Obesity, Inflammation, and Clinical Outcomes in COVID-19: A Multicenter Prospective Cohort Study.

CONTEXT: Obesity is a risk factor for coronavirus disease 2019 (COVID-19)-related outcomes; however, the mechanism remains unclear. OBJECTIVE: The objective of this analysis was to determine whether inflammation mediates the association between obesity and COVID-19 outcomes. DESIGN: The International Study of Inflammation in Covid-19 (ISIC): A Prospective Multi-Center Observational Study Examining the Role of Biomarkers of Inflammation in Predicting Covid-19 Related Outcomes in Hospitalized Patients. SETTING: Ten hospitals in the United States and Europe. PARTICIPANTS: Adults hospitalized specifically for COVID-19 between February 1, 2020, through October 19, 2022. MAIN OUTCOME MEASURES: Inflammatory biomarkers, including soluble urokinase plasminogen activator receptor (suPAR), were measured at admission. Associations were examined between body-mass index (BMI, kg/m2) and a composite of death, need for mechanical ventilation, and renal replacement therapy, stratified by pre- and post-Omicron variants. The contribution of inflammation to the relationship between obesity and outcomes was assessed. RESULTS: Among 4644 participants (mean age 59.3, 45.6% male, 21.8% BMI≥35), those with BMI>40 (n=485) had 55% higher odds of the composite outcome (95% CI[1.21 to 1.98]) compared to non-obese individuals (BMI<30, n=2358) in multivariable analysis. In multiple mediation analysis, only suPAR remained a significant mediator between BMI and composite outcome. Associations were amplified for participants younger than 65 years and with pre-Omicron variants. CONCLUSION: Obesity is associated with worse outcomes in COVID-19, notably in younger participants and in the pre-Omicron era. Inflammation, as measured by suPAR, is a significant mediator of the association between obesity and COVID-19 outcomes.

Intubation Decision Based on Illness Severity and Mortality in COVID-19: An International Study.

OBJECTIVES: To evaluate the impact of intubation timing, guided by severity criteria, on mortality in critically ill COVID-19 patients, amidst existing uncertainties regarding optimal intubation practices. DESIGN: Prospective, multicenter, observational study conducted from February 1, 2020, to November 1, 2022. SETTING: Ten academic institutions in the United States and Europe. PATIENTS: Adults (≥ 18 yr old) confirmed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and hospitalized specifically for COVID-19, requiring intubation postadmission. Exclusion criteria included patients hospitalized for non-COVID-19 reasons despite a positive SARS-CoV-2 test. INTERVENTIONS: Early invasive mechanical ventilation (EIMV) was defined as intubation in patients with less severe organ dysfunction (Sequential Organ Failure Assessment [SOFA] < 7 or Pa o2 /F io2 ratio > 250), whereas late invasive mechanical ventilation (LIMV) was defined as intubation in patients with SOFA greater than or equal to 7 and Pa o2 /F io2 ratio less than or equal to 250. MEASUREMENTS AND MAIN RESULTS: The primary outcome was mortality within 30 days of hospital admission. Among 4464 patients, 854 (19.1%) required mechanical ventilation (mean age 60 yr, 61.7% male, 19.3% Black). Of those, 621 (72.7%) were categorized in the EIMV group and 233 (27.3%) in the LIMV group. Death within 30 days after admission occurred in 278 patients (42.2%) in the EIMV and 88 patients (46.6%) in the LIMV group ( p = 0.28). An inverse probability-of-treatment weighting analysis revealed a statistically significant association with mortality, with patients in the EIMV group being 32% less likely to die either within 30 days of admission (adjusted hazard ratio [HR] 0.68; 95% CI, 0.52-0.90; p = 0.008) or within 30 days after intubation irrespective of its timing from admission (adjusted HR 0.70; 95% CI, 0.51-0.90; p = 0.006). CONCLUSIONS: In severe COVID-19 cases, an early intubation strategy, guided by specific severity criteria, is associated with a reduced risk of death. These findings underscore the importance of timely intervention based on objective severity assessments.

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.

Evolution of Care and Outcomes Across Surges in Hospitalized Patients with Coronavirus Disease 2019.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has unfolded in distinct surges. Understanding how surges differ may reveal important insights into the evolution of the pandemic and improve patient care. METHODS: We leveraged the Michigan Medicine COVID-19 Cohort, a prospective observational study at an academic tertiary medical center that systematically enrolled 2309 consecutive patients hospitalized for COVID-19, comprising 5 distinct surges. RESULTS: As the pandemic evolved, patients hospitalized for COVID-19 tended to have a lower burden of comorbidities and a lower inflammatory burden as measured by admission levels of C-reactive protein, ferritin, lactate dehydrogenase, and D-dimer. Use of hydroxychloroquine and azithromycin decreased substantially after Surge 1, while use of corticosteroids and remdesivir markedly increased (P < .001 for all). In-hospital mortality significantly decreased from 18.3% in Surge 1 to 5.3% in Surge 5 (P < .001). The need for mechanical ventilation significantly decreased from 42.5% in Surge 1 to 7.0% in Surge 5 (P < .001), while the need for renal replacement therapy decreased from 14.4% in Surge 1 to 2.3% in Surge 5 (P < .001). Differences in patient characteristics, treatments, and inflammatory markers accounted only partially for the differences in outcomes between surges. CONCLUSIONS: The COVID-19 pandemic has evolved significantly with respect to hospitalized patient populations and therapeutic approaches, and clinical outcomes have substantially improved. Hospitalization after the first surge was independently associated with improved outcomes, even after controlling for relevant clinical covariates.

NMR chemical shift assignments of RNA oligonucleotides to expand the RNA chemical shift database.

RNAs play myriad functional and regulatory roles in the cell. Despite their significance, three-dimensional structure elucidation of RNA molecules lags significantly behind that of proteins. NMR-based studies are often rate-limited by the assignment of chemical shifts. Automation of the chemical shift assignment process can greatly facilitate structural studies, however, accurate chemical shift predictions rely on a robust and complete chemical shift database for training. We searched the Biological Magnetic Resonance Data Bank (BMRB) to identify sequences that had no (or limited) chemical shift information. Here, we report the chemical shift assignments for 12 RNA hairpins designed specifically to help populate the BMRB.