Surveillance of COVID-19 vaccine safety among elderly persons aged 65 years and older

BackgroundMonitoring safety outcomes following COVID-19 vaccination is critical for understanding vaccine safety especially when used in key populations such as elderly persons age 65 years and older who can benefit greatly from vaccination. We present new findings from a nationally representative early warning system that may expand the safety knowledge base to further public trust and inform decision making on vaccine safety by government agencies, healthcare providers, interested stakeholders, and the public. MethodsWe evaluated 14 outcomes of interest following COVID-19 vaccination using the US Centers for Medicare & Medicaid Services (CMS) data covering 30,712,101 elderly persons. The CMS data from December 11, 2020 through Jan 15, 2022 included 17,411,342 COVID-19 vaccinees who received a total of 34,639,937 doses. We conducted weekly sequential testing and generated rate ratios (RR) of observed outcome rates compared to historical (or expected) rates prior to COVID-19 vaccination. FindingsFour outcomes met the threshold for a statistical signal following Pfizer-BioNTech vaccination including pulmonary embolism (PE; RR=1.54), acute myocardial infarction (AMI; RR=1.42), disseminated intravascular coagulation (DIC; RR=1.91), and immune thrombocytopenia (ITP; RR=1.44). After further evaluation, only the RR for PE still met the statistical threshold for a signal; however, the RRs for AMI, DIC, and ITP no longer did. No statistical signals were identified following vaccination with either the Moderna or Janssen vaccines. InterpretationThis early warning system is the first to identify temporal associations for PE, AMI, DIC, and ITP following Pfizer-BioNTech vaccination in the elderly. Because an early warning system does not prove that the vaccines cause these outcomes, more robust epidemiologic studies with adjustment for confounding factors, including age and nursing home residency, are underway to further evaluate these signals. FDA strongly believes the potential benefits of COVID-19 vaccination outweigh the potential risks of COVID-19 infection.

Smartphone electrocardiogram for detecting atrial fibrillation after a cerebral ischaemic event: a multicentre randomized controlled trial.

AIMS: Atrial fibrillation (AF) is a preventable cause of ischaemic stroke but it is often undiagnosed and undertreated. The utility of smartphone electrocardiogram (ECG) for the detection of AF after ischaemic stroke is unknown. The aim of this study is to determine the diagnostic yield of 30-day smartphone ECG recording compared with 24-h Holter monitoring for detecting AF ≥30 s. METHODS AND RESULTS: In this multicentre, open-label study, we randomly assigned 203 participants to undergo one additional 24-h Holter monitoring (control group, n = 98) vs. 30-day smartphone ECG monitoring (intervention group, n = 105) using KardiaMobile (AliveCor®, Mountain View, CA, USA). Major inclusion criteria included age ≥55 years old, without known AF, and ischaemic stroke or transient ischaemic attack (TIA) within the preceding 12 months. Baseline characteristics were similar between the two groups. The index event was ischaemic stroke in 88.5% in the intervention group and 88.8% in the control group (P = 0.852). AF lasting ≥30 s was detected in 10 of 105 patients in the intervention group and 2 of 98 patients in the control group (9.5% vs. 2.0%; absolute difference 7.5%; P = 0.024). The number needed to screen to detect one AF was 13. After the 30-day smartphone monitoring, there was a significantly higher proportion of patients on oral anticoagulation therapy at 3 months compared with baseline in the intervention group (9.5% vs. 0%, P = 0.002). CONCLUSIONS: Among patients ≥55 years of age with a recent cryptogenic stroke or TIA, 30-day smartphone ECG recording significantly improved the detection of AF when compared with the standard repeat 24-h Holter monitoring.

SARS-CoV-2 Control on a Large Urban College Campus Without Mass Testing

ObjectiveA small percentage of universities and colleges conduct mass SARS-CoV-2 testing. However, universal testing is resource-intensive, strains national testing capacity, and false negative tests can encourage unsafe behaviors. ParticipantsA large urban university campus. MethodsVirus control centered on three pillars: mitigation, containment, and communication, with testing of symptomatic and a random subset of asymptomatic students. ResultsRandom surveillance testing demonstrated a prevalence among asymptomatic students of 0.4% throughout the term. There were two surges in cases that were contained by enhanced mitigation and communication combined with targeted testing. Cumulative cases totaled 445 for the term, most resulting from unsafe undergraduate student behavior and among students living off-campus. A case rate of 232/10,000 undergraduates equaled or surpassed several peer institutions that conducted mass testing. ConclusionsAn emphasis on behavioral mitigation and communication can control virus transmission on a large urban campus combined with a limited and targeted testing strategy.

The Pitfall of Utilizing a Commercial Biochemical Yeast Identification Kit to Detect Candida auris.

Candida auris is an emerging pathogenic yeast responsible for nosocomial infections with high mortality, on a global scale. A 65-year-old woman with hypovolemic shock and severe metabolic acidosis was intubated and admitted to the intensive care unit (ICU). Shortly after admission, she developed ventilator-associated pneumonia caused by multidrug-resistant Acinetobacter baumannii, which necessitated treatment with high-dose ampicillin-sulbactam. Two weeks later, a yeast was cultured from her blood. It formed pale pink colonies on CHROMagar Candida medium and produced predominantly oval budding yeast cells with the occasional rudimentary pseudohyphae on cornmeal agar. ID 32 C identified the yeast as Candida sake However, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) and sequencing of the D1/D2 region of the 28S rRNA gene identified the yeast as C. auris.