Complete genome sequence of Azrael100, a V cluster mycobacteriophage.

Azrael100, a cluster V siphoviral mycobacteriophage, was isolated from a garden in Johannesburg, South Africa. It can infect and lyse Mycobacterium smegmatis mc2155. The double-stranded DNA genome contains 78,063 base pairs with a GC content of 56.9%, with 141 predicted open reading frames, 23 tRNAs, and one tmRNA.

Evaluation of a human mucosal tissue explant model for SARS-CoV-2 replication.

With the onset of COVID-19, the development of ex vivo laboratory models became an urgent priority to study host-pathogen interactions in response to the pandemic. In this study, we aimed to establish an ex vivo mucosal tissue explant challenge model for studying SARS-CoV-2 infection and replication. Nasal or oral tissue samples were collected from eligible participants and explants generated from the tissue were infected with various SARS-CoV-2 strains, including IC19 (lineage B.1.13), Beta (lineage B.1.351) and Delta (lineage B.1.617.2). A qRT-PCR assay used to measure viral replication in the tissue explants over a 15-day period, demonstrated no replication for any viral strains tested. Based on this, the ex vivo challenge protocol was modified by reducing the viral infection time and duration of sampling. Despite these changes, viral infectivity of the nasal and oral mucosa was not improved. Since 67% of the enrolled participants were already vaccinated against SARS-CoV-2, it is possible that neutralizing antibodies in explant tissue may have prevented the establishment of infection. However, we were unable to optimize plaque assays aimed at titrating the virus in supernatants from both infected and uninfected tissue, due to limited volume of culture supernatant available at the various collection time points. Currently, the reasons for the inability of these mucosal tissue samples to support replication of SARS-CoV-2 ex vivo remains unclear and requires further investigation.

Mobile phone apps for family caregivers: A scoping review and qualitative content analysis.

BACKGROUND: The growth of mHealth apps has been exponential in recent years, but there is limited knowledge regarding the availability, functionality, and quality of apps to support family caregivers. Our objectives were to identify the apps currently available to support family caregivers and to analyze the app functions and evaluation claims. METHODS: This scoping review was conducted across the iOS, Android, and Windows Phone app stores in three steps: (1) electronic app search; (2) iterative inclusion and exclusion criteria development; (3) mixed-method analysis of app characteristics and evaluation claims. RESULTS: The search identified 1008 apps; 175 met our inclusion/exclusion criteria. Most apps offered either one (36%, 63/175) or two (41%, 71/175) specific functions, the most common of which were access to service and provider directories, providing patient-caring tips, and tools to facilitate daily activities associated with caring for a loved one. For fully two-thirds (67%, 118/175) of the identified apps, the functions serve to assist caregivers to support the care recipient as opposed to supporting the family caregivers themselves. CONCLUSIONS: The findings of this review indicate that, while a wide range of family caregiver apps are now available across the mHealth landscape, most apps offer limited functionality. Therefore, there is a need for multi-functionality to avoid the inherent challenges that caregivers may experience when navigating and managing multiple apps to meet all their various needs. Moreover, as this specific niche continues to develop, greater attention should be devoted to supporting family caregivers' own personal care needs as caregiver burden is a pressing challenge.

Out-of-hospital cardiac arrest volumes and characteristics during the COVID-19 pandemic.

AIM: The COVID-19 pandemic has significantly impacted Emergency Medical Services (EMS) operations throughout the country. Some studies described variation in total volume of out-of-hospital cardiac arrests (OHCA) during the pandemic. We aimed to describe the changes in volume and characteristics of OHCA patients and resuscitations in one urban EMS system. METHODS: We performed a retrospective cohort analysis of all recorded atraumatic OHCA in Marion County, Indiana, from January 1, 2019 to June 30, 2019 and from January 1, 2020 to June 30, 2020. We described patient, arrest, EMS response, and survival characteristics. We performed paired and unpaired t-tests to evaluate the changes in those characteristics during COVID-19 as compared to the prior year. Data were matched by month to control for seasonal variation. RESULTS: The total number of arrests increased from 884 in 2019 to 1034 in 2020 (p = 0.016). Comparing 2019 to 2020, there was little difference in age [median 62 (IQR 59-73) and 60 (IQR 47-72), p = 0.086], gender (38.5% and 39.8% female, p = 0.7466, witness to arrest (44.3% and 39.6%, p = 0.092), bystander AED use (10.1% and 11.4% p = 0.379), bystander CPR (48.7% and 51.4%, p = 0.242). Patients with a shockable initial rhythm (19.2% and 15.4%, p = 0.044) both decreased in 2020, and response time increased by 18 s [6.0 min (IQR 4.5-7.7) and 6.3 min (IQR 4.7-8.0), p = 0.008]. 47.7% and 54.8% (p = 0.001) of OHCA patients died in the field, 19.7% and 19.3% (p = 0.809) died in the Emergency Department, 21.8% and 18.5% (p = 0.044) died in the hospital, 10.8% and 7.4% (p = 0.012) were discharged from the hospital, and 9.3% and 5.9% (p = 0.005) were discharged with Cerebral Performance Category score ≤ 2. CONCLUSION: Total OHCA increased during the COVID-19 pandemic when compared with the prior year. Although patient characteristics were similar, initial shockable rhythm, and proportion of patients who died in the hospital decreased during the pandemic. Further investigation will explore etiologies of those findings.

Validation of the NUE Rule to Predict Futile Resuscitation of Out-of-Hospital Cardiac Arrest.

AIM: We validated the NUE rule, using three criteria (Non-shockable initial rhythm, Unwitnessed arrest, Eighty years or older) to predict futile resuscitation of patients with out-of-hospital cardiac arrest (OHCA). METHODS: We performed a retrospective cohort analysis of all recorded OHCA in Marion County, Indiana, from January 1, 2014 to December 31, 2019. We described patient, arrest, and emergency medical services (EMS) response characteristics, and assessed the performance of the NUE rule in identifying patients unlikely to survive to hospital discharge. RESULTS: From 2014 to 2019, EMS responded to 4370 patients who sustained OHCA. We excluded 329 (7.5%) patients with incomplete data. Median patient age was 62 years (IQR 49 - 73), 1599 (39.6%) patients were female, and 1728 (42.8%) arrests were witnessed. The NUE rule identified 290 (7.2%) arrests, of whom none survived to hospital discharge. CONCLUSION: In external validation, the NUE rule (Non-shockable initial rhythm, Unwitnessed arrest, Eighty years or older) correctly identified 7.2% of OHCA patients unlikely to survive to hospital discharge. The NUE rule could be used in EMS protocols and policies to identify OHCA patients very unlikely to benefit from aggressive resuscitation.

The availability of prior ECGs improves paramedic accuracy in recognizing ST-segment elevation myocardial infarction.

INTRODUCTION: Early and accurate identification of ST-elevation myocardial infarction (STEMI) by prehospital providers has been shown to significantly improve door to balloon times and improve patient outcomes. Previous studies have shown that paramedic accuracy in reading 12 lead ECGs can range from 86% to 94%. However, recent studies have demonstrated that accuracy diminishes for the more uncommon STEMI presentations (e.g. lateral). Unlike hospital physicians, paramedics rarely have the ability to review previous ECGs for comparison. Whether or not a prior ECG can improve paramedic accuracy is not known. STUDY HYPOTHESIS: The availability of prior ECGs improves paramedic accuracy in ECG interpretation. METHODS: 130 paramedics were given a single clinical scenario. Then they were randomly assigned 12 computerized prehospital ECGs, 6 with and 6 without an accompanying prior ECG. All ECGs were obtained from a local STEMI registry. For each ECG paramedics were asked to determine whether or not there was a STEMI and to rate their confidence in their interpretation. To determine if the old ECGs improved accuracy we used a mixed effects logistic regression model to calculate p-values between the control and intervention. RESULTS: The addition of a previous ECG improved the accuracy of identifying STEMIs from 75.5% to 80.5% (p=0.015). A previous ECG also increased paramedic confidence in their interpretation (p=0.011). CONCLUSIONS: The availability of previous ECGs improves paramedic accuracy and enhances their confidence in interpreting STEMIs. Further studies are needed to evaluate this impact in a clinical setting.