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This systematic scoping review aimed to examine the literature on expanding role of telepharmacy services during the ongoing COVID-19 pandemic. Four electronic databases, PubMed, Scopus, ProQuest, and Cochrane, were searched to identify published studies that reported implementation of telepharmacy services since the start of pandemic (31st December 2019 to 31st May 2022). Twenty-eight studies met the inclusion criteria comprising 15 cross-sectional studies, 12 studies sharing experience and practice related to telepharmacy services, and one pre-post intervention study. Studies reported establishment and implementation of various novel telepharmacy models in different settings;primary, secondary, tertiary, and quaternary care hospitals, hospital and community pharmacies, and specialized care centers. Telepharmacy provided pharmaceutical care to patients with COVID-19, chronic diseases, HIV infection, cancer, cystic fibrosis, and patients on anticoagulants. Pharmaceutical care services like patient counseling services (19 studies), medication order review and medication reconciliation (15 studies), drug therapy optimization (11 studies), adverse drug reaction monitoring and management (7 studies), medication adherence assessment (5 studies), and drug-related problem monitoring (4 studies) were delivered using telepharmacy. Based on the identified evidence, telepharmacy proved beneficial in delivering a range of pharmaceutical care services to the patients during the current pandemic. However, there is a need for more rigorous evidence on the reliability, safety, and effectiveness of telepharmacy in comparison to the traditional face-to-face healthcare delivery model © 2023 Syed Arman Rabbani et al. This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/)
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Background: To mitigate the risks of chemotherapy associated neutropenia, during the COVID-19 pandemic, all genitourinary (GU) cancer patients treated with chemotherapy at the Princess Margaret Cancer Centre (PMCC) were offered primary prophylaxis with GCSF. We hypothesize that this reduced rates of febrile neutropenia, hospitalizations, healthcare costs and improved overall outcomes, compared to GU cancer patients treated with chemotherapy without GCSF in the 2 years prior to the pandemic. Method(s): We performed a retrospective review of GU cancer patients, receiving curative or palliative intent chemotherapy, with or without primary GCSF prophylaxis between January 2018 and June 2022. GCSF was given either as a single dose or as consecutive doses post chemotherapy. Main outcomes were incidence of febrile neutropenia, hospitalization, health care expenditures as well as disease specific outcomes. Result(s): Overall, 248 patients with prostate cancer (44%), urothelial cancers (33%) germ cell (21%), and rare GU cancers (4%) were identified. Median age was 70 (range 19-91), 92% were male, 65% were ECOG 0/1. Treatment intent was neoadjuvant (13%), adjuvant (20%), or palliative (67%). Main regimens used were docetaxel, cabazitaxel, carboplatin, cisplatin/ etoposide, gemcitabine/cisplatin and BEP. Median follow-up was 10.5 months (0.23-52.3 months). A total of 206/248 received primary GCSF prophylaxis. During chemotherapy, the median white blood cell levels were higher in the GCSF group compared to the non-GCSF group (14.1+/-10+/-9/L vs 2.90+/-10+/-9/L, p<0.0001);and neutropenia rates were markedly lower (2% vs. 93%, P=,0.0001). Hospital admission rates were significantly lower in G-CSF users compared to nonusers (19% vs. 69%, P,0.0001). Symptomatic disease progression 13% was the leading cause of admission in the G-CSF group. Infectious causes such as UTI, pneumonia, COVID-19, and sepsis were seen in only 12% of the G-CSF group compared to 31% in the non-users. G-CSF was generally well tolerated with just 0.97% discontinuing G-CSF. Conclusion(s): During the COVID-19 pandemic, primary prophylactic G-CSF use in GU cancer patients, undergoing chemotherapy significantly lowered rates of both febrile neutropenia and hospitalizations and could be a cost-effective strategy in this patient population that warrants further study.
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Background: To direct limited specialized palliative care resources to patients in greatest need, we developed STEP (Symptom screening with Targeted Early Palliative care). STEP entails symptom screening (ESAS-r) at each oncology clinic visit and triggered alerts (for moderate-high physical and psychological symptoms) to a nurse who calls the patient to offer a palliative care clinic (PCC) visit. We conducted a phase III RCT to assess the impact of STEP versus usual care on quality of life and other patient-reported outcomes (PROs). Methods: Adults with advanced cancer were recruited from medical oncology clinics at the Princess Margaret Cancer Centre, Toronto, Canada. Consenting patients with oncologist-assessed ECOG 0-2 and estimated survival of 6-36 months were enrolled and block randomized (stratified by tumour site and symptom severity) to STEP or usual care. Participants completed measures of quality of life (FACT-G7), depression (PHQ-9), symptom control (ESASr-CS), and satisfaction with care (FAMCARE-P16) at baseline, 2, 4 and 6 months. The primary outcome was FACT-G7 at 6 months, with a planned sample size of 261/arm. Results: From 8/2019 to 3/2020, 69 patients were enrolled: 33 randomized to STEP and 36 to usual care. The trial was then halted permanently due to the COVID-19 pandemic, owing to substantial changes to elements of STEP (shift to virtual symptom screening and palliative care) and usual care (shift to virtual oncology care). Median age was 64 years (range 25-87) and 62% (43/69) were women;study arms were balanced at baseline except gender, with more women randomized to STEP. Within the STEP arm, 20 (61%) participants triggered a nurse's call to offer a PCC visit, of whom 13 attended the clinic at least once. All outcomes tended to be better in the STEP arm compared to usual care, particularly depression and satisfaction with care at 6 months;however, results were not statistically significant (Table). Conclusions: STEP holds promise for improving quality of life and other PROs in patients with advanced cancer and effectively directing early palliative care towards those who need it most. In response to the pandemic, an online version of STEP has been developed and a further trial is in progress.
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Introduction To direct scant specialized palliative care (PC) resources to patients in greatest need, we developed the STEP intervention (Symptom screening with Targeted Early Palliative care). STEP entails symptom screening with ESAS-r at each oncology visit and triggered alerts (for moderatehigh symptoms) to a nurse who calls the patient to offer a PC clinic visit. Methods Consenting adults with advanced cancer, ECOG 0-2, attending medical oncology clinics at the Princess Margaret Cancer Centre, were randomized to STEP or usual care. Participants completed quality of life (FACTG7), depression (PHQ-9), symptom control (ESASr-CS), and satisfaction with care (FAMCARE-P16) measures at baseline, 2, 4, and 6 months. The primary outcome was FACT-G7 at 6 months. Results From August 2019 to March 2020, 33 patients were randomized to STEP and 36 to usual care. The trial was subsequently permanently halted due to the COVID-19 pandemic. Groups were balanced at baseline except gender, with more females in the STEP arm (Table 1). In the STEP arm, 20 participants triggered a nurse 's call, of whom 13 had ≥1 PC clinic visit. At 6 months, all outcomes tended to be better in the STEP arm compared to usual care, particularly depression and satisfaction with care;however, results were not statistically significant (Table 2, Figure 1). Conclusions STEP holds promise for improving outcomes in patients with advanced cancer. An online version (eSTEP) is being developed in response to the COVID-19 pandemic.
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The vascular endothelial injury occurs in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, but the mechanisms are poorly understood. We sought to determine the frequency and type of cytokine elevations and their relationship to endothelial injury induced by plasma from patients with SARS-CoV-2 versus controls. Plasma from eight consecutively enrolled patients hospitalized with acute SARS-CoV-2 infection was compared to controls. Endothelial cell (EC) barrier integrity was evaluated using ECIS (electric cell-substrate impedance sensing) on human lung microvascular EC. Plasma from all SARS-CoV-2 but none from controls decreased transendothelial resistance to a greater degree than that produced by tumor necrosis factor-alpha (TNF-alpha), the positive control for the assay. Thrombin, angiopoietin 2 (Ang2), and vascular endothelial growth factor (VEGF), complement factor C3a and C5a, and spike protein increased endothelial permeability, but to a lesser extent and a shorter duration when compared to SARS-CoV-2 plasma. Analysis of Ang2, VEGF, and 15 cytokines measured in plasma revealed striking patient-to-patient variability within the SARS-CoV-2 patients. Pretreatment with thrombin inhibitors, single, or combinations of neutralizing antibodies against cytokines, Ca3 and C5a receptor antagonists, or with ACE2 antibody failed to lessen the SARS-CoV-2 plasma-induced EC permeability. The EC barrier destructive effects of plasma from patients with SARS-CoV-2 were susceptible to heat inactivation. Plasma from patients hospitalized with acute SARS-CoV-2 infection uniformly disrupts lung microvascular integrity. No predicted single, or set of, cytokine(s) accounted for the enhanced vascular permeability, although the factor(s) were heat-labile. A still unidentified but potent circulating factor(s) appears to cause the EC disruption in SARS-CoV-2 infected patients. IMPORTANCE Lung vascular endothelial injury in SARS-CoV-2 patients is one of the most important causes of morbidity and mortality and has been linked to more severe complications including acute respiratory distress syndrome (ARDS) and subsequent death due to multiorgan failure. We have demonstrated that in eight consecutive patients with SARS-CoV-2, who were not selected for evidence of endothelial injury, the diluted plasma-induced intense lung microvascular damage, in vitro. Known endothelial barrier-disruptive agents and proposed mediators of increased endothelial permeability in SARS-CoV-2, induced changes in permeability that were smaller in magnitude and shorter in duration than plasma from patients with SARSCoV-2. The effect on endothelial cell permeability of plasma from patients with SARS-CoV-2 was heat-labile. The main plasma factor that causes the increased endothelial permeability remains to be identified. Our study provides a possible approach for future studies to understand the underlying mechanisms leading to vascular injury in SARS-CoV-2 infections.
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Objectives: The objective of the study is to evaluate herbal immunomodulators (Septilin and Bresol) as a possible adjuvant therapy for the treatment of asymptomatic and mildly symptomatic COVID-19. Methods: Randomized, open-label, comparative clinical study. Subjects were randomized to either arm I [Septilin and Bresol+standard of care (SOC)] or arm II (SOC). This study was registered on CTRI (CTRI/2020/06/025801). Results: Subjects in arm I showed a greater reduction in levels of interleukin-6 tumor necrosis factor-α following treatment than in arm II. Subjects in arm I showed a greater increase in levels of interferon (IFN)-β and IFN-λ than those in arm II. There was a greater reduction in D-dimer in arm I than in arm II subjects (64.28% vs. 35.59%) and all arm I subjects had D-dimer values in the normal range compared to 70% of arm II subjects. There were statistically significant reduction in lactate dehydrogenase and neutrophil-to-lymphocyte ratio in arm I (p<0.016 and p<0.013, respectively). Clinical assessments during the post-illness convalescence period showed significant improvements in fatigue assessment scores and quality of life. Conclusion: This herbal combination as an adjuvant to SOC may provide additional long-term benefits in COVID-19 infection by reducing inflammation. This treatment may offer a good addendum for the management of post-COVID-19 illness.
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COVID-19, caused by SARS-COV-2 virus, has spread to almost all the countries in the world. Much like the SARS pandemic in 2002 and 2003, conventional control measures like travel restriction and patient isolation are being used to control spread of COVID-19. However, the morbidity rate of COVID-19 is still more than 1. Despite the high morbidity rate in all the countries COVID-19 has spread to, mortality rate due to COVID-19 varies greatly between different countries. Through a few recent epidemiological studies, it has been suggested that a negative association between national BCG vaccination policy and prevalence and mortality of COVID-19 exists. It has been observed that countries with BCG in their national immunisation programs have a lower mortality rate than countries without BCG in their national immunisation programs. We survey public datasets and repositories from websites like BCGAtlas, WHO, John Hopkins GitHub and World Bank, to understand and predict, with the power of data science, the implications of a plausible BCG cross-protection from severe COVID-19. We study COVID-19 related statistics to understand the spread of the disease, compare it with other countries to understand the role of cross-protective vaccines like BCG
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Objective: The objective of the study was to evaluate the role of the herbal immunomodulators Immusante and Guduchi in boosting the immunity and overall health of healthcare workers assigned to coronavirus disease 2019 (COVID-19) wards. Methods: An open-label, randomized, prospective, and single center clinical study was conducted among 100 healthcare workers assigned to COVID-19 wards. Eligible subjects (50 in each arm) were randomly assigned to either arm I (Immusante+Guduchi tablets) or arm II (treatment as per the institutional policy). Assessments after 30 days of treatment included respiratory symptoms, Adapted Immune Status Questionnaire (ISQ), improvement in quality of life (Short form 12 [SF-12] Health Survey), and safety and tolerability. Results: All 100 subjects completed the study as per the protocol. There were no respiratory symptoms in the subjects in arm 1. However, four subjects (8%) in arm II reported cough during the study period. A better Immune status improvement was seen through the adapted ISQ in arm I as compared to arm II. In each of the 8 SF-12 Health Survey domains, a statistically significant difference was observed in arm I compared to arm II. A retrospective assessment of COVID-19 infection showed only 8% of subjects as COVID-19 positive in arm I compared with 26% of subjects in arm II. Conclusion: Considering the positive trend observed in this study in terms of ISQ, SF-12, and COVID-19 infection rates, the combination of Immusante and Guduchi in healthcare workers at a high risk of contracting COVID-19 infection had a beneficial effect in boosting immunity and overall health.
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The occurrence of imbalanced datasets in medical imaging has proven to be a challenge for the development of models to analyze and evaluate the underlying condition. In this paper, the bias of the chest CT scan dataset is handled by taking discrete splits and employing ResNets to detect COVID-19 in each split. The scraped images were pre-processed using CLARE histogram for comparison with low contrast images. Multiple ResNets were extended to form an ensemble neural network model using ANNs which handles the class imbalance. The system has an overall accuracy of 87.23% and the performance is assessed for each class. The image features identified are visualized using the GradCAM algorithm and some of the commonly found clinical features in the CT scan images of the patients suffering from this disease are summarized for better understanding the working of the model.
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Background: The COVID-19 pandemic has led to significant disruptions across all levels of medical training. International fellows in subspecialty training programs are essential members of the frontline physician workforce, who may be facing additional and unique challenges being far away from their home country. We aimed to understand the impact of the pandemic on the wellbeing of current international fellows in the Hematology/Oncology training program. Methods: We conducted an online survey of 52 international fellows at the PMCC from July 6-August 10, 2020. There were 60 questions divided into 4 sections: demographics, wellbeing assessment using the validated Short Warwick Edinburgh Mental Wellbeing Scale (SWEMWBS), fellowship specific questions (personal and professional) and coping strategies using the validated brief COPE scale. Results: Response rate was 46% (n = 24). Relevant demographics include: married (65%), male (54%), age between 31-35 years (48%), have children (48%), and home country from Asia (48%). Mean SWEMWBS score was 21, indicating lower overall wellbeing than the general population (23.6). Compared to pre-COVID-19, many reported a decline in their wellbeing (63%), sense of guilt for not being with their family (45%) or helping their country (41%), stress in personal relationships (26%), fatigue (50%), sleep disorders (38%) and loss of interest in daily activities (38%). Personal events were altered by almost 80% and 20% plans to extend their fellowship. According to the Brief- COPE scale, most fellows used more adaptive coping mechanisms (mean score 39.2) as opposed to maladaptive ones (mean score 21.8). Conclusions: The ongoing COVID-19 pandemic has negatively affected the overall wellbeing of international fellows. Understanding the specific challenges and coping mechanisms of international fellows may help Institutions develop better targeted strategies to promote their overall wellbeing, professional development and highquality patient care during these unprecedented times.
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The COVID-19 pandemic in the world has given rise to a lot of research done in the field of medical imaging using deep learning and artificial intelligence methods for the detection and prognosis of the disease. Capsule Networks (CapsNet) perform image classification by identifying the spatial location and orientation of features within the images. In this paper, a Multi-lane Capsule Neural Networks (MLCN) model is introduced that performs dynamic routing networks with dimensionally distinct parallel lanes, replacing the traditional pooling operations in Convolutional Neural Networks (CNN). With the use of parallel capsules, feature orientation identification at any given part of the image is improved. The MLCN model has been studied in this paper using the X-ray images collected from patients tested for COVID-19 and its performance is evaluated using a number of metrics. It has been observed that the performance of the constructed CapsNet model achieved a testing accuracy of 96.8% with the F-1 score 97.19% performing better than the existing state-of-the-art models. © 2021 IEEE.
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Description: The COVID-19 pandemic compelled the traditional higher educational institutions to make a quick transition to the virtual instruction model. Considering the COVID-19 restrictions, the Department of Clinical Pharmacy and Pharmacology at Ras Al Khaimah College of Pharmaceutical Sciences, United Arab Emirates restructured their original onsite experiential training for final year Bachelor of Pharmacy students as a virtual online experience to ensure educational continuity. Evaluation: The virtual experiential training was conducted over two weeks and was imparted employing different virtual platforms like Google Classroom, Google Meet, Google Forms, Google Docs, etc. As a part of the community pharmacy training, the students were given different e-activities and tasks like e-case scenario analysis and interpretation, e-prescription screening, virtual patient education and were shown various 3-D animated videos related to community pharmacy. For the hospital training, the students were given different e-cases for developing pharmaceutical care plans, e-case scenario analysis, e-drug information query and were shown different animated videos related to rounds of different hospital departments. Conclusion: The virtual experiential training was successfully conducted achieving the desired learning outcomes and was well received by the students. Based on this experience, it is recommended that efforts should be made to develop an integrated model for experiential training in the future, which can be an amalgamation of online tools and traditional experiential methods.
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Covid-19, an infectious disease, is currently the leading topic of conversation throughout the world. Declared as a pandemic by the WHO, the virus attacks the respiratory system and causes dry cough, fever and in severe cases difficulty in breathing. In this paper, we analyse the similarity in features between the novel coronavirus 2019 and various other lung diseases such as Pneumonia, Pneumothorax, Atelectasis, Pleural Thickening etc. Chest X-ray scans in the posteroanterior view for various diseases are collected. Convolutional Neural Network using the Residual Network (ResNet) is built to identify the similar regions in the chest X-rays of COVID-19 and various lung diseases. The regions of similarity are visualized using class activation maps. A total of eleven conditions affecting the lungs are studied and compared to COVID-19. The results show that Atelectasis, Consolidation, Emphysema, and Pneumonia are most similar in nature to COVID-19 of the eleven diseases considered. Diseases which our model detects as similar to COVID-19, occur either prior to onset of COVID-19 or as a consequence of COVID-19. © 2020 IEEE.
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BACKGROUND: In late 2019, a novel human coronavirus - severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) - emerged in Wuhan, China. This virus has caused a global pandemic involving more than 200 countries. SARS-CoV-2 is highly adapted to humans and readily transmits from person-to-person. AIM: To investigate the infectivity of SARS-CoV-2 under various environmental and pH conditions. The efficacies of various laboratory virus inactivation methods and home disinfectants against SARS-CoV-2 were investigated. METHODS: The residual virus in dried form or in solution was titrated on to Vero E6 cells on days 0, 1, 3, 5 and 7 after incubation at different temperatures. Viral viability was determined after treatment with various disinfectants and pH solutions at room temperature (20-25oC). FINDINGS: SARS-CoV-2 was able to retain viability for 3-5 days in dried form or 7 days in solution at room temperature. SARS-CoV-2 could be detected under a wide range of pH conditions from pH 4 to pH 11 for several days, and for 1-2 days in stool at room temperature but lost 5 logs of infectivity. A variety of commonly used disinfectants and laboratory inactivation procedures were found to reduce viral viability effectively. CONCLUSION: This study demonstrated the stability of SARS-CoV-2 on environmental surfaces, and raises the possibility of faecal-oral transmission. Commonly used fixatives, nucleic acid extraction methods and heat inactivation were found to reduce viral infectivity significantly, which could ensure hospital and laboratory safety during the SARS-CoV-2 pandemic.
Subject(s)
Betacoronavirus/growth & development , Betacoronavirus/pathogenicity , Coronavirus Infections/physiopathology , Microbial Viability , Pneumonia, Viral/physiopathology , Severe Acute Respiratory Syndrome/pathology , Virulence , Virus Inactivation , COVID-19 , China/epidemiology , Coronavirus Infections/epidemiology , Humans , Pandemics , Pneumonia, Viral/epidemiology , SARS-CoV-2 , Severe Acute Respiratory Syndrome/epidemiologyABSTRACT
Purpose The purpose of this paper is to identify coronavirus contact using internet of things. The disease is said to be highly contagious with the contact of infected persons. Feared to be air-borne, droplets of body fluids can transmit the disease in a matter of hours. The predominant symptoms of the COVID-19 are high fever, cough, breathing problem, etc. Recent studies have demonstrated the evolution of the disease to hide its symptoms. As it is highly transmissible, this disease might spread at an exponential rate costing the lives of thousands of people. The chain of transmission has to be detected with utmost priority through early detection and isolation of infected people. Automated internet of things (IoT) devices can be used in design and implementation of a prediction scheme for reporting the health-care risks of the patients with various parameters such as temperature, humidity and blood pressure. Design/methodology/approach IoT is a configuration of multiple autonomous and embedded wireless devices for serving a purpose. Every object possesses an individual identity and will serve to register critical events as entries for future learning and decisions. IoT plays an inevitable role in medical industries, detection of vital signs of diseases and monitoring. Among other life-threatening diseases, a new pandemic is on rise among world nations. COVID-19, a novel severe acute respiratory syndrome virus originated from animals in December 2019 and is becoming a serious menace to Governments, despite serious measures of lockdowns. Findings In this paper, the authors defined an architecture of an IoT system to predict the Covid-19 disease by getting the data from the human through sensors and send the data to the doctor using mobile, computer, etc. The main goal is early health surveillance by predicting COVID-19. Accordingly, the authors are able to identify both symptomatic and asymptomatic patients, which will help in the early prediction of disease. Originality/value Using the proposed method, the authors can save the time of both patient and doctor by ensuring timely medical treatment and contribute toward breaking the transmission chain. In so doing, the method also contributes toward avoiding unnecessary expenses and saving human lives.