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Background: COVID-19-related lung injury may persist or require time to recover in some individuals. Objective(s): To better understand the post-acute pathophysiology of non-critical COVID-19 by evaluating respiratory system resistance and reactance in COVID-19 survivors 4-weeks and 6-months after recovery, compared to neverCOVID-19 controls. Method(s): Individuals with no history of lung disease who were hospitalized or home-isolated during the acute-phase of COVID-19, and age-matched never-COVID-19 controls, performed respiratory oscillometry (tremoFlo C-100) to measure resistance (Rrs5Hz, Rrs19Hz , Rrs5-19Hz ), reactance (Xrs5Hz ) and area of reactance (A ), Six Minute Walk Test, and completed the Borg Dyspnea Scale 4-weeks (visit 1) and 6-months (visit 2) post-recovery. Result(s): Hospitalized (n=9), home-isolated (n=20) and never-COVID-19 (n=17) cohorts were similar with respect to age (p=0.12), sex (p=0.89), and BMI (p=0.08). Figure 1 shows that Rrs5-19Hz (p=0.04) and A (p=0.009) were higher, and Xrs5Hz (p=0.007) was more negative, in the hospitalized cohort compared to control cohort at visit 1, but not visit 2. These measures were associated with greater dyspnea and decreased six-minute walk distance. Conclusion(s): Increased peripheral resistance and reactance following recovery from non-critical COVID-19 may only be prevalent among hospitalized COVID-19 survivors, within which these respiratory abnormalities may be temporary.
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Coronavirus disease 2019 (COVID-19) survivors experience impaired pulmonary function, reduced muscle strength, and exercise intolerance affecting their activities of daily living. Literature has demonstrated a need for multi-disciplinary approach for their faster recovery. In a pandemic like situation where maintaining social distancing to reduce the risk of transmission had become a norm, telerehabilitation services came to a great rescue of both the patients and health-care providers. At present, there are not any established guidelines for rendering pulmonary rehabilitation through telerehabilitation (TR). Besides, it's effective implementation depends on numerous patient-centric factors such as age, hemodynamic stability, presence of comorbidities, availability of resources, and cognitive level of the patient. We hereby present the case of a 69-year-old female diagnosed with COVID-19 with prolonged hospital stay, having a history of multiple co-morbidities, focusing on the role of 12 weeks of TR in improving her functional outcomes.
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Oil and Gas industry is seeking new ways to improve efficiencies, reducing operating costs and increasing revenues in the current volatile market conditions. Data Science and all the new emerging technologies enable the discovery of new opportunities and digitalization is a vital element for making business more effective and efficient. While COVID19 has disrupted the world, ADNOC Onshore has recognized the importance of reskilling and empowering the future workforce through strategic enterprise data science and analytics program to achieve 2030 smart growth strategy. This paper talks about successful approach and enablers for development of in-house capability for transformation that lead to generating significant business value The digital transition can pose both challenges and opportunities in this transformation. ADNOC ONSHORE has developed an integrated framework to encourage and accelerate data science capabilities. This framework promotes a vision with collaborative, sustainable mechanisms to develop talent. It is not just the formal learning and additional professional qualification that make it possible to build this in house capability. There are five major areas are enabled this framework such as data science & analytics skills competency model, sustainable on-line collaborative learning program, organizational culture change, democratizing AI through open platform & a digital business model for performing real business problems/use case PoCs. Each area has a detailed program and execution strategy with a collaborative effort from technical and non-technical stakeholders. ADNOC ONSHORE has successfully implemented this framework and able to certify 20 employees as part of this program. The Data Science Competency Model identified and defined the skills required to be successful within the enterprise with a clear learning path and mentorship. The leadership played a pivotal role to encourage data driven decision making and predictive capabilities in addition to executive awareness to lead the change with clear performance indicators. By democratizing AI platform across upstream user community, six real business cases have been successfully developed with clear business value in subsurface and production workflows according to the defined digital business model. The successful business cases have improved efficiency by 75% in performing cement & corrosion log interpretation & well portfolio optimization. Data driven analytics have been evaluated in subsurface workflows such as infill location optimization, gas-lift candidate identification and they have complemented the existing techniques. The framework has been successfully extended to other group companies in ADNOC. The rapid growth of AI in business in the last five years presents an opportunity for oil and gas professionals for enhancing the skills and transformation. This paper talks about an integrated framework, learning path, democratizing AI, engagement of leadership, digital business model for business case evaluation by applying agile way of working and sustainable value creation. Copyright © 2022, Society of Petroleum Engineers.
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The COVID-19 pandemic posed a real challenge to business continuity of our safety assurance programs, incident investigations and training of young engineers which are traditionally conducted through physical rig site visits. The measures taken to control the spread of the COVID-19 virus meant that physical visits to the rig sites were restricted and during certain times completely stopped. The consequence of such measure meant that the safety assurance program was heavily impacted as the weekly leadership site visits were suspended. This posed a risk of a potential increase in safety incidents. Moreover, only safety critical personnel were allowed at the rig sites meaning that all trainee drilling supervisors and engineers were not allowed to visit the rig sites as part of the COVID-19 control measures. This in turn directly impacted the training program of our young engineers and trainee drilling supervisors for the entire COVID-19 pandemic period - Not Good! The potential risk of an increase in safety incidents due to lack of safety assurance was too great a cost to accept. Therefore, the drilling team started to think differently. A multi-disciplinary brainstorming workshop involving technology providers in the digital space was conducted to discuss possible ways of conducting rig site visit virtually. During this workshop, augmented reality via use of the wearable camera was flagged as a technology ready solution for our challenge. Several subsequent sessions were conducted with ADNOC Onshore IT team to build a business case for the wearable camera. The wearable camera is an intrinsically safe Zone 1 certified fully rugged head-mounted device made for harsh environments. The high-resolution micro display fits just below the user's line of sight and views like a 7" tablet. A business case was put forward and approved to conduct a proof of concept (PoC) to specifically test the ability to conduct remote rig visits, investigations and training programs. The PoC was successfully completed and allowed the team to conduct remote rig visits, audits, investigations and training programs with the "touch and feel" of being at the rig site - a paradigm shift in the way we run our business. Copyright © 2022, Society of Petroleum Engineers.
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Aims To look at the individual experiences amongst paediatricians in DGH (District General Hospitals) with regards to the management of PIMS-TS (Paediatric Multisystem Inflammatory syndrome) over the last 2 years Methods A survey was sent to paediatricians via a survey link. The survey asked for multiple questions regarding the respondents' individual experiences in the management of children presenting with PIMS TS. Results 38 completed responses were obtained and analysed. Among the 38 respondents, each had seen between 2-20 patients with PIMS-TS over the last 2 years. 40% of the cases were predominantly cardiovascular, 30% were gastrointestinal and 30% were mixed. 50% of the respondents said that <25% of their patients were transferred to PICU, 22% said around 50% of patients were transferred, 18% said 90% of their patients were transferred and 10% of the respondents said 100% of their patients were transferred to PICU. 66% of respondents had no problems getting a PICU bed or retrieval services however 33% of the respondents agreed to some difficulties. 92% of the time patients were discussed with the infectious diseases (ID) team and 8% of the time this wasn't discussed with the ID team. 17% of the respondents used steroids in all their patients whereas the rest used in varying numbers. 40% of the respondents said they used IVIG in 75% of their patients whereas the rest used it in varying numbers. Inotropes were used in 25% of the patients whilst in DGH, on average 25% of the patients needed peripheral noradrenaline and no complications were reported. Comfort levels in the management of PIMS TS were in the moderate range amongst paediatricians in DGH. Around 60% of the patients had echocardiography within 48 hours of presentation. Some of the other difficulties encountered were nursing training in regards to administering noradrenaline, interpreting cardiac biomarkers, follow-up arrangements, and education. Conclusion PIMS TS is still a new clinical entity and often these patients present to District general hospitals in varying circumstances of clinical instability. Some of these patients need PICU transfer which can be challenging at times. Around 25% of these patients need inotropes predominantly noradrenaline with no reported complications. There are still wide variations in the management of these patients, and further education and clear guidelines would be helpful to ensure the management of these complex children is done safely & effectively.
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Background and Aim: We aimed to study the healthcare disparity among elderly patients with cirrhosis and its impact on composite outcomes during the COVID pandemic. Methods: We conducted a prospective observational study between July 21- May 2022 via telephonic interview or physical consultations at 2 large tertiary care centers in India. The data was captured using pre-validated questionnaires to assess healthcare disparity amongst elderly patients with cirrhosis. Results: Of 475 elderly (≥65years) patients with cirrhosis (based on imaging) were included with mean age of 72.1years, male:female(3.8:1) with aetiology of cirrhosis being NAFL/NASH (58%), alcohol(32%) in majority. 323 (69%) had access to internet, however amongst them only 247 (52%) were conversant with use of WhatsApp, the preferred platform for tele-consultations in most hospitals in India. 147(31%) had walkability and accessibility to hospitals and 223(47%) had access to a family physician or community nurse, 271 (67%) had laboratory access. 295(62%) had taken both Covid vaccines, 349(74%) had first dose alone and only 38(8%) had booster dose. 213 (45%) felt that they needed admission/ expert opinion at least once during the period with 137 (29%) needed inpatient treatment. 266 (56%) missed at least 15 days doses of drugs with 85(32%) citing unavailability and 48(18%) unaffordability. Cancellation/rescheduling of medical services was widely prevalent with 74(15.5%) needing to reschedule endoscopy, 132 (28%) had cancellation of imaging of any form at least once, loco-regional therapy was rescheduled in 14(18%) patients of HCC. Advanced age, presence of >1 co-morbidity, tense ascites, hepatic encephalopathy, lack of caregivers were signi cantly associated with poor quality of life, restricted access and utilization of healthcare Conclusions: Elderly patients with cirrhosis had significant barriers in seeking healthcare during Covid19 pandemic highlighting the disparity and need for concerted e orts to improve their access to care.
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COVID-19 disease discovered from the novel corona virus can spread through close contact with a COVID-19 infected person. One of the measures advised to contain the spread of the virus is to maintain social distancing by minimizing contact between potentially infected individuals and healthy individuals or between population groups with high rates of transmission and population groups with no or low-levels of transmission. Motivated by this practice, we propose a deep learning framework for social distance detection and monitoring using surveillance video that can aid in reducing the impact of COVID-19 pandemic. This work utilizes YOLO, Detectron2 and DETR pre-trained models for detecting humans in a video frame to obtain bounding boxes and their coordinates. Bottom-centre points of the boxes were determined and were then transformed to top-down view for accurate measurement of distances between the detected humans. Based on the depth of each bottom-centre point estimated using monodepth2, dynamic distance between pairs of bounding boxes and corresponding distance threshold (safe distance) to prevent violation of social distancing norm were computed. Bounding boxes which violate the distance threshold were categorized as unsafe. All the experiments were conducted on publicly available Oxford Town Center, PETS2009 and VIRAT dataset. Results showed that Detectron2 with top-down view transformation and distance thresholding using pixel depth estimation outperformed other state-of-the-art models. The major contribution of this work is the estimation and integration of variable depth information in obtaining the distance threshold for evaluating social distances between humans in videos. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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BACKGROUND AND AIMS: Despite the lungs are the major targets of COVID-19, other organs such as the kidneys are also affected. Renal complications of COVID-19 are not yet well studied. We aimed to study the prevalence of acute kidney injury (AKI) among positive COVID-19 cases that were managed in the intensive care unit (ICU) in a single isolation hospital during the pandemic, and to explore its impact on patient outcome. METHOD: This retrospective study included 616 patients with COVID-19 who were managed in the ICU in a single isolation hospital in Kuwait during the pandemic, from February to December 2020. AKI was defined according to the serum creatinine criteria in the Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. Of the 616 patients, 40.2% developed AKI (group 1, n = 248) and were compared with the patients without AKI (group 2, n = 368). RESULTS: Most of cases in the two groups were males (73% versus 70.7%), aged (60.8 ± 14 versus 51.7 ± 16 years), respectively. The two groups were comparable regarding chronic kidney disease (2% versus 0.8%) and chronic pulmonary disease. Other factors were significantly predominating among group 1 as diabetes mellitus (63.7 versus 40.5%), hypertension (74.2% versus 40.5%) and ischemic heart disease (26.2% versus 12.5%) (P < .05). Fever, cough, shortness of breath and dehydration were significantly more frequent presentations among patients of group 1, and had radiological findings that were synchronized with COVID-19 (89.5% versus 50.8%) (P < .05). Moreover, sepsis, volume depletion, shock, arrhythmias and ARDS predominated among the AKI group (P < .05). The number of cases who were managed by therapeutic anticoagulation was significantly higher in AKI patients (89.9% versus 51.9%);also, cases who received supportive vasopressors and convalescent plasma transfusion as well as steroid were significantly higher in the same group (P < .05). Other therapeutic modalities such as antivirals, tocilizumab and hydroxychloroquine were comparable in both groups. We found that acute respiratory failure requiring mechanical ventilation was significant among the AKI group (66.8% versus 29.4%), and the overall mortality rate was significantly higher in the same group (62.5% versus 32.8%). CONCLUSION: The prevalence of AKI in patients with COVID-19 was 40.2%, and it was associated with poor prognosis among ICU COVID-19 positive cases.
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Purpose—The objective of this paper is to suggest methods to compute an effective Information and Communication Technology (ICT), Capability Index for Supply Chain Management (SCM) as part of assessment framework on ICT impact on SCM. The other part of this assessment framework is an empirical model based on SCOR level I performance indicators. This framework can be seamlessly dovetailed into the universally accepted and popular APICS Supply Chain Operations Reference (SCOR) model as its constructs are based on SCOR. The assessment framework will be a welcome addition to the Industry 4.0 research underway. Design/methodology/approach—Survey questionnaire was administered and collected from 200 + SCM professionals in sectors such as manufacturing, services, MSMEs, international companies as well as SCM/ERP professionals working as domain experts in IT and service companies. Snowball sampling was primarily used with the support of various industrial associations and professional body chapters. This questionnaire combines quantitative and qualitative inputs with adequate provision for open-ended questions with user input as a means of eliciting case interviews. After Confirmatory Factor Analysis (CFA) using SEM was employed to validate the empirical model, its performance indicators are ranked using AHP and the weights are ascertained. Computing the ICT Capability Index for SCM from the metrics of the assessment model is done using tools such as Balanced Scorecard (BSC) and Snorm De Boer standardized normalization (SNORM) method. Findings—An ICT capability index for SCM is computed based on user input with respect to the impact of ICT on the supply chain performance indicator as part of this framework using the methods of BSC & SNORM. 2 industry case studies are used for the computation and analysis of this index. Research limitations/implications—Discussion with an enterprise is needed to take input on the impact of ICT on each supply chain performance indicator in our calculation for the index. This investigation considers ICT deployment as the variable which encompasses the entire gamut of ICT tools and technologies. There could be different granular approaches to ICT as a variable. A scoring system, scale, and rubric are proposed to be evolved based on multiple case studies of various enterprises as an extension to this research work. There is tremendous scope to extend the investigation into SCOR level II metrics which are diagnostics of strategic metrics and level III metrics which are context or sector-specific and also considering various geographies. Originality/value–The managerial implications of this ICT Capability Index for SCM assumes greater significance as a result of the present situation due to Covid-19 pandemic, which has accelerated the need for Industry 4.0, digitalization and embracing of ICT not only for supply chain but also all aspects of the enterprise. There is also an identified lacuna in terms of performance scoring and assessment framework with respect to impact of ICT in SCM. The advantages of this index are that it is universal and can be used by any enterprise irrespective of the geography or country, vertical or domain, manufacturing or services. This index will provide insights to enterprises on their ICT capabilities and help them to further leverage ICT so as to adapt their organizations, digitize their operations and also benchmark with their peers and competitors. A scoring system and rubric is proposed to be evolved based on multiple case studies of various enterprises as an extension to this research work. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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The COVID-19 pandemic resulted in nearly all universities switching courses to online formats. We surveyed the online learning experience of undergraduate students (n = 187) at a large, public research institution in course structure, interpersonal interaction, and academic resources. Data was also collected from course evaluations. Students reported decreases in live lecture engagement and attendance, with 72 percent reporting that low engagement during lectures hurt their online learning experience. A majority of students reported that they struggled with staying connected to their peers and instructors and managing the pace of coursework. Students had positive impressions, however, of their instructional staff. Majorities of students felt more comfortable asking and answering questions in online classes, suggesting that there might be features of learning online to which students are receptive, and which may also benefit in-person classes.
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Public Policy Relevance Statement The present study sheds light on how social media engagement was associated with different indicators of well-being in India during COVID-19-imposed social distancing mandates. The study also suggests that some of these outcomes may be related to social media users' dispositions, namely, social comparison orientation, sense of loneliness, and their perceived social support. As the people around the globe suffered physically, relationally, emotionally, and financially in response to the COVID-19 crisis and accompanying social distancing mandates, they often turned to social media to cope. This study used an online survey to understand the relationships between social media engagement, loneliness, well-being, perceived social support, and social comparison with an Indian sample (N = 364). Correlations showed significant associations between all variables of interest, with the exception of social media engagement and perceived social support. Partial correlations revealed that an association between social media engagement and loneliness disappeared when social comparison orientation was controlled for;however, an inverse relationship between social media engagement and well-being remained, even when social comparison orientation was accounted for.
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Hands are the primary means of germ transmission, which results in the transmission of deadly diseases. Hand hygiene is thus an important measure to prevent the spread of harmful diseases. The World Health Organization (WHO) has recommended seven steps for proper handwashing hygiene. However, not everyone adheres to the WHO’s handwashing guidelines of seven steps. A proper hand wash is an important factor in protecting people’s health during the corona virus disease (COVID-19) pandemic, especially for healthcare workers who are exposed to bacteria, influenza, and other infectious diseases. There are technologies available like ultraviolet (UV) images to check a person’s hand hygiene. However, there is no real-time system to monitor how efficiently a person makes his or her hand wash. A real-time monitoring system is needed to check people’s hand wash hygiene in public places and hospitals, reducing the risk of spreading communicable diseases. In this paper, we have discussed predicting the accuracy of handwashing actions performed by humans using a deep learning model with transfer learning (VGG16). © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.