Prognostic Accuracy of the SIRS, qSOFA, and NEWS for Early Detection of Clinical Deterioration in SARS-CoV-2 Infected Patients

Jang, Jong Geol; Hur, Ji An; Hong, Kyung Soo; Lee, Wonhwa; Ahn, Jae‐Jun

doi:10.3346/jkms.2020.35.e234

Cited by 90 publications

(111 citation statements)

References 19 publications

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“…The National Early Warning Score 2 (NEWS2), based on vital signs, is the most used score in ED. Its predictive accuracy in COVID-19 patients is higher than other clinical risk scores [28,29], but the models developed in this study exceed this accuracy (AUC-ROC=0.94 and AUC-ROC=0.97 for severity and mortality respectively), as expected because the addition of other relevant variables.…”

Section: Discussioncontrasting

confidence: 47%

Development of Severity and Mortality Prediction Models for COVID-19 Patients at Emergency Department Including the Chest X-Ray

Batllés

Cerdá-Alberich²,

Fonfría-Esparcia

et al. 2020

Preprint

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Objectives: To develop prognosis prediction models for COVID-19 patients attending an emergency department (ED) based on initial chest X-ray (CXR), demographics, clinical and laboratory parameters. Methods: All symptomatic confirmed COVID-19 patients admitted to our hospital ED between February 24th and April 24th 2020 were recruited. CXR features, clinical and laboratory variables and CXR abnormality indices extracted by a convolutional neural network (CNN) diagnostic tool were considered potential predictors on this first visit. The most serious individual outcome defined the three severity level: 0) home discharge or hospitalization ≤ 3 days, 1) hospital stay >3 days and 2) intensive care requirement or death. Severity and in-hospital mortality multivariable prediction models were developed and internally validated. The Youden index was used for model selection.Results: A total of 440 patients were enrolled (median 64 years; 55.9% male); 13.6% patients were discharged, 64% hospitalized, 6.6% required intensive care and 15.7% died. The severity prediction model included oxygen saturation/inspired oxygen fraction (SatO2/FiO2), age, C-reactive protein (CRP), lymphocyte count, extent score of lung involvement on CXR (ExtScoreCXR), lactate dehydrogenase (LDH), D-dimer level and platelets count, with AUC-ROC=0.94 and AUC-PRC=0.88. The mortality prediction model included age, SatO2/FiO2, CRP, LDH, CXR extent score, lymphocyte count and D-dimer level, with AUC-ROC=0.97 and AUC-PRC=0.78. The addition of CXR CNN-based indices slightly improved the predictive metrics for mortality (AUC-ROC=0.97 and AUC-PRC=0.83).Conclusion: The developed and internally validated severity and mortality prediction models could be useful as triage tools for COVID-19 patients and they should be further validated at different ED.

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Section: Discussioncontrasting

confidence: 47%

Development of Severity and Mortality Prediction Models for COVID-19 Patients at Emergency Department Including the Chest X-Ray

Batllés

Cerdá-Alberich²,

Fonfría-Esparcia

et al. 2020

Preprint

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“…ARDS and septic shock are the main symptoms of severe COVID-19 patients, and are the leading causes of death. 50 , 51 In particular, we monitored high levels of activation of the selected treatment targets, SREBP-2 and NF-κB (Fig. 1 ).…”

Section: Discussionmentioning

confidence: 99%

COVID-19-activated SREBP2 disturbs cholesterol biosynthesis and leads to cytokine storm

Lee

Ahn

Park

et al. 2020

Sig Transduct Target Ther

Self Cite

115

106

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Sterol regulatory element binding protein-2 (SREBP-2) is activated by cytokines or pathogen, such as virus or bacteria, but its association with diminished cholesterol levels in COVID-19 patients is unknown. Here, we evaluated SREBP-2 activation in peripheral blood mononuclear cells of COVID-19 patients and verified the function of SREBP-2 in COVID-19. Intriguingly, we report the first observation of SREBP-2 C-terminal fragment in COVID-19 patients’ blood and propose SREBP-2 C-terminal fragment as an indicator for determining severity. We confirmed that SREBP-2-induced cholesterol biosynthesis was suppressed by Sestrin-1 and PCSK9 expression, while the SREBP-2-induced inflammatory responses was upregulated in COVID-19 ICU patients. Using an infectious disease mouse model, inhibitors of SREBP-2 and NF-κB suppressed cytokine storms caused by viral infection and prevented pulmonary damages. These results collectively suggest that SREBP-2 can serve as an indicator for severity diagnosis and therapeutic target for preventing cytokine storm and lung damage in severe COVID-19 patients.

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“…1 However, NEWS2 has been described as a robust tool to predict outcome during sepsis 2 and seems to predict evolution of COVID-19 upon admission to the hospital in other recently studies. [3][4][5] Considering the evolution of the epidemic, there is a need for reliable tools to predict some evolution in particular with regard to hospitalized patients, in order to discharge more quickly the patients from medical wards to home.…”

Section: Letter To the Editormentioning

confidence: 99%

The usefulness of NEWS2 at day 7 of hospitalization in predicting COVID-19 evolution and as an early endpoint in therapeutic trials

Sixt

Moretto

Devilliers

et al. 2021

Journal of Infection

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Prognostic Accuracy of the SIRS, qSOFA, and NEWS for Early Detection of Clinical Deterioration in SARS-CoV-2 Infected Patients

Cited by 90 publications

References 19 publications

Development of Severity and Mortality Prediction Models for COVID-19 Patients at Emergency Department Including the Chest X-Ray

Development of Severity and Mortality Prediction Models for COVID-19 Patients at Emergency Department Including the Chest X-Ray

COVID-19-activated SREBP2 disturbs cholesterol biosynthesis and leads to cytokine storm

The usefulness of NEWS2 at day 7 of hospitalization in predicting COVID-19 evolution and as an early endpoint in therapeutic trials

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