scholarly journals Patient trajectories and risk factors for severe outcomes among persons hospitalized for COVID-19 in the Maryland/DC region

2020 ◽  
Author(s):  
Brian T. Garibaldi ◽  
Jacob Fiksel ◽  
John Muschelli ◽  
Matthew Robinson ◽  
Masoud Rouhizadeh ◽  
...  
Keyword(s):  
Risk Factors ◽  
Respiratory Rate ◽  
Disease Severity ◽  
Clinical Features ◽  
Hospital Admissions ◽  
Severe Disease ◽  
Cohort Analysis ◽  
Ordinal Scale ◽  
Severe Illness ◽  
Poor Outcomes

AbstractBackgroundRisk factors for poor outcomes from COVID-19 are emerging among US cohorts, but patient trajectories during hospitalization ranging from mild-moderate, severe, and death and the factors associated with these outcomes have been underexplored.MethodsWe performed a cohort analysis of consecutive COVID-19 hospital admissions at 5 Johns Hopkins hospitals in the Baltimore/DC area between March 4 and April 24, 2020. Disease severity and outcomes were classified using the WHO COVID-19 disease severity ordinal scale. Cox proportional-hazards regressions were performed to assess relationships between demographics, clinical features and progression to severe disease or death.Results832 COVID-19 patients were hospitalized; 633 (76.1%) were discharged, 113 (13.6%) died, and 85 (10.2%) remained hospitalized. Among those discharged, 518 (82%) had mild/moderate and 116 (18%) had severe illness. Mortality was statistically significantly associated with increasing age per 10 years (adjusted hazard ratio (aHR) 1.54; 95%CI 1.28-1.84), nursing home residence (aHR 2.13, 95%CI 1.41-3.23), Charlson comorbidity index (1.13; 95% CI 1.02-1.26), respiratory rate (aHR 1.13; 95%CI 1.09-1.17), D-dimer greater than 1mg/dL (aHR 2.79; 95% 1.53-5.09), and detectable troponin (aHR 2.79; 95%CI 1.53-5.09). In patients under 60, only male sex (aHR 1.7;95%CI 1.11-2.58), increasing body mass index (BMI) (aHR1.25 1.14-1.37), Charlson score (aHR 1.27; 1.1-1.46) and respiratory rate (aHR 1.16; 95%CI 1.13-1.2) were associated with severe illness or death.ConclusionsA combination of demographic and clinical features on admission is strongly associated with progression to severe disease or death in a US cohort of COVID-19 patients. Younger patients have distinct risk factors for poor outcomes.

scholarly journals Informing the public health response to COVID-19: a systematic review of risk factors for disease, severity, and mortality

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
M. Flook ◽  
C. Jackson ◽  
E. Vasileiou ◽  
C. R. Simpson ◽  
M. D. Muckian ◽  
...  
Keyword(s):  
Public Health ◽  
Risk Factors ◽  
Systematic Review ◽  
At Risk ◽  
Risk Factor ◽  
Disease Severity ◽  
Severe Disease ◽  
Public Health Response ◽  
Wide Range ◽  
Multivariable Analyses

Abstract Background Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2) has challenged public health agencies globally. In order to effectively target government responses, it is critical to identify the individuals most at risk of coronavirus disease-19 (COVID-19), developing severe clinical signs, and mortality. We undertook a systematic review of the literature to present the current status of scientific knowledge in these areas and describe the need for unified global approaches, moving forwards, as well as lessons learnt for future pandemics. Methods Medline, Embase and Global Health were searched to the end of April 2020, as well as the Web of Science. Search terms were specific to the SARS-CoV-2 virus and COVID-19. Comparative studies of risk factors from any setting, population group and in any language were included. Titles, abstracts and full texts were screened by two reviewers and extracted in duplicate into a standardised form. Data were extracted on risk factors for COVID-19 disease, severe disease, or death and were narratively and descriptively synthesised. Results One thousand two hundred and thirty-eight papers were identified post-deduplication. Thirty-three met our inclusion criteria, of which 26 were from China. Six assessed the risk of contracting the disease, 20 the risk of having severe disease and ten the risk of dying. Age, gender and co-morbidities were commonly assessed as risk factors. The weight of evidence showed increasing age to be associated with severe disease and mortality, and general comorbidities with mortality. Only seven studies presented multivariable analyses and power was generally limited. A wide range of definitions were used for disease severity. Conclusions The volume of literature generated in the short time since the appearance of SARS-CoV-2 has been considerable. Many studies have sought to document the risk factors for COVID-19 disease, disease severity and mortality; age was the only risk factor based on robust studies and with a consistent body of evidence. Mechanistic studies are required to understand why age is such an important risk factor. At the start of pandemics, large, standardised, studies that use multivariable analyses are urgently needed so that the populations most at risk can be rapidly protected. Registration This review was registered on PROSPERO as CRD42020177714.

scholarly journals Healthcare utilization and costs in adults with SLE in the United Kingdom: a real-world observational retrospective cohort analysis

2021 ◽  
Author(s):  
Mihail Samnaliev ◽  
Volkan Barut ◽  
Sharada Weir ◽  
Julia Langham ◽  
Sue Langham ◽  
...  
Keyword(s):  
Disease Severity ◽  
Healthcare Costs ◽  
Severe Disease ◽  
Cohort Analysis ◽  
Practice Research ◽  
Future Research ◽  
First Year ◽  
Clinical Practice Research Datalink ◽  
Comorbid Conditions ◽  
The Uk

Abstract Objectives To describe direct healthcare costs for adults with systemic lupus erythematosus (SLE) in the UK over time and by disease severity and encounter type. Methods Patients aged ≥18 years with SLE were identified using the linked Clinical Practice Research Datalink—Hospital Episode Statistics database from January 2005 to December 2017. Patients were classified as having mild, moderate, or severe disease using an adapted claims-based algorithm based on prescriptions and comorbid conditions. We estimated all-cause healthcare costs and incremental costs associated with each year of follow-up compared with a baseline year adjusting for age, sex, disease severity, and comorbid conditions (2017 UK pounds). Results We identified 802 patients; 369 (46.0%) with mild, 345 (43.0%) moderate, and 88 (11.0%) severe disease. The mean all-cause cost increased in the 3 years before diagnosis, peaked in the first year after diagnosis and remained high. Adjusted total mean annual increase in costs per patient was £4476 (95% confidence interval £3809–5143) greater in the year of diagnosis compared with the baseline year (p < 0.0001). The increase in costs per year were 4.7-fold and 1.6-fold higher among patients with severe SLE compared with those with mild and moderate SLE respectively. Primary care utilisation was the leading component of costs during the first year of diagnosis. Conclusion The healthcare costs for patients with SLE in the UK are substantial, remain high after diagnosis and increase with increasing severity. Future research should assess whether earlier diagnosis and treatment may reduce disease severity and associated high healthcare costs.

scholarly journals The Predictive Value of Myoglobin for COVID-19-Related Adverse Outcomes: A Systematic Review and Meta-Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Chaoqun Ma ◽  
Dingyuan Tu ◽  
Jiawei Gu ◽  
Qiang Xu ◽  
Pan Hou ◽  
...  
Keyword(s):  
Troponin I ◽  
Meta Analysis ◽  
Severe Disease ◽  
Cardiac Injury ◽  
Case Fatality ◽  
Adverse Outcomes ◽  
Cardiac Biomarkers ◽  
Severe Illness ◽  
Poor Outcomes ◽  
Meta Analyses

Objective: Cardiac injury is detected in numerous patients with coronavirus disease 2019 (COVID-19) and has been demonstrated to be closely related to poor outcomes. However, an optimal cardiac biomarker for predicting COVID-19 prognosis has not been identified.Methods: The PubMed, Web of Science, and Embase databases were searched for published articles between December 1, 2019 and September 8, 2021. Eligible studies that examined the anomalies of different cardiac biomarkers in patients with COVID-19 were included. The prevalence and odds ratios (ORs) were extracted. Summary estimates and the corresponding 95% confidence intervals (95% CIs) were obtained through meta-analyses.Results: A total of 63 studies, with 64,319 patients with COVID-19, were enrolled in this meta-analysis. The prevalence of elevated cardiac troponin I (cTnI) and myoglobin (Mb) in the general population with COVID-19 was 22.9 (19–27%) and 13.5% (10.6–16.4%), respectively. However, the presence of elevated Mb was more common than elevated cTnI in patients with severe COVID-19 [37.7 (23.3–52.1%) vs.30.7% (24.7–37.1%)]. Moreover, compared with cTnI, the elevation of Mb also demonstrated tendency of higher correlation with case-severity rate (Mb, r = 13.9 vs. cTnI, r = 3.93) and case-fatality rate (Mb, r = 15.42 vs. cTnI, r = 3.04). Notably, elevated Mb level was also associated with higher odds of severe illness [Mb, OR = 13.75 (10.2–18.54) vs. cTnI, OR = 7.06 (3.94–12.65)] and mortality [Mb, OR = 13.49 (9.3–19.58) vs. cTnI, OR = 7.75 (4.4–13.66)] than cTnI.Conclusions: Patients with COVID-19 and elevated Mb levels are at significantly higher risk of severe disease and mortality. Elevation of Mb may serve as a marker for predicting COVID-19-related adverse outcomes.Prospero Registration Number:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020175133, CRD42020175133.

scholarly journals Poor Physical Capacity in Bronchiectasis Patients Is Correlated with Poor Quality of Life

2021 ◽  
Author(s):  
Jarkko Mäntylä ◽  
Tanja Törölä ◽  
Witold Mazur ◽  
Paula Bergman ◽  
Paula Kauppi
Keyword(s):  
Quality Of Life ◽  
Risk Factors ◽  
Disease Severity ◽  
Bacterial Colonization ◽  
Severe Disease ◽  
Poor Quality ◽  
Physical Capacity ◽  
Bacterial Colonisation ◽  
Cross Sectional

Abstract BackgroundTo study the risk factors associated with quality of life (QoL) in a cohort of Finnish non-cystic fibrosis bronchiectasis (BE) patients. We aimed to evaluate which of the clinical characteristics were risk factors for poor quality of life, how patients with frequent exacerbations differed from those with only few exacerbations and if QoL symptom domains were correlated with dyspnoea or severity of BE.MethodsA cross-sectional study and part of the EMBARC study including questionnaire data and medical record data. Study participants were recruited between August 2016 and March 2018 from three different pulmonary clinics in Helsinki University Central Hospital (HUH) catchment area, Finland. The study included 95 adult patients with (mean age was 69 (SD± 13) years).A Finnish translation of the disease-specific quality of life-bronchiectasis (QoL-B) questionnaire was applied, and scores in the lowest quarter (25%) of the scale were considered to indicate poor QoL. The bronchiectasis severity index (BSI) and FACED (including FEV1, age, pulmonary bacterial colonization, affected lobes and dyspnoea) score were used. The severity of dyspnoea was examined using the modified Medical Research Council (mMRC) dyspnoea scale.ResultsAlmost all (82%) presented with chronic sputum production and exacerbations, with a median rate of 1.7 (SD ±1.6). Exacerbations (OR 1.7, p < 0.01), frequent exacerbations (OR 4.9, p < 0.01), high BSI score (OR 1.3, p < 0.01) and extensive disease (OR 3.7, p = 0.05) were predictive of poor QoL. Frequent exacerbations were associated with bronchial bacterial colonisation, low forced expiratory volume in one second (FEV1) and radiological disease severity. Based on the BSI, 34.1% of our cohort had severe disease, whereas 11.6% were classified as severe according to the FACED score. The mMRC dyspnoea score (r = -0.57) and BSI (r = -0.60) were negatively correlated with physical domain in QoL-B questionnaire. ConclusionFrequent exacerbations, radiological disease severity and high BSI score were predictive of poor QoL. Reduced physical capacity was correlated with dyspnoea and severity of disease. Interventions to reduce bacterial colonisation and to maintain physical functioning should be used to minimize exacerbations and to improve quality of life in BE patients.Study registrationUniversity of Helsinki, faculty of medicine; 148/16.08.2017

scholarly journals Malaria in patients with sickle cell anemia: burden, risk factors, and outcome at the outpatient clinic and during hospitalization

Blood ◽  
2010 ◽  
Vol 115 (2) ◽  
pp. 215-220 ◽  
Author(s):  
Julie Makani ◽  
Albert N. Komba ◽  
Sharon E. Cox ◽  
Julie Oruo ◽  
Khadija Mwamtemi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Sickle Cell ◽  
Sickle Cell Anemia ◽  
Outpatient Clinic ◽  
Hospital Admissions ◽  
Clinical Malaria ◽  
Dar Es Salaam ◽  
Severe Illness ◽  
Severe Anemia ◽  
Prospective Surveillance

Abstract Approximately 280 000 children are born with sickle cell anemia (SCA) in Africa annually, yet few survive beyond childhood. Falciparum malaria is considered a significant cause of this mortality. We conducted a 5-year prospective surveillance study for malaria parasitemia, clinical malaria, and severe malarial anemia (SMA) in Dar-es-Salaam, Tanzania, between 2004 and 2009. We recorded 10 491 visits to the outpatient clinic among 1808 patients with SCA and 773 visits among 679 patients without SCA. Similarly, we recorded 691 hospital admissions among 497 patients with SCA and 2017 in patients without SCA. Overall, the prevalence of parasitemia was lower in patients with SCA than in patients without SCA both at clinic (0.7% vs 1.6%; OR, 0.53; 95% CI, 0.32-0.86; P = .008) and during hospitalization (3.0% vs 5.6%; OR, 0.46; 95% CI, 0.25-0.94; P = .01). Furthermore, patients with SCA had higher rates of malaria during hospitalization than at clinic, the ORs being 4.29 (95% CI, 2.63-7.01; P < .001) for parasitemia, 17.66 (95% CI, 5.92-52.71; P < .001) for clinical malaria, and 21.11 (95% CI, 8.46-52.67; P < .001) for SMA. Although malaria was rare among patients with SCA, parasitemia during hospitalization was associated with both severe anemia and death. Effective treatment for malaria during severe illness episodes and further studies to determine the role chemoprophylaxis are required.

scholarly journals Development and validation of a prognostic model for COVID-19: a population-based cohort study in Iceland

2021 ◽  
Author(s):  
Elias Eythorsson ◽  
Valgerdur Bjarnadottir ◽  
Hrafnhildur Linnet Runolfsdottir ◽  
Dadi Helgason ◽  
Ragnar Freyr Ingvarsson ◽  
...  
Keyword(s):  
Risk Factors ◽  
Prognostic Model ◽  
Outpatient Visit ◽  
Severe Disease ◽  
Population Based ◽  
Adverse Outcomes ◽  
Clinical Severity ◽  
Ordinal Scale ◽  
Chronic Obstructive ◽  
C Statistic

Background: The severity of SARS-CoV-2 infection varies from asymptomatic state to severe respiratory failure and the clinical course is difficult to predict. The aim of the study was to develop a prognostic model to predict the severity of COVID-19 at the time of diagnosis and determine risk factors for severe disease. Methods: All SARS-CoV-2-positive adults in Iceland were prospectively enrolled into a telehealth service at diagnosis. A multivariable proportional-odds logistic regression model was derived from information obtained during the enrollment interview with those diagnosed before May 1, 2020 and validated in those diagnosed between May 1 and December 31, 2020. Outcomes were defined on an ordinal scale; no need for escalation of care during follow-up, need for outpatient visit, hospitalization, and admission to intensive care unit (ICU) or death. Risk factors were summarized as odds ratios (OR) adjusted for confounders identified by a directed acyclic graph. Results: The prognostic model was derived from and validated in 1,625 and 3,131 individuals, respectively. In total, 375 (7.9%) only required outpatient visits, 188 (4.0%) were hospitalized and 50 (1.1%) were either admitted to ICU or died due to complications of COVID-19. The model included age, sex, body mass index (BMI), current smoking, underlying conditions, and symptoms and clinical severity score at enrollment. Discrimination and calibration were excellent for outpatient visit or worse (C-statistic 0.75, calibration intercept 0.04 and slope 0.93) and hospitalization or worse (C-statistic 0.81, calibration intercept 0.16 and slope 1.03). Age was the strongest risk factor for adverse outcomes with OR of 75- compared to 45- year-olds, ranging from 5.29-17.3. Higher BMI consistently increased the risk and chronic obstructive pulmonary disease and chronic kidney disease correlated with worse outcomes. Conclusion: Our prognostic model can accurately predict the outcome of SARS-CoV-2 infection using information that is available at the time of diagnosis.

scholarly journals A retrospective study of sepsis-associated encephalopathy: epidemiology, clinical features and adverse outcomes

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Jiayi Chen ◽  
Xiaobei Shi ◽  
Mengyuan Diao ◽  
Guangyong Jin ◽  
Ying Zhu ◽  
...  
Keyword(s):  
Risk Factors ◽  
Retrospective Study ◽  
Clinical Features ◽  
Sofa Score ◽  
Adverse Outcomes ◽  
Apache Ii ◽  
Apache Ii Score ◽  
Gastrointestinal Infections ◽  
Independent Risk Factors ◽  
Poor Outcomes

Abstract Background Sepsis-associated encephalopathy (SAE) is a common complication of sepsis that may result in worse outcomes. This study was designed to determine the epidemiology, clinical features, and risk factors of SAE. Methods This was a retrospective study of all patients with sepsis who were admitted to the Critical Care Medicine Department of Hangzhou First People’s Hospital Affiliated with Zhejiang University School of Medicine from January 2015 to December 2019. Results A total of 291 sepsis patients were screened, and 127 (43.6%) were diagnosed with SAE. There were significant differences in median age, proportion of underlying diseases such as hypertension, Sequential Organ Failure Assessment (SOFA) score, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, gastrointestinal infections, detection rate of Enterococcus, and 28-day mortality between the SAE and non-SAE groups. Both the SOFA score and APACHE II score were independent risk factors for SAE in patients with sepsis. All 127 SAE patients were divided into survival and non-survival groups. The age, SOFA score, and APACHE II score were independently associated with 28-day mortality in SAE patients. Conclusion In the present retrospective study, nearly half of patients with sepsis developed SAE, which was closely related to poor outcomes. Both the SOFA score and APACHE II score were independent risk factors for predicting the occurrence and adverse outcome of SAE.

Factors Associated with COVID-19 Morbidity and Mortality: A Narrative Review

2021 ◽  
Author(s):  
Omid Dadras ◽  
Nazanin Shahrokhnia ◽  
Sarina Borran ◽  
Ali Asadollahi-Amin ◽  
SeyedAhmad SeyedAlinaghi
Keyword(s):  
Risk Factors ◽  
Severe Disease ◽  
Narrative Review ◽  
Morbidity And Mortality ◽  
Laboratory Findings ◽  
Factors Affecting ◽  
Impaired Liver ◽  
Duration Of Hospitalization ◽  
Poor Outcomes ◽  
Underlying Diseases

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has been declared as a pandemic on March 11th 2020 by the WHO. Morbidity and mortality of COVID-19 has been shown to be high among patients with underlying diseases. In this narrative review, searching a number of electronic databases (PubMed, Google Scholar, Scopus, and Science Direct), 127 related articles written in English were retrieved and of which 73 articles related to risk factors affecting morbidity and mortality of COVID-19 were extracted and summarized. Factors such as old age, male gender and working in health setting were associated with higher morbidity and mortality. Hypertension was the most frequent reported condition among those with severe disease. It also appeared to increase the mortality and duration of hospitalization. Diabetes, respiratory chronic illnesses (COPD, asthma), impaired liver and renal function, and malignancies were also mentioned as the risk factors for severe disease, longer hospitalization, poor prognosis and outcome. Some laboratory findings such as elevated D-dimer, CRP, and LDH as well as severe lymphopenia were associated with severity, mortality and poor outcomes in hospitalized patients. All in all, a considerable number of comorbidities and biomarkers are associated with severity and presentations of COVID-19 disease, affecting its morbidity and mortality rates.

Pneumothorax in Patients with Idiopathic Pleuroparenchymal Fibroelastosis: Incidence, Clinical Features, and Risk Factors

Respiration ◽  
2021 ◽  
pp. 1-8
Author(s):  
Masato Kono ◽  
Yutaro Nakamura ◽  
Yasunori Enomoto ◽  
Hideki Yasui ◽  
Hironao Hozumi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Clinical Features ◽  
Cumulative Incidence ◽  
Rank Test ◽  
Prior History ◽  
Pleuroparenchymal Fibroelastosis ◽  
History Of ◽  
Poor Outcomes ◽  
Persistent Air Leak ◽  
Retrospective Multicenter Study

<b><i>Background:</i></b> Idiopathic pleuroparenchymal fibroelastosis (PPFE) is a rare form of idiopathic interstitial pneumonia that is characterized by predominantly upper lobe pleural and subpleural lung parenchymal fibrosis. Pneumothorax is one of the major respiratory complications in PPFE patients; however, its clinical features are poorly understood. <b><i>Objective:</i></b> We aimed to investigate the complication of pneumothorax in patients with idiopathic PPFE. <b><i>Methods:</i></b> A retrospective multicenter study involving 89 patients who had been diagnosed with idiopathic PPFE was conducted. We investigated the cumulative incidence, clinical features, and risk factors of pneumothorax after the diagnosis of idiopathic PPFE. <b><i>Results:</i></b> Pneumothorax developed in 53 patients (59.6%) with 120 events during the observation period (41.8 ± 35.0 months). The cumulative incidence of pneumothorax was 24.8, 44.9, and 53.9% at 1, 2, and 3 years, respectively. Most events of pneumothorax were asymptomatic (<i>n</i> = 85; 70.8%) and small in size (<i>n</i> = 92; 76.7%); 30 patients (56.6%) had recurrent pneumothorax. Chest drainage was required in 23 pneumothorax events (19.2%), and a persistent air leak was observed in 13 (56.5%). Patients with pneumothorax were predominantly male and frequently had pathological diagnoses of PPFE and prior history of pneumothorax and corticosteroid use; they also had significantly poorer survival than those without pneumothorax (log-rank test; <i>p</i> = 0.001). Multivariate analysis revealed that a higher residual volume/total lung capacity ratio was significantly associated with the development of pneumothorax after the diagnosis. <b><i>Conclusion:</i></b> Pneumothorax is often asymptomatic and recurrent in patients with idiopathic PPFE, leading to poor outcomes in some cases.

scholarly journals 322. Risk Factors for COVID-19 Disease Severity Using Electronic-Health Records in a Real-World Cohort in the United States

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S266-S267
Author(s):  
Shemra Rizzo ◽  
Ryan Gan ◽  
Devika Chawla ◽  
Kelly Zalocusky ◽  
Xin Chen ◽  
...  
Keyword(s):  
Risk Factors ◽  
Electronic Health Records ◽  
Confidence Intervals ◽  
Disease Severity ◽  
Charlson Comorbidity Index ◽  
Severe Disease ◽  
Older Age ◽  
Calendar Time ◽  
Health Records ◽  
Comorbidity Index

Abstract Background Over 32 million cases of COVID-19 have been reported in the US. Outcomes range from mild upper respiratory infection to hospitalization, acute respiratory failure, and death. We assessed risk factors associated with severe disease, defined as hospitalization within 21 days of diagnosis or death, using US electronic health records (EHR). Methods Patients in the Optum de-identified COVID-19 EHR database who were diagnosed with COVID-19 in 2020 were included in the analysis. Regularized multivariable logistic regression was used to identify risk factors for severe disease. Covariates included demographics, comorbidities, history of influenza vaccination, and calendar time. Results Of the 193,454 eligible patients, 36,043 (18.6%) were hospitalized within 21 days of COVID-19 diagnosis, and 6,397 (3.3%) died. Calendar time followed an inverse J-shaped relationship where severe disease rates rapidly declined in the first 25 weeks of the pandemic. BMI followed an asymmetric V-shaped relationship with highest rates of disease severity observed at the extremes. In the multivariable model, older age had the strongest association with disease severity (odds ratios and 95% confidence intervals of significant associations in Figure). Other risk factors were male sex, uninsured status, underweight and obese BMI, higher Charlson Comorbidity Index, and individual comorbidities including hypertension. Asthma and overweight BMI were not associated with disease severity. Blacks, Hispanics, and Asians experienced higher odds of disease severity compared to Whites. Figure. Significant associations (odds ratio and 95% confidence intervals) with COVID-19 severity (hospitalization or death), adjusted for geographical division. Reference and abbreviation categories: Charlson comorbidity index (CCI) = 0; Age = 18-30; Sex = Female; Race/Ethnicity = White; Insurance = Commercial; Body mass index (BMI) = 18.5-25; Calendar time = 0-25 weeks; Chronic obstructive pulmonary disease (COPD). Conclusion Odds of hospitalization or death have decreased since the start of the pandemic, with the steepest decline observed up to mid-August, possibly reflecting changes in both testing and treatment. Older age is the most important predictor of severe COVID-19. Obese and underweight, but not overweight, BMI were associated with increased odds of disease severity when compared to normal weight. Hypertension, despite not being included in many guidelines for vaccine prioritization, is a significant risk factor. Pronounced health disparities remain across race and ethnicity after accounting for comorbidities, with minorities experiencing higher disease severity. Disclosures Shemra Rizzo, PhD, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Ryan Gan, PhD, F. Hoffmann-La Roche Ltd (Shareholder)Genentech, Inc. (Employee) Devika Chawla, PhD MSPH, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Kelly Zalocusky, PhD, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Xin Chen, PhD, F. Hoffmann-La Roche Ltd. (Shareholder)Genentech, Inc. (Employee) Yifeng Chia, PhD, F. Hoffmann-La Roche Ltd (Shareholder)Genentech, Inc. (Employee)

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