Do the oxidative stress biomarkers predict COVID-19 outcome? An in-hospital cohort study

Neves, Fábio Fernandes; Pott-Júnior, Henrique; Yamashita, Kouhei; Santos, Suelen Silvana dos; Cominetti, Márcia Regina; Freire, Caio César de Melo; Cunha, Anderson Ferreira da; Júnior, Alceu Afonso Jordão

doi:10.1016/j.freeradbiomed.2023.06.026

Cited by 5 publications

(1 citation statement)

References 39 publications

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“…Healthcare institutions are in high demand of tools for quick evaluation of patient status severity or resource planning. However, assessments of the severity of the condition often vary, ranging from outcomes like in-hospital death [1][2][3] or need for intensive care [4] to specific health indicators like respiratory distress [5][6][7] or organ failure markers [7,8]. Although there is an essential need to stratify patients according to their disease severity, the diversity in assessments makes it challenging to establish a standardized approach to measure and compare the severity of COVID-19 cases across different healthcare facilities and regions.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the disease severity in patients hospitalized for COVID-19 based on the National Early Warning Score (NEWS) using statistical and machine learning methods: An electronic health records database analysis

Lycholip,

Puronaitė,

Skorniakov

et al. 2023

THC

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BACKGROUND: The coronavirus disease 2019 (COVID-19) was a cause of concern in the healthcare system and increased the need for disease severity indicators. However, they still vary in use to evaluate in-hospital outcomes and severity. National Early Warning Score (NEWS) is routinely used to evaluate patient health status at the hospital. Further research is needed to ensure if NEWS can be a good instrument for an overall health status assessment with or without additional information like laboratory tests, intensive care needs, and history of chronic diseases. OBJECTIVE: To evaluate if NEWS can be an indicator to measure COVID-19 patient status in-hospital. METHODS: We used the fully anonymized Electronic Health Records (EHR) characterizing patients admitted to the hospital with COVID-19. Data was obtained from Vilnius University Hospital Santaros Klinikos EHR system (SANTA-HIS) from 01-03-2020 to 31-12-2022. The study sample included 3875 patients. We created several statistical and machine learning models for discrimination between in-hospital death/discharge for evaluation NEWS as a disease severity measure for COVID-19 patients. In these models, two variable sets were considered: median NEWS and its combination with clinical parameters and medians of laboratory test results. Assessment of models’ performance was based on the scoring metrics: accuracy, sensitivity, specificity, area under the ROC curve (AUC), and F1-score. RESULTS: Our analysis revealed that NEWS predictive ability for describing patient health status during the stay in the hospital can be increased by adding the patient’s age at hospitalization, gender, clinical and laboratory variables (0.853 sensitivity, 0.992 specificity and F1-score – 0.859) in comparison with single NEWS (0.603, 0.995, 0.719, respectively). A comparison of different models showed that stepwise logistic regression was the best method for in-hospital mortality classification. Our findings suggest employing models like ours for advisory routine usage. CONCLUSION: Our model demonstrated incremental value for COVID-19 patient’s status evaluation.

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Section: Introductionmentioning

confidence: 99%

Assessment of the disease severity in patients hospitalized for COVID-19 based on the National Early Warning Score (NEWS) using statistical and machine learning methods: An electronic health records database analysis

Lycholip,

Puronaitė,

Skorniakov

et al. 2023

THC

View full text Add to dashboard Cite

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Anti-inflammatory and nutritional interventions against SARS-CoV-2: A comprehensive review

Mu,

Akan,

Lin

et al. 2024

Journal of Agriculture and Food Research

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Nutrition and immunity: lessons from coronavirus disease-2019

Calder

2023

Proc. Nutr. Soc.

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This review will provide an overview of the immune system and then describe the effects of frailty, obesity, specific micronutrients and the gut microbiota on immunity and susceptibility to infection including data from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic where relevant. A key role for the immune system is providing host defence against pathogens. Impaired immunity predisposes to infections and to more severe infections and weakens the response to vaccination. A range of nutrients, including many micronutrients, play important roles in supporting the immune system to function. The immune system can decline in later life and this is exaggerated by frailty. The immune system is also weakened with obesity, generalised undernutrition and micronutrient deficiencies, which all result in increased susceptibility to infection. Findings obtained during the SARS-CoV-2 pandemic support what was already known about the effects of ageing, frailty and obesity on immunity and susceptibility to infection. Observational studies conducted during the pandemic also support previous findings that multiple micronutrients including vitamins C, D and E, zinc and selenium and long-chain n-3 fatty acids are important for immune health, but whether these nutrients can be used to treat those already with coronavirus disease discovered in 2019 (COVID-19), particularly if already hospitalised, is uncertain from current inconsistent or scant evidence. There is gut dysbiosis in patients with COVID-19 and studies with probiotics report clinical improvements in such patients. There is an inverse association between adherence to a healthy diet and risk of SARS-CoV-2 infection and hospitalisation with COVID-19 which is consistent with the effects of individual nutrients and other dietary components. Addressing frailty, obesity and micronutrient insufficiency will be important to reduce the burden of future pandemics and nutritional considerations need to be a central part of the approach to preventing infections, optimising vaccine responses and promoting recovery from infection.

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Do the oxidative stress biomarkers predict COVID-19 outcome? An in-hospital cohort study

Cited by 5 publications

References 39 publications

Assessment of the disease severity in patients hospitalized for COVID-19 based on the National Early Warning Score (NEWS) using statistical and machine learning methods: An electronic health records database analysis

Assessment of the disease severity in patients hospitalized for COVID-19 based on the National Early Warning Score (NEWS) using statistical and machine learning methods: An electronic health records database analysis

Anti-inflammatory and nutritional interventions against SARS-CoV-2: A comprehensive review

Nutrition and immunity: lessons from coronavirus disease-2019

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