Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19

McRae, Michael; Simmons, Glennon W.; Christodoulides, Nicolaos; Lu, Zhibing; Kang, Stella K.; Fenyö, David; Alcorn, Timothy M.; Dapkins, Isaac; Sharif, Iman; Vurmaz, Deniz; Modak, Sayli S.; Rajsri, Kritika Srinivasan; Warhadpande, Shruti; Shrivastav, Ravi; McDevitt, John T.

doi:10.1039/d0lc00373e

Cited by 84 publications

(56 citation statements)

References 33 publications

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“…It operates in two modes: self-powering modes and imaging pixel mode, which causes the system to consume ultra-low-power of 6 microwatts. As per our study, we consider the potent system related to lungs is COVID-19 severity detection [ 38 ] because, through this system, the disease severity of the patient can be detected and thereby predict the mortality, from that, the decision can be made whether the patient can be quarantined or needs to be treated in ICUs (intensive care unit). As per the survey, the most powerful system related to bacterial cells is biofilm detection [ 44 ] that uses lensFree imaging technology with an ultra-large field of view and zooming capacity of 25 times larger than 100× optical microscope with three times more stability.…”

Section: Discussionmentioning

confidence: 99%

“…Due to unfortunate outbreaks, hospitalizations are increased in huge numbers, and the overwhelming need for intensive care units is necessary to save the patients from dying. Michael P. McRae et al [ 38 ] developed an integrated care COVID-19 clinical decision supporting system to find the severity score of the COVID-19 patients to prioritize their care and resources for treating them in which a disposable programmable bio nanochip (p-BNC) is used to determine the severity of COVID-19 as shown in Figure 33 .…”

Section: Role Of Cis In Human Body-related Disease Diagnosis Systementioning

confidence: 99%

“…Among the four systems reviewed, COVID-19 severity detection [ 38 ] uses the statistical learning algorithm and provides the severity score result in 16 min to give the suitable treatment and predict mortality with accuracy. Still, some of the input biomarkers yield redundant data that cause different results.…”

Section: Role Of Cis In Human Body-related Disease Diagnosis Systementioning

confidence: 99%

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Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review

Sukhavasi

Elleithy

Abuzneid

et al. 2021

Sensors

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According to the Center for Disease Control and Prevention (CDC), the average human life expectancy is 78.8 years. Specifically, 3.2 million deaths are reported yearly due to heart disease, cancer, Alzheimer’s disease, diabetes, and COVID-19. Diagnosing the disease is mandatory in the current way of living to avoid unfortunate deaths and maintain average life expectancy. CMOS image sensor (CIS) became a prominent technology in assisting the monitoring and clinical diagnosis devices to treat diseases in the medical domain. To address the significance of CMOS image ‘sensors’ usage in disease diagnosis systems, this paper focuses on the CIS incorporated disease diagnosis systems related to vital organs of the human body like the heart, lungs, brain, eyes, intestines, bones, skin, blood, and bacteria cells causing diseases. This literature survey’s main objective is to evaluate the ‘systems’ capabilities and highlight the most potent ones with advantages, disadvantages, and accuracy, that are used in disease diagnosis. This systematic review used PRISMA workflow for study selection methodology, and the parameter-based evaluation is performed on disease diagnosis systems related to the human body’s organs. The corresponding CIS models used in systems are mapped organ-wise, and the data collected over the last decade are tabulated.

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Section: Discussionmentioning

confidence: 99%

Section: Role Of Cis In Human Body-related Disease Diagnosis Systementioning

confidence: 99%

Section: Role Of Cis In Human Body-related Disease Diagnosis Systementioning

confidence: 99%

See 1 more Smart Citation

Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review

Sukhavasi

Elleithy

Abuzneid

et al. 2021

Sensors

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“…Thus, it requires the establishments of standards with help of government, institutions, and experts. Usually most of the academic development fails on the part of patients and only few qualifies the first evaluation stage ( McRae et al, 2020 ). This is mainly because of discrepancy between perception and reality as laboratory testing are carried out indoors rather than in the health care settings.…”

Section: Commercial Challengesmentioning

confidence: 99%

Internet of medical things (IoMT)-integrated biosensors for point-of-care testing of infectious diseases

Jain

Nehra

Kumar

et al. 2021

Biosensors and Bioelectronics

235

155

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On global scale, the current situation of pandemic is symptomatic of increased incidences of contagious diseases caused by pathogens. The faster spread of these diseases, in a moderately short timeframe, is threatening the overall population wellbeing and conceivably the economy. The inadequacy of conventional diagnostic tools in terms of time consuming and complex laboratory-based diagnosis process is a major challenge to medical care. In present era, the development of point-of-care testing (POCT) is in demand for fast detection of infectious diseases along with “on-site” results that are helpful in timely and early action for better treatment. In addition, POCT devices also play a crucial role in preventing the transmission of infectious diseases by offering real-time testing and lab quality microbial diagnosis within minutes. Timely diagnosis and further treatment optimization facilitate the containment of outbreaks of infectious diseases. Presently, efforts are being made to support such POCT by the technological development in the field of internet of medical things (IoMT). The IoMT offers wireless-based operation and connectivity of POCT devices with health expert and medical centre. In this review, the recently developed POC diagnostics integrated or future possibilities of integration with IoMT are discussed with focus on emerging and re-emerging infectious diseases like malaria, dengue fever, influenza A (H1N1), human papilloma virus (HPV), Ebola virus disease (EVD), Zika virus (ZIKV), and coronavirus (COVID-19). The IoMT-assisted POCT systems are capable enough to fill the gap between bioinformatics generation, big rapid analytics, and clinical validation. An optimized IoMT-assisted POCT will be useful in understanding the diseases progression, treatment decision, and evaluation of efficacy of prescribed therapy.

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“…In agreement with this thinking, Roche's Elecsys interleukin-6 (IL-6) test and Beckman Coulter's Access Interleukin-6 (IL-6) assay received authorization for emergency use from the U.S. FDA as a method for identifying COVID-19 patients who are having a severe inflammatory response and at high risk of developing respiratory failure and needing a ventilator. In addition, a number of clinical decision support tools (COVID-19 severity score/index) that combine multiple (laboratorybased) biomarker measurements and risk factors are actively being developed and validated to inform the clinical management and treatment of patients with COVID-19 (Ji et al, 2020;Liang et al, 2020;McRae et al, 2020;Shang et al, 2020).…”

Section: Biochemical Markers and Clinical Management Of Covid-19mentioning

confidence: 99%

Illuminating the immunopathology of SARS‐CoV‐2

Saksena

Chattopadhyay

2021

Cytometry Part B Clinical

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Over a remarkably short period of time, a great deal of knowledge about severe acute respiratory syndrome coronavirus 2 (SARS‐CoV2) infection has been acquired, through the focused and cooperative effort of the international scientific community. Much has become known about how the immune response is coordinated to fight infection, and how it becomes dysregulated in severe disease. In this review, we take an in‐depth look at the many immune features associated with the host response to SARS‐CoV2, as well as those that appear to mark severe disease.

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Clinical decision support tool and rapid point-of-care platform for determining disease severity in patients with COVID-19

Abstract: The COVID-19 Severity Score combines multiplex biomarker measurements and risk factors in a statistical learning algorithm to predict mortality.

Cited by 84 publications

References 33 publications

Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review

Human Body-Related Disease Diagnosis Systems Using CMOS Image Sensors: A Systematic Review

Internet of medical things (IoMT)-integrated biosensors for point-of-care testing of infectious diseases

Illuminating the immunopathology of SARS‐CoV‐2

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