Sep 17, 2021
Last Posted: Sep-17-2021 14:31:33
Comparative Effectiveness of Moderna, Pfizer-BioNTech, and Janssen (Johnson & Johnson) Vaccines in Preventing COVID-19 Hospitalizations Among Adults Without Immunocompromising Conditions — United States, March–August 2021
WH Self et al, MMWR, September 17, 2021
Two 2-dose mRNA COVID-19 vaccines (from Pfizer-BioNTech and Moderna) and a 1-dose viral vector vaccine (from Janssen [Johnson & Johnson]) are currently used in the United States. Among U.S. adults without immunocompromising conditions, vaccine effectiveness against COVID-19 hospitalization during March 11–August 15, 2021, was higher for the Moderna vaccine (93%) than the Pfizer-BioNTech vaccine (88%) and the Janssen vaccine (71%).
What have we learned from the COVID-19 plague?
SA Plotkin, Science Translational Medicine, September 15, 2021
What have we learned from the COVID-19 pandemic, aside from the need to have prototype vaccines “ready to go”? Foremost is our new ability to use various technologies for rapid vaccine development. Information about the sequence of DNA and RNA genomes of old and new pathogens now enables us to rapidly construct vaccines based on these nucleic acids. We even can use this information to mutate the genomes to produce attenuated strains of the pathogens. Also, once armed with information that identifies the protective antigens, genetic information for those antigens can be inserted into a wide array of nonreplicating vectors, including not only adenoviruses but also other viruses.
Adverse reactions to BNT162b2 mRNA COVID-19 vaccine in medical staffs with a history of allergy.
S Inoue et al, MEDRXIV, September 16, 2021
Social Capital Dimensions are Differentially Associated with COVID-19 Vaccinations, Masks, and Physical Distancing
I Fenwana et al, MEDRXIV, September 16, 2021
Spread of SARS-CoV-2 Delta variant infections bearing the S:E484Q and S:T95I mutations in July and August 2021 in France
L Verdume et al, MEDRXIV, September 16, 2021
Detailed Overview of the Buildout and Integration of an Automated High-Throughput CLIA Laboratory for SARS-CoV-2 Testing on a Large Urban Campus
L Landaverde et al, MEDRXIV, September 16, 2021
Using Artificial Intelligence-based models to predict the risk of Mucormycosis among COVID-19 Survivors: An Experience from India
SS Abdul et al, MEDRXIV, September 16, 2021
mRNA COVID-19 Vaccination and Development of CMR-confirmed Myopericarditis
T Kafil et al, MEDRXIV, September 16, 2021
Reduced levels of convalescent neutralizing antibodies against SARS-CoV-2 B.1+L249S+E484K lineage
DAA Diaz et al, MEDRXIV, September 16, 2021
Meta-analysis of rapid direct-to-PCR assays for the qualitative detection of SARS-CoV-2
RA Trevor et al, MEDRXIV, September 16, 2021
Reinfection by the SARS-CoV-2 Gamma variant in blood donors in Manaus, Brazil
CA Prete et al, MEDRXIV, September 16, 2021
COVID-19 mRNA Vaccination in Lactation: Assessment of adverse events and vaccine related antibodies in mother-infant dyads
Y Golan et al, MEDRXIV, September 16, 2021
Subgenomic and negative sense RNAs are not markers of active replication of SARS-CoV-2 in nasopharyngeal swabs
A Chamings et al, MEDRXIV, September 17, 2021
Federated learning for predicting clinical outcomes in patients with COVID-19
I Dayan et al, Nature Medicine, September 15, 2021
We used data from 20?institutes across the globe to train a FL model, called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays. EXAM achieved an average area under the curve (AUC) >0.92 for predicting outcomes at 24 and 72?h from the time of initial presentation to the emergency room, and it provided 16% improvement in average AUC measured across all participating sites and an average increase in generalizability of 38% when compared with models trained at a single site using that site’s data.
Did the coronavirus jump from animals to people twice? A preliminary analysis of viral genomes suggests the COVID-19 pandemic might have multiple animal origins
S Mallapaty, Nature, September 16, 2021
Yield of clinically reportable genetic variants in unselected cerebral palsy by whole genome sequencing
CL van Eyk et al, NPJ Genomic Medicine, September 16, 2021
Despite increasing evidence for a major contribution of genetics to CP aetiology, genetic testing is currently not performed systematically. We assessed the diagnostic rate of genome sequencing (GS) in a clinically unselected cohort of 150 singleton CP patients, with CP confirmed at >4 years of age. Clinical grade GS was performed on the proband and variants were filtered, and classified according to American College of Medical Genetics and Genomics–Association for Molecular Pathology (ACMG-AMP) guidelines. Variants classified as pathogenic or likely pathogenic (P/LP) were further assessed for their contribution to CP. In total, 24.7% of individuals carried a P/LP variant(s) causing or increasing risk of CP, with 4.7% resolved by copy number variant analysis and 20% carrying single nucleotide or indel variants.
Digital intervention increases influenza vaccination rates for people with diabetes in a decentralized randomized trial
JL Lee et al, NPJ Digital Medicine, September 17, 2021
People with diabetes (PWD) have an increased risk of developing influenza-related complications, including pneumonia, abnormal glycemic events, and hospitalization. Annual influenza vaccination is recommended for PWD, but vaccination rates are suboptimal. The study aimed to increase influenza vaccination rate in people with self-reported diabetes. This study was a prospective, 1:1 randomized controlled trial of a 6-month Digital Diabetes Intervention in U.S. adults with diabetes.
Preventing Glaucoma Vision Loss with ‘Big Data’
F Collins, NIH Director blog, September 16, 2021
A recent study analyzed data from more than 1,200 people with glaucoma who participate in NIH’s All of Us Research Program. With consent from the participants, Baxter used their EHRs to train a computer to find telltale patterns within the data and then predict with 80 to 99 percent accuracy who would later require eye surgery.
Measuring the Value of a Practical Text Mining Approach to Identify Patients With Housing Issues in the Free-Text Notes in Electronic Health Record: Findings of a Retrospective Cohort Study.
Hatef Elham et al. Frontiers in public health 2021 9697501
Despite the growing efforts to standardize coding for social determinants of health (SDOH), they are infrequently captured in electronic health records (EHRs). Most SDOH variables are still captured in the unstructured fields (i.e., free-text) of EHRs. In this study we attempt to evaluate a practical text mining approach (i.e., advanced pattern matching techniques) in identifying phrases referring to housing issues, an important SDOH domain affecting value-based healthcare providers.
Identification of social determinants of health using multi-label classification of electronic health record clinical notes.
Stemerman Rachel et al. JAMIA open 2021 4(3) ooaa069
Social determinants of health (SDH), key contributors to health, are rarely systematically measured and collected in the electronic health record (EHR). We investigate how to leverage clinical notes using novel applications of multi-label learning (MLL) to classify SDH in mental health and substance use disorder patients who frequent the emergency department.
Evaluating Primary Care Providers' Readiness for Delivering Genetic and Genomic Services to Underserved Populations.
Sharma Yashoda et al. Public health genomics 2021 1-10
We evaluated the readiness of primary care providers at a Federally Qualified Health Center, the Community Health Center, Inc. (CHCI) for delivering genetic and genomic testing to underserved populations. Online survey questions focused on providers' education and training in basic and clinical genetics, familiarity with current genetic tests, and needs for incorporating genetics and genomics into their current practice.Fifty of 77 (65%) primary care providers responded to the survey. Less than half received any training in basic or clinical genetics (40%), were familiar with specific genetic tests (36%), or felt confident with collecting family health history (44%), and 70% believed patients would benefit from genetic testing.Despite knowledge gaps, respondents recognized the value and need to bring these services to their patients.