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Prognosis Score System to Predict Survival for COVID-19 Cases: a Korean Nationwide Cohort Study.
Cho, Sung-Yeon; Park, Sung-Soo; Song, Min-Kyu; Bae, Young Yi; Lee, Dong-Gun; Kim, Dong-Wook.
  • Cho SY; Catholic Hematology Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Park SS; Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Song MK; Catholic Hematology Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Bae YY; Division of Hematology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
  • Lee DG; Data Research Institute, YMDtech Inc, Seoul, Republic of Korea.
  • Kim DW; St. Mary's Gong-Gam Mental Health Clinic, Siheung-si, Gyeonggi-do, Republic of Korea.
J Med Internet Res ; 23(2): e26257, 2021 02 22.
Article in English | MEDLINE | ID: covidwho-1574035
ABSTRACT

BACKGROUND:

As the COVID-19 pandemic continues, an initial risk-adapted allocation is crucial for managing medical resources and providing intensive care.

OBJECTIVE:

In this study, we aimed to identify factors that predict the overall survival rate for COVID-19 cases and develop a COVID-19 prognosis score (COPS) system based on these factors. In addition, disease severity and the length of hospital stay for patients with COVID-19 were analyzed.

METHODS:

We retrospectively analyzed a nationwide cohort of laboratory-confirmed COVID-19 cases between January and April 2020 in Korea. The cohort was split randomly into a development cohort and a validation cohort with a 21 ratio. In the development cohort (n=3729), we tried to identify factors associated with overall survival and develop a scoring system to predict the overall survival rate by using parameters identified by the Cox proportional hazard regression model with bootstrapping methods. In the validation cohort (n=1865), we evaluated the prediction accuracy using the area under the receiver operating characteristic curve. The score of each variable in the COPS system was rounded off following the log-scaled conversion of the adjusted hazard ratio.

RESULTS:

Among the 5594 patients included in this analysis, 234 (4.2%) died after receiving a COVID-19 diagnosis. In the development cohort, six parameters were significantly related to poor overall survival older age, dementia, chronic renal failure, dyspnea, mental disturbance, and absolute lymphocyte count <1000/mm3. The following risk groups were formed low-risk (score 0-2), intermediate-risk (score 3), high-risk (score 4), and very high-risk (score 5-7) groups. The COPS system yielded an area under the curve value of 0.918 for predicting the 14-day survival rate and 0.896 for predicting the 28-day survival rate in the validation cohort. Using the COPS system, 28-day survival rates were discriminatively estimated at 99.8%, 95.4%, 82.3%, and 55.1% in the low-risk, intermediate-risk, high-risk, and very high-risk groups, respectively, of the total cohort (P<.001). The length of hospital stay and disease severity were directly associated with overall survival (P<.001), and the hospital stay duration was significantly longer among survivors (mean 26.1, SD 10.7 days) than among nonsurvivors (mean 15.6, SD 13.3 days).

CONCLUSIONS:

The newly developed predictive COPS system may assist in making risk-adapted decisions for the allocation of medical resources, including intensive care, during the COVID-19 pandemic.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Diagnostic study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Aged / Female / Humans / Male / Middle aged Country/Region as subject: Asia Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Cohort study / Diagnostic study / Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Long Covid Limits: Aged / Female / Humans / Male / Middle aged Country/Region as subject: Asia Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2021 Document Type: Article