More particularly, an evaluation of the monthly ET estimated from the new algorithm across several fluxnet sites in the US, China, Italy, Belgium, Germany, and France, yielded a Mean Absolute Error (MAE) of 12.22 mm/month versus 14.54 mm/month in the original SEBALIGEE v1. Furthermore, we applied the new any-scale capability of SEBALIGEE v2 over the contiguous United States (CONUS) while emphasizing on the three main crops, including corn, soybeans and winter wheat. Our analysis indicated that all three crops presented two similar ET seasonal cycles with peaks occurring in late spring to the summer (May-Aug) and between October and January, corresponding well to the key stages of crop life cycle. Moreover, corn and soybeans exhibited similar magnitudes of ET (36 - 168 mm/month) and higher than winter wheat (33 - 122 mm/month), with large standard deviations observed in the ET estimates amogst all the crops. On interannual comparisons, the corn and soybeans ET and aKc showed higher values than winter wheat, with the highest and lowest years identified and discussed. Following an exploratory analysis against some of the most common interfering variables such as air temperature, dewpoint temperature, surface net solar radiation, wind speed, SPEI drought index calculated on 14 days and 30-days, it was noted that the surface net solar radiation had the most influencing factor on ET in corn and soybeans plantations with R2 values of -0.72. The SPEI-30 stands out for winter wheat, showing a water scarcity tolerance up to a month in most of its developing stages. Different management practices are then recommended in each of these two crops' categories (corn and soybeans vs. winter wheat).

Climate change mitigation efforts, which require the transition away from carbon-intensive activities, can pose financial risks for owners of fossil fuel assets and investors that the finance companies are engaged in greenhouse gas-emitting activities. For instance, fossil fuel extraction may be significantly scaled-back, and coal-power plants may be idled or even phased out prematurely, thus becoming stranded assets for the shareholders. Using a global general equilibrium model with detailed energy sector and capital stock structures, we estimate the corresponding stranded assets under various emissions mitigation scenarios. Our findings reveal that, depending on the policy scenario, the global net present value of unrealized fossil fuel output through 2050 relative to a “no policy” scenario is between 21.5 and 30.6 trillion USD, and that of stranded assets in coal power generation is between 1.3 and 2.3 trillion USD. The analytical framework presented in our study complements existing research, in which macroeconomic variables required for estimating the stranded assets are often derived from models with more simplified assumptions. Therefore, individual firms and financial institutions can combine our economy-wide analysis with details on their own investment portfolios to determine their climate-related transition risk exposure.

About 140 countries have announced or are considering net zero targets. To explore the implications of such targets, we apply an integrated earth system–economic model to investigate illustrative net zero emissions scenarios. Given the technologies as characterized in our modeling framework, we find that with net zero targets afforestation in earlier years and biomass energy with carbon capture and storage (BECCS) technology in later years are important negative emissions technologies, allowing continued emissions from hard-to-reduce sectors and sources. With the entire world achieving net zero by 2050 a very rapid scale-up of BECCS is required, increasing mitigation costs through mid-century substantially, compared with a scenario where some countries achieve net zero by 2050 while others continue some emissions in the latter half of the century. The scenarios slightly overshoot 1.5 ∘ C at mid-century but are at or below 1.5 ∘ C by 2100 with median climate response. Accounting for climate uncertainty, global achievement of net zero by 2050 essentially guarantees that the 1.5 ∘ C target will be achieved, compared to having a 50–50 chance in the scenario without net zero. This indicates a tradeoff between policy costs and likelihood of achieving 1.5 ∘ C.

The article evaluates the optimum economic hourly dispatch in hydro-thermal systems with massive integration of variable renewable energy, wind and solar. A linear optimization model, Elemod, makes feasible to analyze the power system operation with hourly time step, taking into account one year of planning horizon much larger than the weekly horizon that usually sets the hydro-thermal scheduling studies. It is proposed an alternative formulation for pumped-hydro storage, in a way that the total annual system cost is minimized with the co-optimization of the hourly PHS operation cost. To illustrate the methodology and modeling application, pre-senting a real system analysis, the Brazilian Hydro-thermal System was chosen to be simulated based on its planned capacity stepping into 2029. At the end, the paper shows the ability of PHS system to provide hourly capacity to the power system, as well as better allocate VRE generation and manage the bulk of transmission system usage. The cost reduction could be about 14 Million R$ of the total operation cost estimated for the 2029-power system capacity.

Acute respiratory failure relies on supportive care using non-invasive and invasive oxygen and ventilatory support. Pharmacologic therapies for the most severe form of respiratory failure, acute respiratory distress syndrome (ARDS), are limited. This review focuses on the most promising therapies for ARDS, targeting different mechanisms that contribute to dysregulated inflammation and resultant hypoxemia. Significant heterogeneity exists within the ARDS population. Treatment requires prompt recognition of ARDS and an understanding of which patients may benefit most from specific pharmacologic interventions. The key to finding effective pharmacotherapies for ARDS may rely on deeper understanding of pathophysiology and bedside identification of ARDS subphenotypes.

Exposures to ambient air pollutants may prime the lung enhancing risk of acute respiratory distress syndrome (ARDS) in sepsis. Our objective was to determine the association of short-, medium-, and long-term pollutant exposures and ARDS risk in critically ill sepsis patients. We analyzed a prospective cohort of 1858 critically ill patients with sepsis, and estimated short- (3 days), medium- (6 weeks), and long- (5 years) term exposures to ozone, nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), particulate matter < 2.5 μm (PM2.5), and PM < 10 μm (PM10) using weighted averages of daily levels from monitors within 50 km of subjects’ residences. Subjects were followed for 6 days for ARDS by the Berlin Criteria. The association between each pollutant and ARDS was determined using multivariable logistic regression adjusting for preselected confounders. In 764 subjects, we measured plasma concentrations of inflammatory proteins at presentation and tested for an association between pollutant exposure and protein concentration via linear regression. ARDS developed in 754 (41

Climate policies that target greenhouse gas emissions can improve air quality by reducing co-emitted air pollutant emissions. However, the extent to which climate policy could contribute to the targets of reducing existing pollution disparities across different populations remains largely unknown. We quantify potential air pollution exposure reductions under U.S. federal carbon policy, considering implications of resulting health benefits for exposure disparities across U.S. racial/ethnic groups. We focus on policy cases that achieve reductions of 40-60% in 2030 economy-wide carbon dioxide (CO 2 ) emissions, when compared with 2005 emissions. The 50% CO 2 reduction policy case reduces average fine particulate matter (PM 2.5 ) exposure across racial/ethnic groups, with greatest benefit for non-Hispanic Black (−0.44 μg/m 3 ) and white populations (−0.37 μg/m 3 ). The average exposure disparity for racial/ethnic minorities rises from 12.4% to 13.1%. Applying an optimization approach to multiple emissions reduction scenarios, we find that no alternate combination of reductions from different CO 2 sources would substantially mitigate exposure disparities. Results suggest that CO 2 -based strategies for this range of reductions are insufficient for fully mitigating PM 2.5 exposure disparities between white and racial/ethnic minority populations; addressing disparities may require larger-scale structural changes.

The Cooling to Help Injured Lungs (CHILL) trial is an open label, two group, parallel design multicenter, randomized phase IIB clinical trial assessing the efficacy and safety of targeted temperature management with combined external cooling and neuromuscular blockade to block shivering in patients with early moderate-severe acute respiratory distress syndrome (ARDS). This report provides the background and rationale for the clinical trial and outlines the methods using the Consolidated Standards of Reporting Trials guidelines. Key design challenges include: [1] protocolizing important co-interventions; [2] incorporation of patients with COVID-19 as the cause of ARDS; [3] inability to blind the investigators; and [4] ability to obtain timely informed consent from patients or legally authorized representatives early in the disease process. Results of the Reevaluation of Systemic Early Neuromuscular Blockade (ROSE) trial informed the decision to mandate sedation and neuromuscular blockade only in the group assigned to therapeutic hypothermia and proceed without this mandate in the control group assigned to a usual temperature management protocol. Previous trials conducted in National Heart, Lung, and Blood Institute ARDS Clinical Trials (ARDSNet) and Prevention and Early Treatment of Acute Lung Injury (PETAL) Networks informed ventilator management, ventilation liberation and fluid management protocols. Since ARDS due to COVID-19 is a common cause of ARDS during pandemic surges and shares many features with ARDS from other causes, patients with ARDS due to COVID-19 are included. Finally, a stepwise approach to obtaining informed consent prior to documenting critical hypoxemia was adopted to facilitate enrollment and reduce the number of candidates excluded because eligibility time window expiration.

The COVID-19 pandemic, resulting from SARS-CoV-2, has led to millions of deaths globally and substantial morbidity.1Anesi G.L. Jablonski J. Harhay M.O. et al.Characteristics, outcomes, and trends of patients with COVID-19-related critical illness at a learning health system in the United States.Ann Internal Med. 2021; 174: 613-621Crossref PubMed Scopus (77) Google Scholar COVID-19 has heterogeneous severity, with symptoms ranging from mild fever and cough to ARDS, multisystem organ failure, and death. Genome-wide association studies have identified genetic variants that may explain some of this variability, including the variation that determines ABO histo-blood type.2Ellinghaus D. Degenhardt F. et al.The Severe Covid-19 GWAS GroupGenomewide association study of severe Covid-19 with respiratory failure.N Engl J Med. 2020; 383: 1522-1534Crossref PubMed Scopus (1233) Google Scholar The ABO gene encodes glycosyltransferases responsible for carbohydrate modifications on glycoproteins and has been linked to risk of several vascular diseases,3Stowell S.R. Stowell C.P. Biologic roles of the ABH and Lewis histo-blood group antigens part II: thrombosis, cardiovascular disease and metabolism.Vox Sang. 2019; 114: 535-552Crossref PubMed Scopus (38) Google Scholar as well as plasma concentrations of coagulopathic proteins, particularly von Willebrand factor (vWF).4Morelli V.M. de Visser M.C. van Tilburg N.H. et al.ABO blood group genotypes, plasma von Willebrand factor levels and loading of von Willebrand factor with A and B antigens.Thromb Haemost. 2007; 97: 534-541Crossref PubMed Scopus (68) Google Scholar In ambulatory individuals, ABO blood type explains 30% of the variability of plasma vWF concentration. Excess release of vWF from injured endothelium and a relative deficiency of A disintegrin and metalloprotease with thrombospondin 1 repeats, number 13 (ADAMTS13), the enzyme responsible for cleaving vWF into less thrombogenic multimers, have been implicated in severe COVID-19.5Mancini I. Baronciani L. Artoni A. et al.The ADAMTS13-von Willebrand factor axis in COVID-19 patients.J Thromb Haemost. 2021; 19: 513-521Abstract Full Text Full Text PDF PubMed Scopus (138) Google Scholar ABO antigens are located on the vWF glycoprotein, and the A antigen interferes with ADAMTS13 binding, reducing vWF cleavage, possibly explaining the associations between ABO blood type, vWF, and COVID-19.6Bowen D.J. An influence of ABO blood group on the rate of proteolysis of von Willebrand factor by ADAMTS13.J Thromb Haemost. 2003; 1: 33-40Abstract Full Text Full Text PDF PubMed Scopus (154) Google Scholar Clinically and genetically determined ABO blood type A previously was associated with increased vWF levels, ARDS risk, and disseminated intravascular coagulation risk in critically ill patients without COVID-19.7Reilly J.P. Meyer N.J. Shashaty M.G. et al.The ABO histo-blood group, endothelial activation, and acute respiratory distress syndrome risk in critical illness.J Clin Invest. 2021; 131: e139700Crossref PubMed Scopus (20) Google Scholar Significant hypercoagulability and endothelial dysfunction are frequent characteristics of severe COVID-19.8Ackermann M. Verleden S.E. Kuehnel M. et al.Pulmonary vascular endothelialitis, thrombosis, and angiogenesis in Covid-19.N Engl J Med. 2020; 383: 120-128Crossref PubMed Scopus (3693) Google Scholar We therefore hypothesized that ABO blood type and the ratio of plasma vWF to ADAMTS13 concentrations would associate with COVID-19 outcomes and that measuring the three markers together could identify a population at high risk of poor outcomes for whom drugs targeting the vWF axis may be beneficial. We conducted a prospective cohort study of 215 patients admitted to one of two affiliated hospitals with a primary diagnosis of COVID-19 and followed their clinical status through 28 days. Thirty-seven additional patients screened did not have ABO blood type measured nor plasma collected and were excluded. The study was approved by the institutional review board and informed consent was obtained. We collected plasma samples within 48 h of admission and analyzed them with the multiplex Olink Proximity Extension Assay, which included semiquantitative measurements for vWF and ADAMTS13 concentration. Concentrations were expressed as normalized protein expression values based on the relative concentration compared with pooled healthy control plasma. Normalized protein expression values are arbitrary units on the log2 scale, and therefore, a 1-point normalized protein expression difference corresponds to a doubling of protein concentration. Clinical data, including ABO blood type, were extracted from the medical record. The primary outcome was 28-day mortality, and the secondary outcome was a simplified World Health Organization COVID-19 ordinal severity score at 28 days. We tested the unadjusted associations of ABO blood type and vWF to ADAMTS13 ratio with mortality using the χ2 test and rank-sum test, respectively, and the unadjusted associations with severity score using the nonparametric test for trend. We then constructed multivariable logistic regression models adjusting for age, sex, race, and active malignancy to determine the association of ABO blood type and vWF to ADAMTS13 ratio with mortality. We used these models to estimate standardized risks of death across values of the vWF to ADAMTS13 ratio by ABO blood type. Statistical analyses were conducted using STATA version 16.1 software (StataCorp). Of 215 patients enrolled, the median age was 61 years (interquartile range, 49-71 years), 112 patients (52%) were male, 143 patients (67%) were Black, 61 patients (28%) were White, 10 patients (5%) were Asian, race was unknown for 1 patient (1%), and 14 patients (7%) were Hispanic. An active malignancy was present in 21 patients (10%). ABO blood type was available for 191 patients (89%), and plasma was assayed in 165 patients (78%). At 28 days, 29 patients (13%) had died. Mortality ranged from 10% among patients with blood type O to 22% in patients with blood type A (P = 0.039, unadjusted). Table 1 provides blood type, vWF levels, and ADAMTS13 levels by ordinal 28-day outcome. In multivariable models, blood type A was associated with a higher 28-day mortality relative to blood type O (OR, 3.25; 95% CI, 1.08-9.77; P = .036), and vWF to ADAMTS13 ratio also was associated with 28-day mortality (OR, 1.81; 95% CI, 1.08-3.04 per 1-SD increase; P = .024). We did not detect an interaction in the association of vWF to ADAMTS13 ratio and mortality by blood type. Figure 1 shows standardized risks of death across vWF to ADAMTS13 ratios stratified by blood types A and O, demonstrating that mortality was higher as the ratio increased, but that blood type A shifted the curve toward higher mortality.Table 1Association of ABO Histo-Blood Type, Plasma vWF Levels, Plasma ADAMTS13 Levels, and Plasma vWF to ADAMTS13 Ratio With Outcome at 28 Days After Hospitalization With COVID-19Ordinal OutcomeNo.aIn total, 215 patients with COVID-19 were enrolled and followed up to determine 28-day outcome. ABO blood type was available for 191 patients and was missing in 24 patients.ABO Blood Type, %Plasma ProteinsbPlasma proteins are expressed as median normalized protein expression value (interquartile range), arbitrary units expressed on the log2 scale, whereby a 1-point difference means a doubling of protein concentration.A (n = 58)O (n = 82)B (n = 37)AB (n = 14)vWFADAMTS13vWF to ADAMTS13 RatiocThe vWF to ADAMTS13 ratio was calculated by dividing the raw vWF normalized protein expression value by the raw ADAMTS13 normalized protein expression values. These values are expressed on the log2 scale.Death2922%10%11%21%10.0 (9.1-10.9)5.82 (5.56-6.03)1.67 (1.57-1.88)Mechanically ventilated2116%9%11%7%10.8 (10.0-11.2)5.82 (5.73-6.61)1.72 (1.62-1.93)Hospitalized, requiring oxygen103%5%5%14%10.1 (9.9-11.4)6.15 (5.86-6.38)1.65 (1.58-1.90)Discharged15559%77%73%57%9.7 (8.7-10.4)5.97 (5.85-6.11)1.57 (1.46-1.72)P value. . ..010dComparison of blood type A with type O using the nonparametric test for trend across the ordinal outcome categories.< .001eFrom the nonparametric test for trend across the ordinal outcome categories..025eFrom the nonparametric test for trend across the ordinal outcome categories.< .001eFrom the nonparametric test for trend across the ordinal outcome categories.ADAMTS13 = A disintegrin and metalloprotease with thrombospondin 1 repeats, number 13; vWF = von Willebrand factor.a In total, 215 patients with COVID-19 were enrolled and followed up to determine 28-day outcome. ABO blood type was available for 191 patients and was missing in 24 patients.b Plasma proteins are expressed as median normalized protein expression value (interquartile range), arbitrary units expressed on the log2 scale, whereby a 1-point difference means a doubling of protein concentration.c The vWF to ADAMTS13 ratio was calculated by dividing the raw vWF normalized protein expression value by the raw ADAMTS13 normalized protein expression values. These values are expressed on the log2 scale.d Comparison of blood type A with type O using the nonparametric test for trend across the ordinal outcome categories.e From the nonparametric test for trend across the ordinal outcome categories. Open table in a new tab ADAMTS13 = A disintegrin and metalloprotease with thrombospondin 1 repeats, number 13; vWF = von Willebrand factor. We identified associations among ABO blood type A, higher plasma vWF, and lower ADAMTS13 with higher 28-day mortality and worse outcome in a large population of patients with COVID-19.9Turecek P.L. Peck R.C. Rangarajan S. et al.Recombinant ADAMTS13 reduces abnormally up-regulated von Willebrand factor in plasma from patients with severe COVID-19.Thromb Res. 2021; 201: 100-112Abstract Full Text Full Text PDF PubMed Scopus (35) Google Scholar Additionally, we measured these three markers in a single population and integrated the distinct measurements of vWF biological features to generate standardized mortality curves based on dysregulation of the vWF axis, a novel aspect of our findings. vWF is an essential component of vascular homeostasis. In the setting of severe inflammation and endothelial dysfunction, however, vWF can lead to excess coagulation, organ injury, and death. Our study further suggests that disruption of the relative plasma vWF to ADAMTS13 concentration may contribute to the pathogenesis of severe COVID-19, may be modified by ABO blood type, and may be an important therapeutic target. Severe deficiencies of ADAMTS13 lead to the life-threatening disorder thrombotic thrombocytopenic purpura. Similar to our findings in COVID-19, more moderate ADAMTS13 deficiency and vWF excess are common in sepsis and are relevant to the coagulopathy of sepsis.10Levi M. Scully M. Singer M. The role of ADAMTS-13 in the coagulopathy of sepsis.J Thromb Haemost. 2018; 16: 646-651Abstract Full Text Full Text PDF PubMed Scopus (63) Google Scholar Recombinant ADAMTS13, a drug in development for thrombotic thrombocytopenic purpura, also may be a potential therapeutic for select patients with severe COVID-19 and sepsis of other infectious causes. In an exploratory study, incubation of plasma samples from patients with severe COVID-19 with recombinant ADAMTS13 substantially reduced abnormality high vWF clotting activity.9Turecek P.L. Peck R.C. Rangarajan S. et al.Recombinant ADAMTS13 reduces abnormally up-regulated von Willebrand factor in plasma from patients with severe COVID-19.Thromb Res. 2021; 201: 100-112Abstract Full Text Full Text PDF PubMed Scopus (35) Google Scholar We hypothesize that three major pathways contribute to excess activation of the vWF axis in COVID-19: excess vWF release, plasma ADAMTS13 deficiency, and impaired cleavage of vWF multimers by ADAMTS13 resulting from the presence of A antigens. Future studies of therapeutics aimed at the vWF axis, such as recombinant ADAMTS13, should consider evaluating for heterogeneity of treatment effect by ABO blood type and plasma vWF to ADAMTS13 ratio early in severe COVID-19. Our study has limitations including its small sample size at a two-hospital center, lack of differentiation between genetic blood type A subtypes, lack of measurements of enzymatic activity, and the semiquantitative nature of our measurements; however, we believe our study provides key preliminary data to support a potential role of the vWF to ADAMTS13 axis for prognostic and predictive enrichment for future clinical trials of targeted therapeutics. J. P. R., N. J. M., and M. G. S. S. are funded by the National Institutes of Health [Grants R01-HL155159; R01-HL137006, R01-HL137915, and K24-HL155804; and R01-DK111638, respectively].