Developing Prediction Models for COVID-19 Outcomes: A Valuable Tool for Resource-Limited Hospitals

被引:5
作者
Popescu, Irina-Maria [1 ]
Margan, Madalin-Marius [2 ,11 ]
Anghel, Mariana [1 ]
Mocanu, Alexandra [3 ]
Laitin, Sorina Maria Denisa [1 ]
Margan, Roxana [4 ]
Capraru, Ionut Dragos [1 ]
Tene, Alexandra-Andreea [5 ]
Gal-Nadasan, Emanuela -Georgiana [6 ]
Cirnatu, Daniela [5 ,7 ]
Chicin, Gratiana Nicoleta [5 ,8 ]
Oancea, Cristian [9 ]
Anghel, Andrei [10 ]
机构
[1] Victor Babes Univ Med & Pharm, Dept Infect Dis, Discipline Epidemiol, Timisoara, Romania
[2] Victor Babes Univ Med & Pharm, Dept Funct Sci, Discipline Publ Hlth, Timisoara, Romania
[3] Victor Babes Univ Med & Pharm, Dept Infect Dis, Discipline Infect Dis, Timisoara, Romania
[4] Victor Babes Univ Med & Pharm, Dept Funct Sci, Discipline Physiol, Timisoara, Romania
[5] Reg Ctr Publ Hlth Timisoara, Timisoara, Romania
[6] Victor Babes Univ Med & Pharm, Dept Balneol Med Rehabil & Rheumatol, Discipline Med Rehabil, Timisoara, Romania
[7] Vasile Goldis Western Univ, Fac Med, Dept Med, Arad, Romania
[8] Vasile Goldis Western Univ, Fac Med, Dept Epidemiol Infect Dis & Prevent Med, Arad, Romania
[9] Victor Babes Univ Med & Pharm, Ctr Res & Innovat Precis Med Resp Dis, Timisoara, Romania
[10] Victor Babes Univ Med & Pharm, Dept Biochem & Pharmacol, Discipline Biochem, Timisoara, Romania
[11] Victor Babes Univ Med & Pharm, Eftimie Murgu Sq 2, Timisoara 300041, Romania
关键词
ANC; CRP; risk profiling; unfavourable outcome; RISK SCORE; DISEASE; LEUKOCYTOSIS; MORTALITY;
D O I
10.2147/IJGM.S419206
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Purpose: Coronavirus disease is a global pandemic with millions of confirmed cases and hundreds of thousands of deaths worldwide that continues to create a significant burden on the healthcare systems. The aim of this study was to determine the patient clinical and paraclinical profiles that associate with COVID-19 unfavourable outcome and generate a prediction model that could separate between high-risk and lowrisk groups. Patients and Methods: The present study is a multivariate observational retrospective study. A total of 483 patients, residents of the municipality of Timisoara, the biggest city in the Western Region of Romania, were included in the study group that was further divided into 3 sub-groups in accordance with the disease severity form. Results: Increased age (cOR=1.09, 95% CI: 1.06-1.11, p<0.001), cardiovascular diseases (cOR=3.37, 95% CI: 1.96-6.08, p<0.001), renal disease (cOR=4.26, 95% CI: 2.13-8.52, p<0.001), and neurological disorder (cOR=5.46, 95% CI: 2.71-11.01, p<0.001) were all independently significantly correlated with an unfavourable outcome in the study group. The severe form increases the risk of an unfavourable outcome 19.59 times (95% CI: 11.57-34.10, p<0.001), while older age remains an independent risk factor even when disease severity is included in the statistical model. An unfavourable outcome was positively associated with increased values for the following paraclinical parameters: white blood count (WBC; cOR=1.10, 95% CI: 1.05-1.15, p<0.001), absolute neutrophil count (ANC; cOR=1.15, 95% CI: 1.09-1.21, p<0.001) and C-reactive protein (CRP; cOR=1.007, 95% CI: 1.004-1.009, p<0.001). The best prediction model including age, ANC and CRP achieved a receiver operating characteristic (ROC) curve with the area under the curve (AUC) = 0.845 (95% CI: 0.813-0.877, p<0.001); cut-off value = Conclusion: This model and risk profiling may contribute to a more precise allocation of limited healthcare resources in a clinical setup and can guide the development of strategies for disease management.
引用
收藏
页码:3053 / 3065
页数:13
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