Changes in sleep-wake patterns, circadian timing, and mood in Australian teens during the COVID-19 pandemic

During the COVID-19 pandemic, schools rapidly transitioned from in-person to remote learning. We examined sleep- and mood-related changes in early adolescents, before and after this transition to assess the impact of in-person vs. remote learning. Sleep-wake timing was measured using wrist-actigraphy and sleep diaries over 1–2 weeks in Year 7 students (age M±SD =12.79±0.42 years) during in-person learning (n=28) and remote learning (n=58;n=27 were studied in both conditions). Circadian timing was measured under a single condition in each individual using salivary melatonin (Dim Light Melatonin Onset;DLMO). Online surveys assessed mood (PROMIS Pediatric Anxiety and Depressive Symptoms) and sleepiness (Epworth Sleepiness Scale – Child and Adolescent) in each condition. During remote vs. in-person learning: (i) on school days, students went to sleep 26 min later and woke 49 min later, resulting in 22 min longer sleep duration (all p<0.0001);(ii) DLMO time did not differ significantly between conditions, although participants woke at a later relative circadian phase (43 minutes, p=0.03) during remote learning;(iii) participants reported significantly lower sleepiness (p=0.048) and lower anxiety symptoms (p=0.006). Depressive symptoms did not differ between conditions. Changes in mood symptoms were not mediated by changes in sleep timing. Although remote learning had the same school start times as in-person learning, removing morning commutes likely enabled adolescents to sleep longer, wake later, and to wake at a later circadian phase. These results indicate that remote learning, or later school start times, may extend sleep duration and improve some subjective symptoms in adolescents.

Factors Influencing Covid-19 Risk: Insights from Molnupiravir Exposure-Response

Background: Exposure-response (E-R) models were developed for the primary endpoint of hospitalization or death in COVID-19 patients from the Phase 3 portion of the MOVe-OUT study (Clinicaltrials.gov NCT04577797). Beyond dose, these models can identify other determinants of response, highlight the relationship of virologic response with clinical outcomes, and provide a basis for differential efficacy across trials. Method(s): Logistic regression models were constructed using a multi-step process with influential covariates identified first using placebo arm data only. Subsequently the assessment of drug effect based on drug exposure was determined using placebo and molnupiravir (MOV) arm data. To validate the models, the rate of hospitalization/death was predicted for published studies of COVID-19 treatment. All work was performed using R Version 3.0 or later. Result(s): A total of 1313 participants were included in the E-R analysis, including subjects having received MOV (N=630) and placebo (N=683). Participants with missing baseline RNA or PK were excluded (79 from MOV and 16 from placebo arms). The covariates shown to be significant determinants of response were baseline viral load, baseline disease severity, age, weight, viral clade, and co-morbidities of active cancer and diabetes. Day 5 and Day 10 viral load were identified as strong on-treatment predictors of hospitalization/death, pointing to sustained high viral load as driving negative outcomes. Estimated AUC50 was 19900 nM*hr with bootstrapped 95% C.I. of (9270, 32700). In an external validation exercise based on baseline characteristics, the E-R model predicted the mean (95% CI) placebo hospitalization rates across trials of 9.3% (7.6%, 11.7%) for MOVe-OUT, 7.2% (5.3%, 9.8%) for the nirmatrelvir/ritonavir EPIC-HR trial, and 3.2% (1.9%, 5.5%) for generic MOV trials by Aurobindo and Hetero, consistent with the differing observed placebo rates in these trials. The relative reduction in hospitalization/death rate predicted with MOV treatment (relative to placebo) also varied with the above patient populations. Conclusion(s): Overall, the exposure-response results support the MOV dose of 800 mg Q12H for treatment of COVID-19. The results further support that many clinical characteristics impacted hospitalization rate beyond drug exposures which can vary widely across studies. These characteristics also influenced the magnitude of relative risk reduction achieved by MOV in the MOVe-OUT study.

Immune-Viral Dynamics Modeling of the Basis for Individual Variation in Covid-19

Background: Viral dynamics models provide mechanistic insights into viral disease and therapeutic interventions. A detailed, mechanistic model of COVID-19 was developed and fit to data from molnupiravir (MOV) trials to characterize the SARS-CoV-2 viral dynamics in MOV-treated and untreated participants and describe the basis for variation across individuals. Method(s): An Immune-Viral Dynamics Model (IVDM) incorporating mechanisms of viral infection, viral replication, and induced innate and adaptive immune response described the dynamics of viral load (VL) from pooled data from MOV Phase 2 and 3 trials (N=1958). Population approaches were incorporated to estimate variation across individuals and to conduct an extensive covariate analysis. Nineteen parameters in a system of five differential equations described SARS-CoV-2 viral dynamics in humans. Six population parameters were successfully informed through fitting to observed trial data while the remaining parameters were fixed based on literature values or calibrated via sensitivity analysis. Result(s): Final viral dynamics and immune response parameters were all estimated with high certainty and reasonable inter-individual variabilities. The model captured the viral load profiles across a wide range of subpopulations and predicted lymphocyte dynamics without using this data to inform the parameters, suggesting inferred immune response curves from this model were accurate. This mechanistic representation of COVID-19 disease indicated that the processes of cellular infection, viral production, and immune response are in a time-varying, non-equilibrium state throughout the course of infection. MOV mechanism of action was best described as an inhibitory process on the infectivity term with estimated AUC50 of 10.5 muM*hr. Covariates identified included baseline viral load on infectivity and age, baseline disease severity, viral clade, baseline viral load, and diabetes on immune response parameters. Greater variation was identified for immune parameters than viral kinetic parameters. Conclusion(s): These findings show that the variation in the human response (e.g., immune response) is more influential in COVID-19 disease than variations in the virus kinetics. The model indicates that immunocompromised patients (due to HIV, organ transplant, active cancer, immunosuppressive therapies) develop an immune response to SARS-CoV-2, albeit more slowly than in immunocompetent, and MOV is effective in further reducing viral loads in the immunocompromised.

AI-enabled multiscale modeling of SARS-CoV-2 replication transcription complex

The severe acute respiratory syndrome coronavirus-2 (SARSCoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular machine. Consequently, we develop an innovative workflow that bridges the gap between these resolutions, using mesoscale fluctuating finite element analysis (FFEA) continuum simulations and a hierarchy of AI-methods that continually learn and infer features for maintaining consistency between AAMD and FFEA simulations. We leverage a multi-site distributed workflow manager to orchestrate AI, FFEA, and AAMD jobs, providing optimal resource utilization across HPC centers. Our study provides unprecedented access to study the SARS-CoV-2 RTC machinery, while providing general capability for AI-enabled multi-resolution simulations at scale. We acknowledge funding from NIH P41-GM10460, DOE CSGF (DE-FG02-97ER25308), Exascale Computing Project (17-SC-20-SC) and National Virtual Biotechnology Laboratory.Copyright © 2023 The American Society for Biochemistry and Molecular Biology, Inc.

Molnupiravir Exposure-Response Relationships for Clinical Outcomes, Virology, and Mechanism of Action Biomarkers Are Consistent in Treatment of Covid-19

BACKGROUND: Exposure-response (E-R) analysis supported molnupiravir phase 3 dose selection based on viral load (VL) and mechanism of action (MOA) markers from phase 2.1 This analysis evaluated how well these biomarkers predict the E-R for hospitalization or death in phase 3. METHOD(S): The following E-R models were developed and compared: (1) logistic regression of the primary outcome (hospitalization or death) from phase 3, (2) VL change from baseline (CFB) from phase 2 and 3, and (3) low frequency nucleotide substitutions (LNS), a measure of MOA, from phase 2. Individual estimates of exposure were derived from population PK modeling of sparse samples collected in all patients. All work was performed using R v3.0 or later. RESULT(S): All E-R relationships were best represented by an Emax model with AUC50 estimates of 19,900, 10,260, and 4,390 nM*hr for hospitalization, day 5 VL CFB, and LNS mutation rate, respectively. Normalized E-R relationships were overlaid, illustrating consistency in E-R shape (Figure). Plasma NHC AUC0-12 was identified as the PK driver. Patients at 800 mg achieved near maximal response. CONCLUSION(S): E-R results support the dose of 800 mg Q12H for treatment of COVID-19. E-R relationships for MOA and virology biomarkers were consistent with the clinical E-R. (Figure Presented).

Molnupiravir Exposure-Response of Clinical Outcomes in Treatment of Covid-19

BACKGROUND: The goal of this analysis was to investigate the relationship of molnupiravir pharmacokinetics (PK) and clinical outcomes (primary endpoint of hospitalization or death) in patients with COVID-19 in the phase 3 cohort of MOVe-OUT (clinicaltrials.gov NCT04577797).1 METHODS: Logistic regression models were constructed using a multi-step process with influential covariates identified first using placebo arm data only and subsequently assessment of drug effect as a function of exposures evaluated using placebo and MOV arm data. Individual estimates of exposure were derived from population PK modeling of sparse samples collected in all patients. All work was performed using R v3.0 or later. RESULT(S): A total of 1,313 participants were included in the exposure-response (E-R) analysis, including subjects on MOV (N = 630) and placebo (N = 683). Participants with missing PK or baseline RNA were excluded (79 from MOV and 16 from placebo arms). The covariates shown to be significant determinants of response were baseline viral load, baseline disease severity, age, weight, viral clade, active cancer, and diabetic risk factors. An additive AUC-based Emax model with a fixed hill coefficient of 1 best represented exposure-dependency in drug effect. Estimated AUC50 was 19,900 nM*hr with bootstrapped 95% confidence interval of (9,270, 32,700). Patients at 800 mg achieved near maximal response, which was larger than the response projected for 200 or 400 mg. CONCLUSION(S): Overall, the E-R results support the MOV dose of 800 mg Q12H for treatment of COVID-19. Many patient characteristics, beyond drug exposures, impacted the risk of hospitalization or death.

Technology in Mental Health: Foundations of Clinical Use

Technology in Mental Health focuses on the responsible integration of technology into therapy in a world affected by COVID. Author Jessica Stone discusses the pandemic's effects on the mental health field, historical fundamentals, and possible future implications. Chapters also explore legal and ethical considerations as well as educational and supervision needs. Seasoned and new clinicians alike will find valuable information in these pages as they progress from traditional to modern to post-COVID mental health treatment. © 2023 Jessica Stone. All rights reserved.

Teaching in the time of COVID-19: A biological systems theory approach

In 2020, schools around the United States and globally closed to in-person instruction in response to the COVID-19 pandemic. This study, embedded in ongoing research supported by a United States Department of Education Jacob K. Javits Gifted and Talented Education Award, investigated changes in roles, relationships, and educational activities resulting from the pandemic as perceived by educators in one rural and low SES Appalachian primary school. Using Bronfenbrenner’s (1977;1979;2001) Bioecological Theory of Human Development, this study examined instructional modifications (proximal processes) resulting from the pandemic (chronosystem) in the school and home (microsystem context) and the development of teachers, parents, and students (persons) in response to those changes. Survey data were collected pre- and post-pandemic onset. Results of this mixed-methods study indicated teachers perceived the pandemic as influencing what they taught, how they taught, and the roles of and relationships between teachers, parents, and students. Teachers adapted to the changing educational environment developing proficiency in online tools and skills to enhance communication. Parents assumed a more prominent role in their K-2 student’s schooling to ensure students logged in and were active online, paid attention while in class, and completed their assignments at home. These remote learning environments, which naturally distanced teachers from their students, coupled with uncertain parental involvement, challenged teachers in their formative assessments of student knowledge. While some students thrived with increased support from attentive parents—many students, particularly those already at-risk or in homes where internet or parental support were lacking—were adversely affected, thus widening the achievement gap. Copyright © 2022 Brigandi, Spillane, Rambo-Hernandez and Stone.

TOCILIZUMAB in COMBINATION with 8 WEEKS of PREDNISONE for GIANT CELL ARTERITIS

Background: Even with the use of tocilizumab (TCZ), signifcant glucocorticoid exposure (usually ≥ 6 months) continues to be an important problem in giant cell arteritis (GCA). Objectives: We aimed to evaluate the efficacy and safety of tocilizumab (TCZ) in combination with 2 months of prednisone in a group of patients with GCA. Methods: We conducted a prospective, single arm, open-label study of TCZ in combination with 2 months of prednisone for new-onset and relapsing GCA patients with active disease (ClinicalTrials.gov Identifer NCT03726749). GCA diagnosis required confrmation by temporal artery biopsy or vascular imaging. Active disease was defned as presence of cranial or polymyalgia rheumat-ica symptoms necessitating treatment within 6 weeks of baseline. All patients received TCZ 162 mg subcutaneously every week for 12 months and an 8-week prednisone taper starting between 20 mg and 60 mg daily (Figure 1). The primary endpoint, sustained prednisone-free remission, was defned as absence of relapse from induction of remission up to week 52 while adhering to the prednisone taper. Relapse was defned as the recurrence of symptoms of GCA requiring treatment intensifcation regardless of erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) levels. Safety was also evaluated. 8-week prednisone taper starting between 20 mg and 60 mg Primary endpoint Prednisone-free remission at week 52 Figure 1. Clinical Trial Schema Results: Between 11/2018 and 11/2020 we enrolled 30 patients (mean age 74 years, 60% females, 50% new-onset disease, 77% temporal artery biopsy-proven, 47% imaging-proven). The mean ESR and CRP at screening were 45 mm/hour and 48 mg/L, respectively. The initial prednisone dose was 60 mg (n = 7), 50 mg (n = 1), 40 mg (n = 7), 30 mg (n = 6) and 20 mg (n = 9). All patients entered remission within 4 weeks of baseline. The primary endpoint was achieved by 23 (77%) patients (Table 1). The mean (SD) cumulative prednisone dose in these 23 patients was 1052 (390) mg. After a mean period of 16 weeks, 7 (23%) patients relapsed (Table 1). All relapses but one occurred after the completion of the study prednisone taper. Overall, 6 of the 7 patients with relapse received a second prednisone taper over 8 weeks. Of these 6 patients, 4 achieved and maintained remission for the remainder of the trial period, and 2 withdrew from the study after having a second relapse. One patient with relapse received a second prednisone taper over 26 weeks and stayed in remission until the end of the study. The mean (SD) cumulative prednisone dose in the 7 patients with relapse was 1883 (699) mg (Table 1). Overall, 4 (13%) participants developed a serious adverse event (Table 1). No cases of ischemia-related visual symptoms including permanent vision loss occurred during the study. Table 1. Efficacy and Safety Outcomes GCA patients (n = 30) Efficacy Sustained, prednisone-free remission by week 52 23.0 (76.7) Cumulative prednisone dose (mg) at week 52, mean (SD) 1051.5 (390.3) Relapse 70 (23.3) Time to relapse, weeks: mean (SD) 15.8 (14.7) Prednisone dose (mg/day) at relapse, mean (SD) 2.1 (5.2) Cumulative prednisone dose (mg), mean (SD) 1883.1 (699.2) Clinical manifestations at relapse Cranial symptoms 4 out of 7 patients schemic visual symptoms 0 out of 7 patients PMR symptoms 4 out of 7 patients Safety Serious adverse events 4.0 (13.3) Cellulitis 1 COVID-19 1 Fragility fracture 1 Cholecystitis 1 Values represent number and (%) unless otherwise specifed. SD, standard deviation;PMR, polymyalgia rheumatica Conclusion: These results suggest that 12 months of TCZ in combination with 8 weeks of prednisone could be efficacious for inducing and maintaining disease remission in patients with GCA. Confrmation of these fndings in a randomized controlled trial is required.

OUTCOMES during and after LONG-TERM TOCILIZUMAB TREATMENT in PATIENTS with GIANT CELL ARTERITIS

Background: Data on the long-term efficacy and safety of tocilizumab (TCZ) for giant cell arteritis (GCA), including incidence and timing of disease relapse after TCZ discontinuation, is limited. Objectives: We aimed to evaluate the long-term outcomes of GCA patients treated with TCZ in a real-world setting. Methods: Retrospective analysis of GCA patients treated with TCZ for >9 months at a single center between 2010-2021. Time to relapse and annualized relapse rate during and after TCZ treatment, prednisone use and safety were assessed. Relapse was defned as the re-appearance of clinical manifestations of GCA that required treatment intensifcation regardless of the erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP) levels. The duration of TCZ treatment was determined as per the best clinical judgement of the treating rheumatologist. Results: A total of 57 GCA patients were followed for a mean (SD) period of 3.4 (1.7) years. Baseline characteristics and treatments received are shown in Table 1. Patients were maintained on their initial TCZ course for a mean (SD) period of 2.0 (1.3) years. The initial TCZ course lasted >12 months in 50 (88%) patients. During the initial TCZ course, 8 (14.0%) patients relapsed. Kaplan-Meier (KM) estimated relapse rates on TCZ were 10.5% and 14.9% at 12 and 18 months, respectively (Figure 1A). TCZ was discontinued due to long-term remission in 37 (64.9%) patients and after an adverse event in 6 (10.5%) patients. Of the 43 patients stopping TCZ due to remission or adverse event, 19 (44.2%) subsequently relapsed. KM estimated relapse rates after TCZ discontinuation were 30.4% and 44.0% at 12 and 18 months, respectively (Figure 1B). Overall, 12 patients received more than one TCZ course. The aggregation of all TCZ courses (mean 2.5 years) and all periods off TCZ following the initial TCZ treatment (mean 0.9 years) showed that 11 (19.3%) patients relapsed while on TCZ and 20 (35.1%) patients relapsed during time off TCZ. An analysis adjusting for age, sex, prednisone dose at initiation of frst TCZ course, and disease type (new onset vs. relapsing) at initiation of frst TCZ course showed an annualized relapse rate (95% CI) of 0.1 (0.0-0.2) during TCZ treatment and 0.4 (0.3-0.7) off TCZ (rate ratio 0.2, p<0.0001). By the end of follow up, 42 (73.7%) patients were able to wean off prednisone. During the study, 12 serious adverse events occurred in 11 (19.3%) patients. Among those 12 events, 3 (25%) were related or possibly related to TCZ exclusively (i.e., soft tissue infection, bacteremia, and COVID-19), 3 (25%) to prednisone exclusively (i.e., osteoporotic fracture, diabetic ketoacidosis and stroke), and 2 (16.7%) to either TCZ or prednisone (i.e., pneumonia and sepsis). Conclusion: Long-term TCZ treatment was efficacious in maintaining disease remission and sparing the use of prednisone in patients with GCA. Over 40% of patients stopping TCZ after long-term remission or adverse event relapsed following TCZ discontinuation.

Quality Improvement Developments Following Pediatric Resuscitation and VA Extracorporeal Membrane Oxygenation Support due to a Massive Intentional Antidepressant Overdose

Introduction: The COVID-19 pandemic caused a significant increase in suicide attempts in teenagers. Fluoxetine and Wellbutrin have been prescribed to adolescents to treat depression. Overdosing on these medications can cause seizures, arrhythmias, and cardiogenic shock. We report on a patient who presented with a normal physical assessment following a massive antidepressant drug overdose, but quickly deteriorated, and required VA Extracorporeal Membrane Oxygenation (ECMO). Gaps identified in this case prompted us to assess our ECPR protocol, which led to areas for quality improvement. Case Review: A teenage male presented to our ED after intentionally ingesting Fluoxetine, Wellbutrin, and Hydroxyprogesterone. Fluid boluses, vasopressor infusions and multiple doses of epinephrine were administered, but his hemodynamic instability persisted. Concerns regarding cannulation, team activation and coordination of care during ECPR were areas identified as requiring improvement during a case review. The team was activated and cannulated the patient for VA ECMO. At hour eighty-five, he was hemodynamically stable, including normal sinus rhythm and resolved hypotension, and was removed from ECMO. He was successfully extubated, weaned to room air, and discharged with plans for outpatient therapy. Quality Improvement: An updated process for notifying team members for ECPR cannulation was implemented. Simulation scenarios, which are held quarterly, were developed, with clearly delineated roles, and emphasis on timing of chest compressions with minimal pauses during cannulation. Annual ECPR web-based education is mandatory. Improvements in the time to cannulation and team member interactions were noted during subsequent ECPR scenarios. Timing of team notification and cannulations continues to be tracked.

Telemental Health Play Therapy

This chapter intends to introduce the reader to the pre, peri, and post eras of teleservices. There is a rich and surprising history of teleservices, beginning with telemedicine in the early 1900s, which informs us a bit about how we have arrived in an amazing time in history: the ability for continuity of care despite a global pandemic. The COVID-19 pandemic era of telemental health services is discussed to review the process of this rapid adoption of providing services digitally, the realizations many have experienced, and the pros and cons of such provisions. Finally, the potential future of the incorporation of teleservices in many arenas, but specifically for mental health, with be discussed. © 2022 selection and editorial matter, Jessica Stone individual chapters, the contributors.

Portable Ultraviolet-C Chambers for Inactivation of SARS-CoV-2

The goal of this project was to create and optimize the performance of portable chambers for reliable ultraviolet (UV) disinfection of personal protective equipment (PPE) and enable its safe reuse. During unforeseen times of high demand for PPE, such as during the coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), single-use PPE supply can be quickly depleted. UV radiation has been shown to disinfect materials with high efficacy. This paper reports the design and construction of two 280 nm ultraviolet-C (UV-C) disinfection chambers in the form of portable chambers with 46 cm x 46 cm x 46 cm interior dimensions, one using light-emitting diodes and the other using mercury vapor lamps. This paper summarizes and presents a review of SARS-CoV-2 UV deactivation research during 2020 to 2021. Additionally, this paper discusses efforts to increase the uniformity and overall intensity of the UV-C radiation within the chambers through the installation of a UV-reflective, porous polytetrafluoroethylene (PTFE) material. A calculator prototype was additionally designed to calculate the reduction of SARS-CoV-2 as a result of UV-C disinfection, and the prototype code is presented. The paper describes the selection of UV-C radiation sources for the chambers and the chambers' mechanical and electrical design, PTFE installation, testing, and safety considerations.

Remote training using augmented reality on surgical phantoms

Introduction & Objectives: Workshops with hands-on training using phantoms (anatomical models) are well-known methods for training clinicians and residents. However, during the Covid-19 pandemic it was not possible to attend workshops owing to the restrictions imposed by the lock-down. As a result, both the medical device industry and clinicians were not able to keep current with their skills. We introduce a novel method of education using augmented reality that virtually places the trainer (proctor) in the same room as the student during the procedure.(Figure Presented)A training simulation was created where a proctor trained a student in transperineal local anesthesia and biopsy using a prostate phantom. The hardware platform consisted of a headset containing see-through optic displays with an imbedded webcam. The image from the ultrasound machine was displayed in the optics of the headset, allowing the proctor to view the ultrasound image while looking at the phantom and his hands simultaneously (figure). A web-based software program was developed that displayed the ultrasound image and the video of the proctor’s hands (captured by the imbedded web cam) in a stacked format. These images were transmitted to the student (in a different room) who also wore a comparable headset. Both proctor and student had an ultrasound unit (BK Medical 5000 and 3000 with model 9048 probes) and prostate phantoms (SIM, Inc.). The proctor then demonstrated how to perform the local anesthesia and transperineal biopsy procedure, step by step, while the student observed these in his headset. After each step of the procedure the proctor changed the active feed so he could watch in his own headset the student performing that same step and further instruct him. s EAU22 – 37th Annual EAU Congress Eur Urol Suppl 2022;81(S 1):S1769 Results: The Remote Training Platform allowed the proctor to successfully demonstrate the prostate block and transperineal biopsy techniques to the student. The student was able to ask the proctor for instructions while the proctor was able to annotate additional information on the student’s ultrasound. Successful completion of both procedures was accomplished. Conclusions: The beta testing of this Remote Training Platform demonstrated that augmented reality combined with dedicated hardware and software could provided an efficient means of training physicians in new technology. Eliminating the need for the proctor to travel could increase the safety and efficiency for the introduction of new medical devices and resident education.

Use of Immune-Viral Dynamics Modeling to Understand Molnupiravir Drug Effect for COVID-19

Background. Molnupiravir (MOV) is an orally administered ribonucleoside prodrug of β-D-N4-hydroxycytidine (NHC) against SARS-CoV-2. Here we present viral dynamics analysis of Phase 2 clinical virology data to inform MOV Phase 3 study design and development strategy. Methods. An Immune-Viral Dynamics Model (IVDM) was developed with mechanisms of SARS-CoV-2 infection, replication, and induced immunity, which together describe the dynamics of viral load (VL) during disease progression. Longitudinal virology data from ferret studies (Cox, et al. Nat. Microbiol 2021:6-11) were used to inform IVDM, which was further translated to human by adjusting parameter values to capture clinical data from MOVe-IN/MOVe-OUT studies. Different placements of drug effects (on viral infectivity vs. productivity) and representations of immune response were explored to identify the best ones to describe data. A simplified 95% drug effect was implemented to represent a highly effective dose of MOV. Results. IVDM showed data were best described when MOV acts on viral infectivity, consistent with the error catastrophe mechanism of action. A cascade of innate and adaptive immune response and a basal level activation enabled durable immunity and continued viral decay after treatment end. IVDM reasonably describes VL and viral titer data from animals and humans. Influence of MOV start time was explored using simulations. Consistent with the ferret studies, simulations showed when treatment is started within the first week post infection, MOV reduces viral growth, resulting in a lower and shortened duration of detectable VL. When started later (e.g. >7 days since symptom onset), the magnitude of drug effect is substantially diminished in a typical patient with an effective immune response which reduces VL prior to treatment start. Further work is needed to model response in patients with longer term infection, where MOV drug effects may have more persistent utility. Conclusion. A COVID-19 IVDM developed using multiscale MOV virology data supports drug action on viral infectivity and importance of interplay of treatment and immune response and can describe infection time course and drug effect. IVDM provided mechanistic interpretations for VL drug effect in clinical studies.

Multi-centre development of a secure, cloud based, patient to clinician, neurology video transfer, classification and management syste

Purpose: A government funded;interactive cloud storage platform (www.vcreate.tv/neuro) allowing patients and carers to upload video and linked metadata for neurological diagnosis was established during the Covid-19 pandemic. We describe the utility for epilepsy and paroxysmal disorders in 16 centres with the first centre active from 01/05/2020. Method: Users are invited to register and utilise a password and passcode for access. Videos are uploaded with a structured history. The clinician classifies seizure type, syndrome, aetiology or other diagnosis using drop-down menus. Users and clinicians complete online evaluations. Postcode allows linkage to user index of deprivation score. Consents for teaching by the local clinical team and research within a national neurology video research database with research ethics approval are optional. All data, except the video file, transfer to the electronic patient record. Result: To 24/03/2021, 4582 video uploads (4024 paediatric, 558 adult), 1889 patients (1594 paediatric, 295 adult). 400-600 new videos per month. 323 physician and nurse users. Deprivation scores indicate equitable use across socio-economic groups. Paediatric classification: non-epileptic 55%, epileptic (36.5%), unknown (8.5%). Adult: non-epileptic 73.5% (34% dissociative, 41% movement disorders), epileptic 11%, unknown 15.5%. Paediatric seizure types include: focal impaired awareness (19%), generalised tonic clonic (18%), focal clonic (17%), epileptic spasms (13%). Non-epileptic events: tics (13%), normal behaviour (12%), sleep myoclonus (10%) gratification (8%), dissociative (5%). >95% carers ranked the system positively. Clinicians report video prevented face-to-face review in 57%, investigations in 44% and reduced time to diagnosis in 97%. Median time to review video and classify was 5 minutes. Conclusions: Remote care is facilitated, investigations prevented or prioritised, with rapid diagnosis and efficiencies in the patient pathway. A rapidly growing teaching resource and research database for semiology and machine learning diagnostics for paroxysmal disorders has been established. We plan to establish the system in low-income countries without cost.

Virtual hands-on training of image-guided urologic procedures during the COVID-19 pandemic

INTRODUCTION AND OBJECTIVE: Image-guided training traditionally requires instructors and students to work in close proximity to impart skills and master new medical devices. The classical method of training has been prohibitive during the Covid-19 pandemic. We determined the value of using virtual training on inanimate models that closely replicate the prostate gland on ultrasound and MRI. METHODS: Six urologic procedures which included the injection of a rectal hydrogel spacer, transperineal biopsy, mpMRI fusion biopsy (2 different devices), Cesium-131 implant and focal brachytherapy were taught by urology and radiation oncology experts via a webinar (example in Figure 1). The prostate phantoms were designed to maximize the learning experience and included MRI visible lesions. The training lasted 30 minutes for each procedure. Seven faculty and 110 attendees participated. Survey Monkey was used to assess the education experience of both groups. RESULTS: 31 attendees and the 7 faculty completed the survey. All the faculty responded the phantom simulated human tissue, was easy to set up, and was superior to using a live patient (Table 1). 42.8% believed that 30 minutes was adequate for training. 100% of the attendees also believed the phantom simulated human tissue (Table 1). In contrast to the faculty, only 19.4% of attendee's believed 30 minutes was adequate. 90.3% of the attendees reported that the prostate phantom could substitute for training on a live patient. CONCLUSIONS: This was the first demonstration of remote learning on a physical prostate phantom. While the faculty had more confidence that 30 minutes training was adequate, the attendees requested their own phantom for training. The Covid-19 pandemic provided the opportunity to introduction a novel training approach. Expansion of this method to more complex procedures could substitute for teaching on live patients. Providing phantoms to instructors and attendees represents a future expansion of remote learning.