Does early detection of atrial fibrillation reduce the risk of thromboembolic events? Rationale and design of the Heartline study.

BACKGROUND: The impact of using direct-to-consumer wearable devices as a means to timely detect atrial fibrillation (AF) and to improve clinical outcomes is unknown. METHODS: Heartline is a pragmatic, randomized, and decentralized application-based trial of US participants aged ≥65 years. Two randomized cohorts include adults with possession of an iPhone and without a history of AF and those with a diagnosis of AF taking a direct oral anticoagulant (DOAC) for ≥30 days. Participants within each cohort are randomized (3:1) to either a core digital engagement program (CDEP) via iPhone application (Heartline application) and an Apple Watch (Apple Watch Group) or CDEP alone (iPhone-only Group). The Apple Watch Group has the watch irregular rhythm notification (IRN) feature enabled and access to the ECG application on the Apple Watch. If an IRN notification is issued for suspected AF then the study application instructs participants in the Apple Watch Group to seek medical care. All participants were "watch-naïve" at time of enrollment and have an option to either buy or loan an Apple Watch as part of this study. The primary end point is time from randomization to clinical diagnosis of AF, with confirmation by health care claims. Key secondary endpoint are claims-based incidence of a 6-component composite cardiovascular/systemic embolism/mortality event, DOAC medication use and adherence, costs/health resource utilization, and frequency of hospitalizations for bleeding. All study assessments, including patient-reported outcomes, are conducted through the study application. The target study enrollment is approximately 28,000 participants in total; at time of manuscript submission, a total of 26,485 participants have been enrolled into the study. CONCLUSION: The Heartline Study will assess if an Apple Watch with the IRN and ECG application, along with application-facilitated digital health engagement modules, improves time to AF diagnosis and cardiovascular outcomes in a real-world environment. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04276441.

Epidemiological characteristics of the B.1.526 SARS-CoV-2 variant.

To characterize the epidemiological properties of the B.1.526 SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) variant of interest, here we used nine epidemiological and population datasets and model-inference methods to reconstruct SARS-CoV-2 transmission dynamics in New York City, where B.1.526 emerged. We estimated that B.1.526 had a moderate increase (15 to 25%) in transmissibility, could escape immunity in 0 to 10% of previously infected individuals, and substantially increased the infection fatality risk (IFR) among adults 65 or older by >60% during November 2020 to April 2021, compared to estimates for preexisting variants. Overall, findings suggest that new variants like B.1.526 likely spread in the population weeks before detection and that partial immune escape (e.g., resistance to therapeutic antibodies) could offset prior medical advances and increase IFR. Early preparedness for and close monitoring of SARS-CoV-2 variants, their epidemiological characteristics, and disease severity are thus crucial to COVID-19 (coronavirus disease 2019) response.

Automated analysis of limited echocardiograms: Feasibility and relationship to outcomes in COVID-19.

Background: As automated echocardiographic analysis is increasingly utilized, continued evaluation within hospital settings is important to further understand its potential value. The importance of cardiac involvement in patients hospitalized with COVID-19 provides an opportunity to evaluate the feasibility and clinical relevance of automated analysis applied to limited echocardiograms. Methods: In this multisite US cohort, the feasibility of automated AI analysis was evaluated on 558 limited echocardiograms in patients hospitalized with COVID-19. Reliability of automated assessment of left ventricular (LV) volumes, ejection fraction (EF), and LV longitudinal strain (LS) was assessed against clinically obtained measures and echocardiographic findings. Automated measures were evaluated against patient outcomes using ROC analysis, survival modeling, and logistic regression for the outcomes of 30-day mortality and in-hospital sequelae. Results: Feasibility of automated analysis for both LVEF and LS was 87.5% (488/558 patients). AI analysis was performed with biplane method in 300 (61.5%) and single plane apical 4- or 2-chamber analysis in 136 (27.9%) and 52 (10.7%) studies, respectively. Clinical LVEF was assessed using visual estimation in 192 (39.3%), biplane in 163 (33.4%), and single plane or linear methods in 104 (21.2%) of the 488 studies; 29 (5.9%) studies did not have clinically reported LVEF. LV LS was clinically reported in 80 (16.4%). Consistency between automated and clinical values demonstrated Pearson's R, root mean square error (RMSE) and intraclass correlation coefficient (ICC) of 0.61, 11.3% and 0.72, respectively, for LVEF; 0.73, 3.9% and 0.74, respectively for LS; 0.76, 24.4ml and 0.87, respectively, for end-diastolic volume; and 0.82, 12.8 ml, and 0.91, respectively, for end-systolic volume. Abnormal automated measures of LVEF and LS were associated with LV wall motion abnormalities, left atrial enlargement, and right ventricular dysfunction. Automated analysis was associated with outcomes, including survival. Conclusion: Automated analysis was highly feasible on limited echocardiograms using abbreviated protocols, consistent with equivalent clinically obtained metrics, and associated with echocardiographic abnormalities and patient outcomes.

Using EHR data to identify coronavirus infections in hospitalized patients: Impact of case definitions on disease surveillance.

PURPOSE: To evaluate the number, characteristics, and outcomes of patients identified hospitalized with coronavirus disease 2019 (COVID-19) using two different case definitions. PROCEDURES: Electronic Health Record data were evaluated from patients hospitalized with COVID-19 through May 2020 at 52 health systems across the United States. Characteristics of inpatients with positive laboratory tests for SARS-CoV-2 were compared with those with clinical diagnosis of COVID-19 but without a confirmatory lab result. FINDINGS: Of 14,371 inpatients with COVID-19, 6623 (46.1 %) had a positive laboratory result, and n = 7748 (52.9 %) had only a clinical diagnosis of COVID-19. Compared with clinically diagnosed cases, those with laboratory-confirmed COVID were similar in age and sex, but differed by race, ethnicity, and insurance status. Laboratory-confirmed cases were more likely to receive certain COVID-19 therapies including hydroxychloroquine, anti-IL6 agents and antivirals (p < 0.001). Those with laboratory-confirmed COVID-19 had lower rates of most complications such as myocardial infarction, but higher overall mortality (p < 0.001). CONCLUSION: We observed a two-fold difference in the number of patients hospitalized with COVID-19 depending on whether the case definition required laboratory confirmation. Variations in case definitions also led to differences in cohort characteristics, treatments, and outcomes.

COVID-19 Outbreak - New York City, February 29-June 1, 2020.

New York City (NYC) was an epicenter of the coronavirus disease 2019 (COVID-19) outbreak in the United States during spring 2020 (1). During March-May 2020, approximately 203,000 laboratory-confirmed COVID-19 cases were reported to the NYC Department of Health and Mental Hygiene (DOHMH). To obtain more complete data, DOHMH used supplementary information sources and relied on direct data importation and matching of patient identifiers for data on hospitalization status, the occurrence of death, race/ethnicity, and presence of underlying medical conditions. The highest rates of cases, hospitalizations, and deaths were concentrated in communities of color, high-poverty areas, and among persons aged ≥75 years or with underlying conditions. The crude fatality rate was 9.2% overall and 32.1% among hospitalized patients. Using these data to prevent additional infections among NYC residents during subsequent waves of the pandemic, particularly among those at highest risk for hospitalization and death, is critical. Mitigating COVID-19 transmission among vulnerable groups at high risk for hospitalization and death is an urgent priority. Similar to NYC, other jurisdictions might find the use of supplementary information sources valuable in their efforts to prevent COVID-19 infections.

Effectiveness of Telemedicine Visits in Reducing 30-Day Readmissions Among Patients With Heart Failure During the COVID-19 Pandemic.

Background The COVID-19 pandemic resulted in a rapid implementation of telemedicine into clinical practice. This study examined whether early outpatient follow-up via telemedicine is as effective as in-person visits for reducing 30-day readmissions in patients with heart failure. Methods and Results Using electronic health records from a large health system, we included patients with heart failure living in North Carolina (N=6918) who were hospitalized between March 16, 2020 and March 14, 2021. All-cause readmission within 30 days after discharge was examined using weighted logistic regression models. Overall, 7.6% (N=526) of patients received early telemedicine follow-up, 38.8% (N=2681) received early in-person follow-up, and 53.6% (N=3711) did not receive follow-up within 14 days of discharge. Compared with patients without early follow-up, those who received early follow-up were younger, were more likely to be Medicare beneficiaries, had more comorbidities, and were less likely to live in an disadvantaged neighborhood. Relative to in-person visits, those with telemedicine follow-up were of similar age, sex, and race but with generally fewer comorbidities. Overall, the 30-day readmission rate (19.0%) varied among patients who received telemedicine visits (15.0%), in-person visits (14.0%), or no follow-up (23.1%). After covariate adjustment, patients who received either telemedicine (odds ratio [OR], 0.55; 95% CI, 0.44-0.72) or in-person (OR, 0.52; 95% CI, 0.45-0.60) visits were similarly less likely to be readmitted within 30 days compared with patients with no follow-up. Conclusions During the COVID-19 pandemic, the use of telemedicine visits for early follow-up increased rapidly. Patients with heart failure who received outpatient follow-up either via telemedicine or in-person had better outcomes than those who received no follow-up.

Trends of blood pressure control in the U.S. during the COVID-19 pandemic.

IMPORTANCE: COVID-19 altered lifestyles and disrupted routine health care. Whether blood pressure (BP) control worsened during COVID-19 is unknown. OBJECTIVE: To understand whether home BP control worsened during COVID-19 across the United States (US) . DESIGN, SETTING, AND PARTICIPANTS: A population-based analysis of home BP data from 72,706 participants enrolled in a digital health hypertension control program. Data was compared before (January 2019 to March 2020) and during (April 2020 to August 2020) COVID-19. MAIN OUTCOMES AND MEASURES: Monthly mean home BP readings, systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP) were quantified before and during the pandemic. Multivariable adjustments were made for age, sex, race, region, and months enrolled. Home BP readings were also classified based on monthly averages and highest home BP readings into risk groups: Stage 2 HTN: BP> = 135 or DBP> = 85; Uncontrolled HTN: SBP> = 145 or DBP> = 95; or Severely uncontrolled HTN: SBP> = 160 or DBP> = 100). RESULTS: Overall, 72,706 participants were enrolled in a digital health hypertension program between 1/1/2019 and 8/31/2020. Compared with participants pre-COVID-19 (n = 33,440), those during COVID-19 (n = 39,266) were of similar age (mean 53.0 ± 10.7 years vs 53.3 ± 10.8 years); sex (46% vs 50.6% female) and race (29.1% vs 34.2% non-white). Relative to pre-Covid (Apr-Aug 2019) the mean monthly number of home BP readings rose during COVID-19 (Apr-Aug, 2020), from 7.3 to 9.3 per month (P < .001). During COVID-19, participants had higher monthly adjusted mean SBP (131.6 mmHg vs. 127.5 mmHg, P < .001); DBP (80.2 mmHg vs. 79.2 mmHg, P < .001); and MAP (97.4 mmHg vs. 95.3 mmHg; P < .001). Relative to the pre-pandemic period, during COVID-19 the proportion of participants with a mean monthly BP classified as uncontrolled or severely uncontrolled hypertension also rose, 15% vs 19% and 4% vs 5%, respectively CONCLUSIONS AND RELEVANCE: Based on home BP readings, mean monthly BP rose modestly after COVID-19, despite increased utilization of home monitoring. Further studies are needed to examine the longitudinal effects of the pandemic on cardiovascular disease risk factors, the impact of these on long-term population health.

The impact of race and ethnicity on outcomes in 19,584 adults hospitalized with COVID-19.

INTRODUCTION: At the population level, Black and Hispanic adults in the United States have increased risk of dying from COVID-19, yet whether race and ethnicity impact on risk of mortality among those hospitalized for COVID-19 is unclear. METHODS: Retrospective cohort study using data on adults hospitalized with COVID-19 from the electronic health record from 52 health systems across the United States contributing data to Cerner Real World DataTM. In-hospital mortality was evaluated by race first in unadjusted analysis then sequentially adjusting for demographics and clinical characteristics using logistic regression. RESULTS: Through August 2020, 19,584 patients with median age 52 years were hospitalized with COVID-19, including n = 4,215 (21.5%) Black and n = 5,761 (29.4%) Hispanic patients. Relative to white patients, crude mortality was slightly higher in Black adults [22.7% vs 20.8%, unadjusted OR 1.12 (95% CI 1.02-1.22)]. Mortality remained higher among Black adults after adjusting for demographic factors including age, sex, date, region, and insurance status (OR 1.13, 95% CI 1.01-1.27), but not after including comorbidities and body mass index (OR 1.07, 95% CI 0.93-1.23). Compared with non-Hispanic patients, Hispanic patients had lower mortality both in unadjusted and adjusted models [mortality 12.7 vs 25.0%, unadjusted OR 0.44(95% CI 0.40-0.48), fully adjusted OR 0.71 (95% CI 0.59-0.86)]. DISCUSSION: In this large, multicenter, EHR-based analysis, Black adults hospitalized with COVID-19 had higher observed mortality than white patients due to a higher burden of comorbidities in Black adults. In contrast, Hispanic ethnicity was associated with lower mortality, even in fully adjusted models.

The relationship between coronary artery disease and clinical outcomes in COVID-19: a single-center retrospective analysis.

INTRODUCTION: Recent studies have reported evidence that coronavirus disease 2019 (COVID-19) has disproportionately affected patients with underlying comorbidities. Our study aims to evaluate the impact of both cardiac and noncardiac comorbidities on a high-risk population with COVID-19 infection and coronary artery disease (CAD) compared to those without CAD. METHODS: This is a retrospective study of patients who tested COVID-19 positive via reverse transcriptase-PCR (RT-PCR) assay. We compared the characteristics and outcomes of patients with and without CAD. Population demographics, comorbidities and clinical outcomes were collected and analyzed. Multivariate logistic regression analysis was used to identify factors associated with inpatient mortality. RESULTS: A final sample population of 355 patients was identified, 77 of which had a known diagnosis of coronary artery disease. Our study population had a higher proportion of females, and those with CAD were significantly older. The rates of cardiovascular risk factors including hypertension, diabetes mellitus and chronic kidney disease, as well as heart failure and chronic obstructive pulmonary disease were significantly higher in the CAD population. Lactate dehydrogenase was the only inflammatory marker significantly lower in the CAD group, while troponin and brain natriuretic peptide were significantly higher in this population. Patients with CAD also had significantly higher inpatient mortality (31% vs 20%, P = 0.046) and need for renal replacement therapy (33% vs 11%, P < 0.0001) compared to the non-CAD group. However, only age [odds ratio 1.041 (1.017-1.066), P = 0.001] was significantly associated with mortality in the overall population after adjusting for demographics and comorbidities, while the presence of CAD was not independently associated with mortality. CONCLUSION: Patients with CAD and COVID-19 have higher rates of comorbidities, inpatient mortality and need for renal replacement therapy compared to their non-CAD counterparts. However, CAD in itself was not associated with mortality after adjusting for other covariates, suggesting that other factors may play a larger role in the increased mortality and poor outcomes in these patients.

Characteristics and clinical outcomes of COVID-19 patients in an underserved-inner city population: A single tertiary center cohort.

There is limited information describing the characteristics and clinical outcomes of patients infected with coronavirus disease 2019 (COVID-19) especially those in underserved urban area with minority population in the United States. This is a retrospective single-center study for patients who were admitted with COVID-19 infection. Data collection was from 1 March through 24 April 2020. Demographic, clinical, laboratory, and treatment data were presented using descriptive statistics and frequencies. The χ2 test and multivariate logistic regression were used to determine association of risk factors and clinical outcomes. A total of 242 inpatients were included with a mean age of 66 ± 14.75 (±standard deviation). A total of 50% were female and 70% were African American. Comorbidities included hypertension (74%), diabetes mellitus (49%), and 19% had either COPD or asthma. Older age was associated with higher risk of inpatient death odds ratio (OR): 1.056 (95% confidence interval [CI]: 1.023-1.090; P = .001). Inpatient mortality occurred in 70% who needed mechanical ventilation (OR: 29.51; 95% CI: 13.28-65.60; P < .0001), 58% who required continuous renal replacement therapy/hemodialysis (CRRT/HD) (OR: 6.63; 95% CI: 2.74-16.05; P < .0001), and 69% who needed vasopressors (OR: 30.64; 95% CI: 13.56-69.20; P < .0001). Amongst biomarkers of disease severity, only baseline CRP levels (145 ± 116 mg/L) were associated with mortality OR: 1.008 (95% CI: 1.003-1.012; P = .002). Majority of hospitalized patients had hypertension and diabetes. Older age was an independent risk factor for inpatient mortality. Requirement of mechanical ventilation, vasopressor use, and CRRT/HD was associated significantly with inpatient mortality. Higher baseline CRP was significantly associated with inpatient death.

Detecting COVID-19 Clusters at High Spatiotemporal Resolution, New York City, New York, USA, June-July 2020.

A surveillance system that uses census tract resolution and the SaTScan prospective space-time scan statistic detected clusters of increasing severe acute respiratory syndrome coronavirus 2 test percent positivity in New York City, NY, USA. Clusters included one in which patients attended the same social gathering and another that led to targeted testing and outreach.

Bacterial infections and patterns of antibiotic use in patients with COVID-19.

Bacterial coinfection is associated with poor outcomes in patients with viral pneumonia, but data on its role in the mortality of patients with coronavirus disease 2019 (COVID-19) is limited. This is a single-center retrospective analysis of 242 patients with confirmed COVID-19 admitted to both intensive care and non-intensive care settings. Bacterial coinfection was determined by the presence of characteristic clinical features and positive culture results. Multivariable logistic regression was used to analyze the association of concomitant bacterial infection with inpatient death after adjusting for demographic factors and comorbidities. Antibiotic use pattern was also determined. Bacterial coinfection was detected in 46 (19%) patients. Genitourinary source was the most frequent, representing 57% of all coinfections. The overall mortality rate was 21%. Concomitant bacterial infections were independently associated with increased inpatient mortality (OR, 5.838; 95% CI, 2.647-12.876). Patients with bacterial coinfection were relatively older (71.35 ± 11.20 vs 64.78 ± 15.23; P = .006). A total of 67% of patients received antibiotic therapy, yet 72% did not have an obvious source of bacterial infection. There was a significantly higher rate of inpatient mortality in patients who received antibiotics compared to those who did not (30% vs 5%; P < .0001). Bacterial coinfection in COVID-19 is associated with increased mortality.

Predictors of venous thromboembolism in patients with COVID-19 in an underserved urban population: A single tertiary center experience.

INTRODUCTION: Venous thromboembolism (VTE) is reported in up to 27% of patients with COVID-19 due to SARS-CoV-2 infection. Dysregulated systemic inflammation and various patient traits are presumed to underlie this anomaly. Optimal VTE prophylaxis in COVID-19 patients has not been established due to a lack of validated models for predicting VTE in this population. Our study aims to address this deficiency by identifying demographic and clinical characteristics of COVID-19 patients associated with increased VTE risk. METHODS: This study is a retrospective analysis of all adult patients (final sample, n = 355) hospitalized with confirmed COVID-19 at Einstein Medical Center Philadelphia between March 1 and April 24, 2020. Demographic and clinical patient data were collected and factors associated with VTE were identified and analyzed using t-tests, multivariable logistic regression, and receiver operating characteristic (ROC) curves. RESULTS: Thirty patients (8.5%) developed VTE. Patients with VTE had significantly higher D-dimer levels on admission (P = 0.045) and peak D-dimer levels (P < 0.0001), in addition to higher rates of vasopressor requirements (P = 0.038), intubation (P = 0.003), and death (P = 0.023). Age (OR 1.042), obstructive sleep apnea (OR 5.107), and need for intubation (OR 3.796) were associated with significantly increased odds of VTE. Peak D-dimer level was a good predictor of VTE (AUC 0.806, P < 0.0001) and a D-dimer cutoff of >6640 ng/mL had high (>70%) sensitivity and specificity for VTE. CONCLUSION: Peak D-dimer level may be the most reliable clinical marker in COVID-19 patients for predicting VTE and future prospective studies should attempt to further validate this.

Association of Pre-Admission Statin Use With Reduced In-Hospital Mortality in COVID-19.

BACKGROUND: Coronavirus disease-19 (COVID-19) infection is associated with an uncontrolled systemic inflammatory response. Statins, given their anti-inflammatory properties, may reduce the associated morbidity and mortality. This study aimed to determine the association between statin use prior to hospitalization and in-hospital mortality in COVID-19 patients. METHODS: In this retrospective study, clinical data were collected from the electronic medical records of patients admitted to the hospital with confirmed COVID-19 infection from March 1, 2020 to April 24, 2020. A multivariate regression analysis was performed to study the association of pre-admission statin use with in-hospital mortality. RESULTS: Of 255 patients, 116 (45.5%) patients were on statins prior to admission and 139 (54.5%) were not. The statin group had a higher proportion of end stage renal disease (ESRD) (13.8% vs. 2.9%, p = 0.001), diabetes mellitus (63.8% vs. 35.2%, p<0.001), hypertension (87.9% vs. 61.1%, p < 0.001) and coronary artery disease (CAD) (33.6% vs. 5%, p < 0.001). On multivariate analysis, we found a statistically significant decrease in the odds of in-hospital mortality in patients on statins before admission (OR 0.14, 95% CI 0.03- 0.61, p = 0.008). In the subgroup analysis, statins were associated with a decrease in mortality in those with CAD (OR 0.02, 95% CI 0.0003-0.92 p = 0.045) and those without CAD (OR 0.05, 95% CI 0.005-0.43, p = 0.007). CONCLUSIONS: Our study suggests that statins are associated with reduced in-hospital mortality among patients with COVID-19, regardless of CAD status. More comprehensive epidemiological and molecular studies are needed to establish the role of statins in COVID-19.

Prevailing patterns of liver enzymes in patients with COVID-19 infection and association with clinical outcomes.

BACKGROUND: COVID-19 is now a critical threat to global public health. Although the majority of patients present with respiratory illness, several studies have described multiorgan involvement. This study evaluated the prevailing patterns of liver enzymes in COVID-19 patients on admission and their association with clinical outcomes. METHODS: This was a single-center retrospective analysis of all inpatients with COVID-19. Demographic and clinical factors, and liver enzyme tests, including aspartate aminotransferase (AST) and alanine aminotransferase (ALT), were noted on admission. The association of liver enzyme elevation with outcomes such as inpatient death, need for intubation, and vasopressor use was determined using the chi-square test and multivariate regression analysis. RESULTS: Among 200 patients, AST and ALT elevation was seen in 55% and 20%, respectively. Alkaline phosphatase elevation was seen in 28%. AST elevation was associated with inpatient death (odds ratio [OR] 1.03, 95% confidence interval [CI] 1.01-1.05; P=0.035), need for vasopressors (OR 1.034, 95%CI 1.015-1.055; P=0.001), and intubation (OR 1.03, 95%CI 1.01-1.05; P=0.002). An AST/ALT ratio of 2 or more was seen in 34% of patients and was associated with need for intubation (OR 2.678, 95%CI 1.202-5.963; P=0.016), and need for vasopressors (OR 3.352, 95%CI 1.495-7.514; P=0.003). CONCLUSION: Serum aminotransferase levels are useful markers of hepatocellular injury. Patients with elevated AST or AST/ALT ratio are at higher risk of severe disease, as evidenced by intubation, vasopressor use, and inpatient death. These patients should be monitored closely given their propensity for severe disease.

The Association of Low Molecular Weight Heparin Use and In-hospital Mortality Among Patients Hospitalized with COVID-19.

PURPOSE: To determine the association between low molecular weight heparin (LMWH) use and mortality in hospitalized COVID-19 patients. METHODS: We conducted a retrospective study of patients consecutively enrolled from two major academic hospitals exclusively for COVID-19 in Wuhan, China, from January 26, 2020, to March 26, 2020. The primary outcome was adjusted in-hospital mortality in the LMWH group compared with the non-LMWH group using the propensity score. RESULTS: Overall, 525 patients with COVID-19 enrolled with a median age of 64 years (IQR 19), and 49.33% men. Among these, 120 (22.86%) were treated with LMWH. Compared with the non-LMWH group, the LMWH group was more likely to be older and male; had a history of hypertension, diabetes, coronary heart disease (CHD), or stroke; and had more severe COVID-19 parameters such as higher inflammatory cytokines or D-dimer. Compared with non-LMWH group, LMWH group had a higher unadjusted in-hospital mortality rate (21.70% vs. 11.10%; p = 0.004), but a lower adjusted mortality risk (adjusted odds ratio [OR], 0.20; 95% CI, 0.09-0.46). A propensity score-weighting analysis demonstrated similar findings (adjusted OR, 0.18; 95% CI, 0.10-0.30). Subgroup analysis showed a significant survival benefit among those who were severely (adjusted OR, 0.07; 95% CI, 0.02-0.23) and critically ill (adjusted OR, 0.32; 95% CI, 0.15-0.65), as well as among the elderly patients' age > 65, IL-6 > 10 times upper limit level, and D-dimer > 5 times upper limit level. CONCLUSIONS: Among hospitalized COVID-19 patients, LMWH use was associated with lower all-cause in-hospital mortality than non-LMWH users. The survival benefit was particularly significant among more severely ill patients.

Rapid identification of a human antibody with high prophylactic and therapeutic efficacy in three animal models of SARS-CoV-2 infection.

Effective therapies are urgently needed for the SARS-CoV-2/COVID-19 pandemic. We identified panels of fully human monoclonal antibodies (mAbs) from large phage-displayed Fab, scFv, and VH libraries by panning against the receptor binding domain (RBD) of the SARS-CoV-2 spike (S) glycoprotein. A high-affinity Fab was selected from one of the libraries and converted to a full-size antibody, IgG1 ab1, which competed with human ACE2 for binding to RBD. It potently neutralized replication-competent SARS-CoV-2 but not SARS-CoV, as measured by two different tissue culture assays, as well as a replication-competent mouse ACE2-adapted SARS-CoV-2 in BALB/c mice and native virus in hACE2-expressing transgenic mice showing activity at the lowest tested dose of 2 mg/kg. IgG1 ab1 also exhibited high prophylactic and therapeutic efficacy in a hamster model of SARS-CoV-2 infection. The mechanism of neutralization is by competition with ACE2 but could involve antibody-dependent cellular cytotoxicity (ADCC) as IgG1 ab1 had ADCC activity in vitro. The ab1 sequence has a relatively low number of somatic mutations, indicating that ab1-like antibodies could be quickly elicited during natural SARS-CoV-2 infection or by RBD-based vaccines. IgG1 ab1 did not aggregate, did not exhibit other developability liabilities, and did not bind to any of the 5,300 human membrane-associated proteins tested. These results suggest that IgG1 ab1 has potential for therapy and prophylaxis of SARS-CoV-2 infections. The rapid identification (within 6 d of availability of antigen for panning) of potent mAbs shows the value of large antibody libraries for response to public health threats from emerging microbes.