Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19

Struyf, Thomas; Deeks, Jonathan J; Dinnes, Jacqueline; Takwoingi, Yemisi; Davenport, Clare; Leeflang, Mariska; Spijker, René; Hooft, Lotty; Emperador, Devy; Domen, Julie; Tans, Anouk; Janssens, Stéphanie; Wickramasinghe, Dakshitha; Lannoy, Viktor; Horn, Sebastiaan R A; Bruel, Ann Van den

doi:10.1002/14651858.cd013665.pub3

Cited by 96 publications

(64 citation statements)

References 237 publications

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“…In July 2020, Nigeria had conducted 834 COVID-19 tests per million population with a daily average testing rate of 0�02 per 1,000 people compared to 34,678 and 0�31, respectively, in South Africa and 10,388 and 0�04 in Ghana, respectively [5]. Low testing rates were initially driven by difficulties in procuring sufficient reagents, few testing laboratories in the country, and testing hesitancy due to stigma around COVID-19 as well as testing guidelines which targeted individuals with symptoms consistent with COVID- 19.…”

Section: Introductionmentioning

confidence: 99%

Seroprevalence of SARS-CoV-2 in four states of Nigeria in October 2020: A population-based household survey

Audu

Stafford²,

Steinhardt³

et al. 2022

PLOS Glob Public Health

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The observed epidemiology of SARS-CoV-2 in sub-Saharan Africa has varied greatly from that in Europe and the United States, with much lower reported incidence. Population-based studies are needed to estimate true cumulative incidence of SARS-CoV-2 to inform public health interventions. This study estimated SARS-CoV-2 seroprevalence in four selected states in Nigeria in October 2020. We implemented a two-stage cluster sample household survey in four Nigerian states (Enugu, Gombe, Lagos, and Nasarawa) to estimate age-stratified prevalence of SARS-CoV-2 antibodies. All individuals in sampled households were eligible for interview, blood draw, and nasal/oropharyngeal swab collection. We additionally tested participants for current/recent malaria infection. Seroprevalence estimates were calculated accounting for the complex survey design. Across all four states, 10,629 (96·5%) of 11,015 interviewed individuals provided blood samples. The seroprevalence of SARS-CoV-2 antibodies was 25·2% (95% CI 21·8–28·6) in Enugu State, 9·3% (95% CI 7·0–11·5) in Gombe State, 23·3% (95% CI 20·5–26·4) in Lagos State, and 18·0% (95% CI 14·4–21·6) in Nasarawa State. Prevalence of current/recent malaria infection ranged from 2·8% in Lagos to 45·8% in Gombe and was not significantly related to SARS-CoV-2 seroprevalence. The prevalence of active SARS-CoV-2 infection in the four states during the survey period was 0·2% (95% CI 0·1–0·4). Approximately eight months after the first reported COVID-19 case in Nigeria, seroprevalence indicated infection levels 194 times higher than the 24,198 officially reported COVID-19 cases across the four states; however, most of the population remained susceptible to COVID-19 in October 2020.

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Section: Introductionmentioning

confidence: 99%

Seroprevalence of SARS-CoV-2 in four states of Nigeria in October 2020: A population-based household survey

Audu

Stafford²,

Steinhardt³

et al. 2022

PLOS Glob Public Health

View full text Add to dashboard Cite

show abstract

“…The classic physical presentation of COVID-19 symptoms consists of fever, chills, shortness of breath or difficulty breathing, nasal congestion, fatigue, muscle aches, headache, newly acquired loss of sense of taste and smell, swelling and discoloration of one or several toes or fingers, nausea or vomiting, and diarrhea; there are also reports of body rash and swelling and/or discoloration of the fingers or toes (Struyf et al, 2021). The infectious processes range from a disease presentation consisting of mild symptoms to a deadly multiorgan failure.…”

Section: Covid-19 Diagnosis: a Risk To Human Adaptive Systemsmentioning

confidence: 99%

Roy Adaptation Model: Theory-Based Knowledge and Nursing Care With a Person Experiencing COVID-19

et al. 2022

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Nursing theories shed light and guide nursing care through provision of care to persons based on the specialized knowledge base of the profession. Nurses utilizing Roy’s adaptation model deliver holistic care by accounting for people, processes, and the environments. The aim of this article is to illustrate the value of utilizing the Roy adaptation model in the care of a patients by reviewing nursing care provided to a patient diagnosed with COVID-19.

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“…Most individuals infected by the virus can suffer from undetectable, mild to severe symptoms. The common symptoms of COVID-19 are fever, dry cough, sore throat, and loss of smell and taste [3]. With proper medication and sufficient social distancing, an infected person can recover from the virus from treatment at home.…”

Section: Introductionmentioning

confidence: 99%

Obstructive Sleep Apnea (OSA) and COVID-19: Mortality Prediction of COVID-19-Infected Patients with OSA Using Machine Learning Approaches

Raihan

Shams

2022

COVID

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COVID-19, or coronavirus disease, has caused an ongoing global pandemic causing un-precedented damage in all scopes of life. An infected person with underlaying medical conditions is at greater risk than the rest of the population. Obstructive sleep apnea (OSA) is an illness associated with disturbances during sleep or an unconscious state with blockage of the airway passage. The comobordities of OSA with high blood pressure, diabetes, obesity, and age can place the life of an already infected COVID-19 patient into danger. In this paper, a prediction model for the mortality of a COVID-infected patient suffering from OSA is developed using machine learning algorithms. After an extensive methodical search, we designed an artificial neural network that can predict the mortality with an overall accuracy of 99% and a precision of 100% for forecasting the fatality chances of COVID-infected patients. We believe our model can accurately predict the mortality of the patients and can therefore assist medical health workers in predicting and making emergency clinical decisions, especially in a limited resource scenario, based on the medical history of the patients and their future potential risk of death. In this way, patients with a greater risk of mortality can receive timely treatment and benefit from proper ICU resources. Such artificial intelligent application can significantly reduce the overall mortality rate of vulnerable patients with existing medical disorders.

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Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19

Abstract: Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19 (Review)

Cited by 96 publications

References 237 publications

Seroprevalence of SARS-CoV-2 in four states of Nigeria in October 2020: A population-based household survey

Seroprevalence of SARS-CoV-2 in four states of Nigeria in October 2020: A population-based household survey

Roy Adaptation Model: Theory-Based Knowledge and Nursing Care With a Person Experiencing COVID-19

Obstructive Sleep Apnea (OSA) and COVID-19: Mortality Prediction of COVID-19-Infected Patients with OSA Using Machine Learning Approaches

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