ABSTRACT
Background: Approximately one in eight Canadian males will be diagnosed with prostate cancer. Longer survivorship horizons and resource constraints are leading to increasing strain on current models of specialist-led follow-up care delivery. Nurse-led digital health innovations can reduce demand on specialists if co-designed with health care professionals (HCPs). Methods: Using human-centred design, the purpose of this exploratory qualitative study with ten HCPs was to characterize their experiences with prostate cancer (PCa) follow-up and virtual care to optimally situate a nurse-led clinic within this ecosystem. Results: HCPs highlight how current follow-up care can be fragmented, so the scope of a nurse-led clinic should focus on the management of care with referral as needed. Despite an ambivalence for telemedicine arising from its implementation during the COVID-19 pandemic, HCPs see potential for improved care through digital health but note several concerns. Burn-out, weakened patient-provider relationships, and creeping scope of responsibilities were identified as pain points. We provide a health ecosystem readiness checklist to improve odds of acceptability, appropriateness, and feasibility synthesized from six HCP-defined facilitators mapped onto Proctor’s outcomes. Facilitators include: functionality testing (acceptability), technical support and usability (adoption), expectation management (appropriateness), resource allocation (cost), staff readiness (feasibility), and staff training (penetration). Conclusion: Intentional and empathetic co-design with HCPs during the development of digital health innovations, such as digital therapeutics, is necessary to ensure that HCPs can benefit from, instead of being burdened from, the rising tide of digital health in their clinical responsibilities.
Subject(s)
COVID-19 , Pain , Prostatic NeoplasmsABSTRACT
Previous studies have described RT-LAMP methodology for the rapid detection of SARS-CoV-2 in nasopharyngeal/oropharyngeal swab and saliva samples. Here we describe the validation of an improved simple sample preparation method for Direct SARS-CoV-2 RT-LAMP, removing the need for RNA extraction, using 559 swabs and 86,760 saliva samples from asymptomatic and symptomatic individuals across multiple healthcare settings. Using this improved method we report a diagnostic sensitivity (DSe) of 70.35% (95% CI 63.48-76.60%) on swabs and 84.62% (79.50-88.88%) on saliva, with diagnostic specificity (DSp) 100% (98.98-100.00%) on swabs and 100% (99.72-100.00%) on saliva when compared to RT-qPCR. Analysing samples with RT-qPCR ORF1ab CT values of <25 and <33 (high and medium-high viral loads, respectively), we found DSe of 100% (96.34-100%) and 77.78% (70.99-83.62%) for swabs, and 99.01% (94.61-99.97%) and 87.32% (80.71-92.31%) for saliva. We also describe RNA RT-LAMP (on extracted RNA) performed on 12,619 swabs and 12,521 saliva samples to provide updated performance data with DSe and DSp of 95.98% (92.74-98.06%) and 99.99% (99.95-100%) for swabs, and 80.65% (73.54-86.54%) and 99.99% (99.95-100%) for saliva, respectively. We also report on daily samples collected from one individual from symptom onset where both Direct and RNA RT-LAMP detected SARS-CoV-2 in saliva collected on all six days where symptoms were recorded, with RNA RT-LAMP detecting SARS-CoV-2 for an additional further day. The findings from these studies demonstrate that RT-LAMP testing of swabs and saliva is potentially applicable to a variety of use-cases, including frequent, interval-based testing of saliva from asymptomatic individuals via Direct RT-LAMP that may be missed using symptomatic testing alone.
ABSTRACT
Antiviral compounds displaying remarkable features have been identified by an unconventional drug screen and advanced through animal validation. Efficacy is observed against the six viral families causing most human respiratory viral disease, irrespective of strain, including both influenza (FLUV) and SARS-CoV-2, with cell culture EC50 at or below 100 nM. Survival benefit is demonstrated in pigs against another member of family Coronaviridae, porcine epidemic diarrhea virus (PEDV), and shown equally effective in mild and severe disease. Respiratory syncytial virus (RSV) titer is reduced by drug treatment in cotton rats. A substantial barrier to viral resistance is demonstrated for FLUV. Drug resin affinity chromatography (DRAC) reveals a novel drug target: a multi-protein complex (MPC) formed transiently, in an energy-dependent fashion, and composed of host proteins implicated in both viral lifecycles and manipulation of innate immunity. The protein composition of this host MPC is modified upon viral infection, with increase or decrease of some proteins and appearance or complete loss of others. Valosin-containing protein, also known as Transitional endoplasmatic reticulum ATPase (VCP/p97), is present in the target MPC of uninfected cells and significantly increased in both FLUV and CoV infection. SQSTM1/p62, a key regulator of the autophagy pathway of innate immunity whose dysfunction is implicated in cytokine storm, is i) found in the target MPC from uninfected cells, ii) diminished in DRAC eluates by infection, and iii) restored by drug treatment of infected cells. 14-3-3 is one of likely several proteins that comprise the drug-binding site. Advanced compounds with improved pharmacokinetic (PK) properties and lung exposure are approaching criteria for a Target Product Profile. We propose these novel drug targets to comprise a previously unappreciated molecular basis for homeostasis that is modified by viruses to allow exploitation for viral propagation and is restored by treatment with the therapeutic compounds presented. This discovery has transformative implications for treatment of respiratory viral-related disease, applicable to everything from seasonal FLUV to COVID-19 and future novel respiratory viruses, due to the pan-family nature of drug activity and barrier to resistance development.
Subject(s)
Infections , Virus Diseases , COVID-19 , Respiratory Syncytial Virus Infections , DiarrheaABSTRACT
We describe the optimization of a simplified sample preparation method which permits rapid and direct detection of SARS-CoV-2 RNA within saliva using reverse-transcription loop-mediated isothermal amplification (RT-LAMP). Treatment of saliva samples prior to RT-LAMP by dilution 1:1 in MucolyseTM, followed by dilution (within the range of 1 in 5 to 1 in 40) in 10% (w/v) Chelex 100 Resin and a 98oC heat step for 2 minutes enabled detection of SARS-CoV-2 RNA in all positive saliva samples tested, with no amplification detected in pooled negative saliva. The time to positivity for which SARS-CoV-2 RNA was detected in these positive saliva samples was proportional to the real-time reverse-transcriptase PCR cycle threshold (CT), with SARS-CoV-2 RNA detected in as little as 05:43 (CT 21.08), 07:59 (CT 24.47) and 08:35 (CT 25.27) minutes, respectively. The highest CT where direct RT-LAMP detected SARS-CoV-2 RNA was 31.39 corresponding to a 1 in 40 dilution of a positive saliva sample (1:1 in MucolyseTM) with a starting CT of 25.27. When RT-LAMP was performed on pools of SARS-CoV-2 negative saliva samples spiked with whole inactivated SARS-CoV-2 virus, RNA was detected at dilutions spanning 1 in 5 to 1 in 160 representing CTs spanning 22.49-26.43. Here we describe a simple but critical rapid sample preparation method which can be used up front of RT-LAMP to permit direct detection of SARS-CoV-2 within saliva samples. Saliva is a sample which can be collected non-invasively without the use of highly skilled staff and critically can be obtained from both healthcare and home settings. Critically, this approach overcomes both the requirement and validation of different swabs and the global bottleneck in obtaining RNA extraction robots and reagents to enable molecular testing by PCR. Such testing opens the possibility of public health approaches for effective intervention to control the COVID-19 pandemic through regular SARS-CoV-2 testing at a population scale, combined with isolation and contact tracing for positive cases.