Nutritional Status and Physical Exercise Are Associated with Cognitive Function in Chinese Community-Dwelling Older Adults: The Role of Happiness.

We aim to assess the relationship between nutrition status, physical exercise, and cognitive function and particularly examine how happiness modifies and mediates the relationship, among 699 seniors aged 60 and above in Shanghai, China. Linear regression models were used to validate the effects of nutrition and exercise on cognitive function and to test their interaction effects with happiness. When the interactions were significant, stratified analyses in sub-groups were conducted. Mediation effects of happiness were examined using two-step causal mediation models. We confirmed that better nutrition (p < 0.001) and exercise (p = 0.009) were significantly associated with less cognitive decline. Furthermore, the effects of nutrition and exercise on cognitive decline were significant in the unhappy (happiness < 20) (p < 0.001) and younger (age < 74) sub-groups (p = 0.015). Happiness partially mediated 11.5% of the negative association of cognitive decline with nutrition (p = 0.015) and 23.0% of that with exercise (p = 0.017). This study suggests that happiness moderates and partially mediates the effects of exercise and nutrition on cognitive status. The beneficial effects of exercise and nutrition were stronger in less happy or younger seniors. Future intervention studies are required to confirm this path relationship.

SuPAR, biomarkers of inflammation, and severe outcomes in patients hospitalized for COVID-19: The International Study of Inflammation in COVID-19.

Severe coronavirus disease 2019 (COVID-19) is a hyperinflammatory syndrome. The biomarkers of inflammation best suited to triage patients with COVID-19 are unknown. We conducted a prospective multicenter observational study of adult patients hospitalized specifically for COVID-19 from February 1, 2020 to October 19, 2022. Biomarkers measured included soluble urokinase plasminogen activator receptor (suPAR), C-reactive protein, interleukin-6, procalcitonin, ferritin, and D-dimer. In-hospital outcomes examined include death and the need for mechanical ventilation. Patients admitted in the United States (US, n = 1962) were used to compute area under the curves (AUCs) and identify biomarker cutoffs. The combined European cohorts (n = 1137) were used to validate the biomarker cutoffs. In the US cohort, 356 patients met the composite outcome of death (n = 197) or need for mechanical ventilation (n = 290). SuPAR was the most important predictor of the composite outcome and had the highest AUC (0.712) followed by CRP (0.642), ferritin (0.619), IL-6 (0.614), D-dimer (0.606), and lastly procalcitonin (0.596). Inclusion of other biomarkers did not improve discrimination. A suPAR cutoff of 4.0 ng/mL demonstrated a sensitivity of 95.4% (95% CI: 92.4%-98.0%) and negative predictive value (NPV) of 92.5% (95% CI: 87.5%-96.9%) for the composite outcome. Patients with suPAR < 4.0 ng/mL comprised 10.6% of the cohort and had a 0.8% probability of the composite outcome. Applying this cutoff to the validation cohort yielded a sensitivity of 93.8% (90.4%-96.7%) and NPV of 95.5% (93.1%-97.8%) for the composite outcome. Among commonly measured biomarkers, suPAR offered stronger discriminatory ability and may be useful in triaging low-risk patients with COVID-19.

Cardiovascular Risk Stratification of Patients Undergoing Hematopoietic Stem Cell Transplantation: The CARE-BMT Risk Score.

BACKGROUND: Evidence guiding the pre-hematopoietic stem cell transplantation (HSCT) cardiovascular evaluation is limited. We sought to derive and validate a pre-HSCT score for the cardiovascular risk stratification of HSCT candidates. METHODS AND RESULTS: We leveraged the CARE-BMT (Cardiovascular Registry in Bone Marrow Transplantation) study, a contemporary multicenter observational study of adult patients who underwent autologous or allogeneic HSCT between 2008 and 2019 (N=2435; mean age at transplant of 55 years; 4.9% Black). We identified the subset of variables most predictive of post-HSCT cardiovascular events, defined as a composite of cardiovascular death, myocardial infarction, heart failure, stroke, atrial fibrillation or flutter, and sustained ventricular tachycardia. We then developed a point-based risk score using the hazard ratios obtained from Cox proportional hazards modeling. The score was externally validated in a separate cohort of 919 HSCT recipients (mean age at transplant 54 years; 20.4% Black). The risk score included age, transplant type, race, coronary artery disease, heart failure, peripheral artery disease, creatinine, triglycerides, and prior anthracycline dose. Risk scores were grouped as low-, intermediate-, and high-risk, with the 5-year cumulative incidence of cardiovascular events being 4.0%, 10.3%, and 22.4%, respectively. The area under the receiver operating curves for predicting cardiovascular events at 100 days, 5 and 10 years post-HSCT were 0.65 (95% CI, 0.59-0.70), 0.73 (95% CI, 0.69-0.76), and 0.76 (95% CI, 0.69-0.81), respectively. The model performed equally well in autologous and allogeneic recipients, as well as in the validation cohort. CONCLUSIONS: The CARE-BMT risk score is easy to calculate and could help guide referrals of high-risk HSCT recipients to cardiovascular specialists before transplant and guide long-term monitoring.

Malnutrition in heart failure with preserved ejection fraction.

BACKGROUND: Malnutrition may be an important geriatric condition in adults with heart failure with preserved ejection fraction (HFpEF), but studies on its prevalence and associated clinical outcomes are limited. The aim of this study was to determine if malnutrition is associated with short-term morbidity and mortality in ambulatory patients with HFpEF. METHODS: We examined 231 patients with a clinical diagnosis of HFpEF seen at two dedicated academic HFpEF programs (Weill Cornell Medicine and Michigan Medicine) from June 2018 to April 2022. Malnutrition was defined by Mini-Nutritional Assessment Short Form (MNA-SF) scores ≤11. The primary endpoint was a 6-month composite of all-cause mortality and all-cause hospitalization. A Cox proportional-hazard models was used to examine the association between malnutrition and the primary endpoint, adjusting for race, prior hospitalization history, and the validated Meta-Analysis Global Group in Chronic (MAGGIC) heart failure prognostic risk score. RESULTS: The median age of the cohort was 73 years (interquartile range 64-81). The most common comorbid conditions included hypertension (prevalence 81%), atrial fibrillation (43%), and obesity (63%). The prevalence of malnutrition was 42% (n = 97), and MNA-SF scores did not significantly correlate with body mass index (R = -0.02, p = 0.71). At the 6-month follow-up, 62 patients (26.8%) were hospitalized and four patients died (1.7%). In a fully-adjusted analysis, malnutrition was independently associated with the composite outcome of all-cause mortality and all-cause hospitalization (HR 1.94 [95% CI: 1.17-3.20], p = 0.01). CONCLUSION: Despite a high prevalence of obesity, two out of five ambulatory adults with HFpEF are malnourished. Malnutrition was independently associated with adverse outcomes at 6 months. Future work is necessary to develop interventions that can address malnutrition.

BondGraphs.jl: composable energy-based modelling in systems biology.

SUMMARY: BondGraphs.jl is a Julia implementation of bond graphs. Bond graphs provide a modelling framework that describes energy flow through a physical system and by construction enforce thermodynamic constraints. The framework is widely used in engineering and has recently been shown to be a powerful approach for modelling biology. Models are mutable, hierarchical, multiscale, and multiphysics, and BondGraphs.jl is compatible with the Julia modelling ecosystem. AVAILABILITY AND IMPLEMENTATION: BondGraphs.jl is freely available under the MIT license. Source code and documentation can be found at https://github.com/jedforrest/BondGraphs.jl.

Sensitivity analysis of biochemical systems using bond graphs.

The sensitivity of systems biology models to parameter variation can give insights into which parameters are most important for physiological function, and also direct efforts to estimate parameters. However, in general, kinetic models of biochemical systems do not remain thermodynamically consistent after perturbing parameters. To address this issue, we analyse the sensitivity of biological reaction networks in the context of a bond graph representation. We find that the parameter sensitivities can themselves be represented as bond graph components, mirroring potential mechanisms for controlling biochemistry. In particular, a sensitivity system is derived which re-expresses parameter variation as additional system inputs. The sensitivity system is then linearized with respect to these new inputs to derive a linear system which can be used to give local sensitivity to parameters in terms of linear system properties such as gain and time constant. This linear system can also be used to find so-called sloppy parameters in biological models. We verify our approach using a model of the Pentose Phosphate Pathway, confirming the reactions and metabolites most essential to maintaining the function of the pathway.

Direct Thermal Growth of Gold Nanopearls on 3D Interweaved Hydrophobic Fibers as Ultrasensitive Portable SERS Substrates for Clinical Applications.

Surface-enhanced Raman spectroscopy (SERS)-based biosensors have attracted much attention for their label-free detection, ultrahigh sensitivity, and unique molecular fingerprinting. In this study, a wafer-scale, ultrasensitive, highly uniform, paper-based, portable SERS detection platform featuring abundant and dense gold nanopearls with narrow gap distances, are prepared and deposited directly onto ultralow-surface-energy fluorosilane-modified cellulose fibers through simple thermal evaporation by delicately manipulating the atom diffusion behavior. The as-designed paper-based SERS substrate exhibits an extremely high Raman enhancement factor (3.9 × 1011 ), detectability at sub-femtomolar concentrations (single-molecule level) and great signal reproductivity (relative standard deviation: 3.97%), even when operated with a portable 785-nm Raman spectrometer. This system is used for fingerprinting identification of 12 diverse analytes, including clinical medicines (cefazolin, chloramphenicol, levetiracetam, nicotine), pesticides (thiram, paraquat, carbaryl, chlorpyrifos), environmental carcinogens (benzo[a]pyrene, benzo[g,h,i]perylene), and illegal drugs (methamphetamine, mephedrone). The lowest detection concentrations reach the sub-ppb level, highlighted by a low of 16.2 ppq for nicotine. This system appears suitable for clinical applications in, for example, i) therapeutic drug monitoring for individualized medication adjustment and ii) ultra-early diagnosis for pesticide intoxication. Accordingly, such scalable, portable and ultrasensitive fibrous SERS substrates open up new opportunities for practical on-site detection in biofluid analysis, point-of-care diagnostics and precision medicine.

Functional outcomes after prostate cancer treatment: A comparison between single and multiple modalities.

Prostate cancer is a widely common and treatable disease, and functional outcomes can greatly affect survivor quality of life. A retrospective review of the SEER-Medicare database was performed to identify patients who underwent prostate cancer treatment between January 1, 2004 and December 31, 2013 and review the rates of diagnosis and treatment of common functional side effects of surgery, radiation, or a combination of the 2 and perform a comparison of the outcomes. A total of 67,527 patients were included in the analysis. Radiation therapy (RT)-only compared to radical prostatectomy (RP)-only had lower rates of diagnosis of erectile dysfunction (30.4%, 95% CI 29.9%-30.9% vs. 56.1%, 95% CI 55.1%-57.04%, P < 0.0001), UI (29.7%, 95% CI 29.0%-30.3% vs. 44.5%, 95% CI 43.3%-45.6%, P < 0.0001), but higher rates of urethral stricture disease (8.44%, 95% CI 8.1%-8.8% vs. 5.35%, 95% CI 4.9%-5.9%, P < 0.0001), cystitis (33.1% 95% CI 32.4%-33.7% vs. 20.3%, 95% CI 19.2%-21.4%, P < 0.0001), and proctitis (14.7%, 95% CI 14.3%-15.1& vs. 2.75%, 95% CI 2.3%-3.3%, P < 0.0001). Compared to either single modality, the RP-then-RT group had higher incontinence medication use (12.0% 95% CI 10.8%-13.2% vs. 9.8%, 95% CI 9.5%-10.1% for RT-only and 8.3%, 95% CI 7.8%-8.8% for RP-only, P < 0.0001), overall incontinence therapy (18.5%, 95%CI 17.1%-20.0% vs. 10.2%, 95%CI 9.9%-10.5% for RT-only and 14.9%, 95% CI 14.3%-15.5% for RP-only, P < 0.0001), and stricture therapy (12.7%, 95% CI 11.5%-13.9% vs. 8.2%, 95% CI 8.0%-8.5% for RT-only and 9.1% 95% CI 8.6%-9.6% for RP-only, P < 0.0001). The RT-then-RP group had higher rates of stricture (25.4% compared to 8.2% for RT-only, 9.1% for RP-only, and 12.7% for RP-then-RT) and fistula (1.0% compared to 0.07% for RT-only, 0.18% for RP-only, and 0.092% for RP-then-RT) treatment than all the other groups. Multimodality therapy is generally associated with higher treatments rates for conditions such as erectile dysfunction , incontinence, urethral stricture disease , irritative cystitis and proctitis in patients older than 65. Radiation therapy followed by prostatectomy is associated with significantly worse functional outcomes. Patients undergoing or anticipating undergoing multimodality therapy for prostate cancer should be counseled regarding the possibility of increased risk of declining functional outcomes.

Cardiovascular Events After Hematopoietic Stem Cell Transplant: Incidence and Risk Factors.

Background: Hematopoietic stem cell transplantation (HSCT) is associated with various cardiovascular (CV) complications. Objectives: We sought to characterize the incidence and risk factors for short-term and long-term CV events in a contemporary cohort of adult HSCT recipients. Methods: We conducted a multicenter observational study of adult patients who underwent autologous or allogeneic HSCT between 2008 and 2019. Data on demographics, clinical characteristics, conditioning regimen, and CV outcomes were collected through chart review. CV outcomes were a composite of CV death, myocardial infarction, heart failure, atrial fibrillation/flutter, stroke, and sustained ventricular tachycardia and were classified as short-term (≤100 days post-HSCT) or long-term (>100 days post-HSCT). Results: In 3,354 patients (mean age 55 years; 40.9% female; 30.1% Black) followed for a median time of 2.3 years (Q1-Q3: 1.0-5.4 years), the 100-day and 5-year cumulative incidences of CV events were 4.1% and 13.9%, respectively. Atrial fibrillation/flutter was the most common short- and long-term CV event, with a 100-day incidence of 2.6% and a 5-year incidence of 6.8% followed by heart failure (1.1% at 100 days and 5.4% at 5 years). Allogeneic recipients had a higher incidence of long-term CV events compared to autologous recipients (5-year incidence 16.4% vs 12.1%; P = 0.002). Baseline CV comorbidities were associated with a higher risk of long-term CV events. Conclusions: The incidence of short-term CV events in HSCT recipients is relatively low. Long-term events were more common among allogeneic recipients and those with pre-existing CV comorbidities.

Relationship Between Preexisting Cardiovascular Disease and Death and Cardiovascular Outcomes in Critically Ill Patients With COVID-19.

BACKGROUND: Preexisting cardiovascular disease (CVD) is perceived as a risk factor for poor outcomes in patients with COVID-19. We sought to determine whether CVD is associated with in-hospital death and cardiovascular events in critically ill patients with COVID-19. METHODS: This study used data from a multicenter cohort of adults with laboratory-confirmed COVID-19 admitted to intensive care units at 68 centers across the United States from March 1 to July 1, 2020. The primary exposure was CVD, defined as preexisting coronary artery disease, congestive heart failure, or atrial fibrillation/flutter. Myocardial injury on intensive care unit admission defined as a troponin I or T level above the 99th percentile upper reference limit of normal was a secondary exposure. The primary outcome was 28-day in-hospital mortality. Secondary outcomes included cardiovascular events (cardiac arrest, new-onset arrhythmias, new-onset heart failure, myocarditis, pericarditis, or stroke) within 14 days. RESULTS: Among 5133 patients (3231 male [62.9%]; mean age 61 years [SD, 15]), 1174 (22.9%) had preexisting CVD. A total of 1178 (34.6%) died, and 920 (17.9%) had a cardiovascular event. After adjusting for age, sex, race, body mass index, history of smoking, and comorbidities, preexisting CVD was associated with a 1.15 (95% CI, 0.98-1.34) higher odds of death. No independent association was observed between preexisting CVD and cardiovascular events. Myocardial injury on intensive care unit admission was associated with higher odds of death (adjusted odds ratio, 1.93 [95% CI, 1.61-2.31]) and cardiovascular events (adjusted odds ratio, 1.82 [95% CI, 1.47-2.24]), regardless of the presence of CVD. CONCLUSIONS: CVD risk factors, rather than CVD itself, were the major contributors to outcomes in critically ill patients with COVID-19. The occurrence of myocardial injury, regardless of CVD, and its association with outcomes suggests it is likely due to multiorgan injury related to acute inflammation rather than exacerbation of preexisting CVD. REGISTRATION: NCT04343898; https://clinicaltrials.gov/ct2/show/NCT04343898.

Network thermodynamics of biological systems: A bond graph approach.

Edmund Crampin (1973-2021) was at the forefront of Systems Biology research and his work will influence the field for years to come. This paper brings together and summarises the seminal work of his group in applying energy-based bond graph methods to biological systems. In particular, this paper: (a) motivates the need to consider energy in modelling biology; (b) introduces bond graphs as a methodology for achieving this; (c) describes extensions to modelling electrochemical transduction; (d) outlines how bond graph models can be constructed in a modular manner and (e) describes stoichiometric approaches to deriving fundamental properties of reaction networks. These concepts are illustrated using a new bond graph model of photosynthesis in chloroplasts.

SBML to bond graphs: From conversion to composition.

The Systems Biology Markup Language (SBML) is a popular software-independent XML-based format for describing models of biological phenomena. The BioModels Database is the largest online repository of SBML models. Several tools and platforms are available to support the reuse and composition of SBML models. However, these tools do not explicitly assess whether models are physically plausible or thermodynamically consistent. This often leads to ill-posed models that are physically impossible, impeding the development of realistic complex models in biology. Here, we present a framework that can automatically convert SBML models into bond graphs, which imposes energy conservation laws on these models. The new bond graph models are easily mergeable, resulting in physically plausible coupled models. We illustrate this by automatically converting and coupling a model of pyruvate distribution to a model of the pentose phosphate pathway.

Soluble Urokinase Plasminogen Activator Receptor and Venous Thromboembolism in COVID-19.

Background Venous thromboembolism (VTE) contributes significantly to COVID-19 morbidity and mortality. The urokinase receptor system is involved in the regulation of coagulation. Levels of soluble urokinase plasminogen activator receptor (suPAR) reflect hyperinflammation and are strongly predictive of outcomes in COVID-19. Whether suPAR levels identify patients with COVID-19 at risk for VTE is unclear. Methods and Results We leveraged a multinational observational study of patients hospitalized for COVID-19 with suPAR and D-dimer levels measured on admission. In 1960 patients (mean age, 58 years; 57% men; 20% Black race), we assessed the association between suPAR and incident VTE (defined as pulmonary embolism or deep vein thrombosis) using logistic regression and Fine-Gray modeling, accounting for the competing risk of death. VTE occurred in 163 (8%) patients and was associated with higher suPAR and D-dimer levels. There was a positive association between suPAR and D-dimer (ß=7.34; P=0.002). Adjusted for clinical covariables, including D-dimer, the odds of VTE were 168% higher comparing the third with first suPAR tertiles (adjusted odds ratio, 2.68 [95% CI, 1.51-4.75]; P<0.001). Findings were consistent when stratified by D-dimer levels and in survival analysis accounting for death as a competing risk. On the basis of predicted probabilities from random forest, a decision tree found the combined D-dimer <1 mg/L and suPAR <11 ng/mL cutoffs, identifying 41% of patients with only 3.6% VTE probability. Conclusions Higher suPAR was associated with incident VTE independently of D-dimer in patients hospitalized for COVID-19. Combining suPAR and D-dimer identified patients at low VTE risk. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04818866.

A semantics, energy-based approach to automate biomodel composition.

Hierarchical modelling is essential to achieving complex, large-scale models. However, not all modelling schemes support hierarchical composition, and correctly mapping points of connection between models requires comprehensive knowledge of each model's components and assumptions. To address these challenges in integrating biosimulation models, we propose an approach to automatically and confidently compose biosimulation models. The approach uses bond graphs to combine aspects of physical and thermodynamics-based modelling with biological semantics. We improved on existing approaches by using semantic annotations to automate the recognition of common components. The approach is illustrated by coupling a model of the Ras-MAPK cascade to a model of the upstream activation of EGFR. Through this methodology, we aim to assist researchers and modellers in readily having access to more comprehensive biological systems models.

The Cell Physiome: What Do We Need in a Computational Physiology Framework for Predicting Single-Cell Biology?

Modern biology and biomedicine are undergoing a big data explosion, needing advanced computational algorithms to extract mechanistic insights on the physiological state of living cells. We present the motivation for the Cell Physiome Project: a framework and approach for creating, sharing, and using biophysics-based computational models of single-cell physiology. Using examples in calcium signaling, bioenergetics, and endosomal trafficking, we highlight the need for spatially detailed, biophysics-based computational models to uncover new mechanisms underlying cell biology. We review progress and challenges to date toward creating cell physiome models. We then introduce bond graphs as an efficient way to create cell physiome models that integrate chemical, mechanical, electromagnetic, and thermal processes while maintaining mass and energy balance. Bond graphs enhance modularization and reusability of computational models of cells at scale. We conclude with a look forward at steps that will help fully realize this exciting new field of mechanistic biomedical data science.

A red fluorescent protein with improved monomericity enables ratiometric voltage imaging with ASAP3.

A ratiometric genetically encoded voltage indicator (GEVI) would be desirable for tracking transmembrane voltage changes in the presence of sample motion. We performed combinatorial multi-site mutagenesis on a cyan-excitable red fluorescent protein to create the bright and monomeric mCyRFP3, which proved to be uniquely non-perturbing when fused to the GEVI ASAP3. The green/red ratio from ASAP3-mCyRFP3 (ASAP3-R3) reported voltage while correcting for motion artifacts, allowing the visualization of membrane voltage changes in contracting cardiomyocytes and throughout the cell cycle of motile cells.

Engineered bacterial voltage-gated sodium channel platform for cardiac gene therapy.

Therapies for cardiac arrhythmias could greatly benefit from approaches to enhance electrical excitability and action potential conduction in the heart by stably overexpressing mammalian voltage-gated sodium channels. However, the large size of these channels precludes their incorporation into therapeutic viral vectors. Here, we report a platform utilizing small-size, codon-optimized engineered prokaryotic sodium channels (BacNav) driven by muscle-specific promoters that significantly enhance excitability and conduction in rat and human cardiomyocytes in vitro and adult cardiac tissues from multiple species in silico. We also show that the expression of BacNav significantly reduces occurrence of conduction block and reentrant arrhythmias in fibrotic cardiac cultures. Moreover, functional BacNav channels are stably expressed in healthy mouse hearts six weeks following intravenous injection of self-complementary adeno-associated virus (scAAV) without causing any adverse effects on cardiac electrophysiology. The large diversity of prokaryotic sodium channels and experimental-computational platform reported in this study should facilitate the development and evaluation of BacNav-based gene therapies for cardiac conduction disorders.

Inflammation, Hyperglycemia, and Adverse Outcomes in Individuals With Diabetes Mellitus Hospitalized for COVID-19.

OBJECTIVE: Diabetes mellitus (DM) is a major risk factor for severe coronavirus disease 2019 (COVID-19) for reasons that are unclear. RESEARCH DESIGN AND METHODS: We leveraged the International Study of Inflammation in COVID-19 (ISIC), a multicenter observational study of 2,044 patients hospitalized with COVID-19, to characterize the impact of DM on in-hospital outcomes and assess the contribution of inflammation and hyperglycemia to the risk attributed to DM. We measured biomarkers of inflammation collected at hospital admission and collected glucose levels and insulin data throughout hospitalization. The primary outcome was the composite of in-hospital death, need for mechanical ventilation, and need for renal replacement therapy. RESULTS: Among participants (mean age 60 years, 58.2% males), those with DM (n = 686, 33.5%) had a significantly higher cumulative incidence of the primary outcome (37.8% vs. 28.6%) and higher levels of inflammatory biomarkers than those without DM. Among biomarkers, DM was only associated with higher soluble urokinase plasminogen activator receptor (suPAR) levels in multivariable analysis. Adjusting for suPAR levels abrogated the association between DM and the primary outcome (adjusted odds ratio 1.23 [95% CI 0.78, 1.37]). In mediation analysis, we estimated the proportion of the effect of DM on the primary outcome mediated by suPAR at 84.2%. Hyperglycemia and higher insulin doses were independent predictors of the primary outcome, with effect sizes unaffected by adjusting for suPAR levels. CONCLUSIONS: Our findings suggest that the association between DM and outcomes in COVID-19 is largely mediated by hyperinflammation as assessed by suPAR levels, while the impact of hyperglycemia is independent of inflammation.

Differences in Inflammation, Treatment, and Outcomes Between Black and Non-Black Patients Hospitalized for COVID-19: A Prospective Cohort Study.

PURPOSE: Racial disparities in coronavirus disease 2019 (COVID-19) outcomes have been described. We sought to determine whether differences in inflammatory markers, use of COVID-19 therapies, enrollment in clinical trials, and in-hospital outcomes contribute to racial disparities between Black and non-Black patients hospitalized for COVID-19. METHODS: We leveraged a prospective cohort study that enrolled 1325 consecutive patients hospitalized for COVID-19, of whom 341 (25.7%) were Black. We measured biomarkers of inflammation and collected data on the use COVID-19-directed therapies, enrollment in COVID-19 clinical trials, mortality, need for renal replacement therapy, and need for mechanical ventilation. RESULTS: Compared to non-Black patients, Black patients had a higher prevalence of COVID-19 risk factors including obesity, hypertension, and diabetes mellitus and were more likely to require renal replacement therapy (15.8% vs 7.1%, P < .001) and mechanical ventilation (37.2% vs 26.6%, P < .001) during their hospitalization. Mortality was similar between both groups (15.5% for Blacks vs 14.0% for non-Blacks, P = .49). Black patients were less likely to receive corticosteroids (44.9% vs 63.8%, P< .001) or remdesivir (23.8% vs 57.8%, P < .001) and were less likely to be enrolled in COVID-19 clinical trials (15.3% vs 28.2%, P < .001). In adjusted analyses, Black race was associated with lower levels of C-reactive protein and soluble urokinase receptor and higher odds of death, mechanical ventilation, and renal replacement therapy. Differences in outcomes were not significant after adjusting for use of remdesivir and corticosteroids. CONCLUSIONS: Racial differences in outcomes of patients with COVID-19 may be related to differences in inflammatory response and differential use of therapies.