scholarly journals External validation of a clinical risk score to predict hospital admission and in-hospital mortality in COVID-19 patients

2020 ◽  
Vol 53 (1) ◽  
pp. 78-86
Author(s):  
Alexandra Halalau ◽  
Zaid Imam ◽  
Patrick Karabon ◽  
Nikhil Mankuzhy ◽  
Aciel Shaheen ◽  
...  
Author(s):  
Harold I. Zeliger ◽  
Harvey Kahaner

We have hypothesized that the Oxidative Stress Index (OSI) can be used to predict the severity of COVID-19. The recently published Clinical Risk Score Calculation (CRSC), based upon clinical data ascertained at the time of hospital admission for patients in 575 hospitals in China following the COVID-19 outbreak, confirms and validates our hypothesis.


BMJ Open ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. e040729 ◽  
Author(s):  
Carlo Fumagalli ◽  
Renzo Rozzini ◽  
Matteo Vannini ◽  
Flaminia Coccia ◽  
Giulia Cesaroni ◽  
...  

ObjectivesSeveral physiological abnormalities that develop during COVID-19 are associated with increased mortality. In the present study, we aimed to develop a clinical risk score to predict the in-hospital mortality in COVID-19 patients, based on a set of variables available soon after the hospitalisation triage.SettingRetrospective cohort study of 516 patients consecutively admitted for COVID-19 to two Italian tertiary hospitals located in Northern and Central Italy were collected from 22 February 2020 (date of first admission) to 10 April 2020.ParticipantsConsecutive patients≥18 years admitted for COVID-19.Main outcome measuresSimple clinical and laboratory findings readily available after triage were compared by patients’ survival status (‘dead’ vs ‘alive’), with the objective of identifying baseline variables associated with mortality. These were used to build a COVID-19 in-hospital mortality risk score (COVID-19MRS).ResultsMean age was 67±13 years (mean±SD), and 66.9% were male. Using Cox regression analysis, tertiles of increasing age (≥75, upper vs <62 years, lower: HR 7.92; p<0.001) and number of chronic diseases (≥4 vs 0–1: HR 2.09; p=0.007), respiratory rate (HR 1.04 per unit increase; p=0.001), PaO2/FiO2 (HR 0.995 per unit increase; p<0.001), serum creatinine (HR 1.34 per unit increase; p<0.001) and platelet count (HR 0.995 per unit increase; p=0.001) were predictors of mortality. All six predictors were used to build the COVID-19MRS (Area Under the Curve 0.90, 95% CI 0.87 to 0.93), which proved to be highly accurate in stratifying patients at low, intermediate and high risk of in-hospital death (p<0.001).ConclusionsThe COVID-19MRS is a rapid, operator-independent and inexpensive clinical tool that objectively predicts mortality in patients with COVID-19. The score could be helpful from triage to guide earlier assignment of COVID-19 patients to the most appropriate level of care.


2021 ◽  
Vol 36 (15) ◽  
Author(s):  
Ae-Young Her ◽  
Youngjune Bhak ◽  
Eun Jung Jun ◽  
Song Lin Yuan ◽  
Scot Garg ◽  
...  

2015 ◽  
Vol 221 (3) ◽  
pp. 689-698 ◽  
Author(s):  
Christopher R. Shubert ◽  
Amy E. Wagie ◽  
Michael B. Farnell ◽  
David M. Nagorney ◽  
Florencia G. Que ◽  
...  

EP Europace ◽  
2013 ◽  
Vol 16 (1) ◽  
pp. 40-46 ◽  
Author(s):  
K. Kraaier ◽  
M. F. Scholten ◽  
J. G. P. Tijssen ◽  
D. A. M. J. Theuns ◽  
L. J. L. M. Jordaens ◽  
...  

2021 ◽  
Vol 5 (3) ◽  
Author(s):  
Joanna Shim ◽  
David J Mclernon ◽  
David Hamilton ◽  
Hamish A Simpson ◽  
Marcus Beasley ◽  
...  

2015 ◽  
Vol 2 (1) ◽  
pp. e000060 ◽  
Author(s):  
Shamil Haroon ◽  
Peymane Adab ◽  
Richard D Riley ◽  
Tom Marshall ◽  
Robert Lancashire ◽  
...  

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