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  1. TI=Predictive Model and Risk Factors for Case Fatality of COVID 19: A Cohort of 21 392 Cases in Hubei China
  2. TI=Isolated Encephalopathy Without Severe Disease in a COVID 19 Patient: Case Presentation and Workup Strategies

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  1. Article ; Online: Predictive Model and Risk Factors for Case Fatality of COVID-19: A Cohort of 21,392 Cases in Hubei, China.

    Wu, Ran / Ai, Siqi / Cai, Jing / Zhang, Shiyu / Qian, Zhengmin Min / Zhang, Yunquan / Wu, Yinglin / Chen, Lan / Tian, Fei / Li, Huan / Li, Mingyan / Lin, Hualiang

    Innovation (New York, N.Y.)

    2020  Volume 1, Issue 2, Page(s) 100022

    Abstract: ... however, risk factors for the fatality of COVID-19 remain unclear. A total of 21,392 COVID-19 cases were recruited ... We adopted Cox regression models to investigate the risk factors for case fatality and predicted the death ... in the Hubei Province of China between December 2019 and February 2020, and followed up until March 18, 2020 ...

    Abstract An increasing number of patients are being killed by coronavirus disease 2019 (COVID-19), however, risk factors for the fatality of COVID-19 remain unclear. A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and followed up until March 18, 2020. We adopted Cox regression models to investigate the risk factors for case fatality and predicted the death probability under specific combinations of key predictors. Among the 21,392 patients, 1,020 (4.77%) died of COVID-19. Multivariable analyses showed that factors, including age (≥60 versus <45 years, hazard ratio [HR] = 7.32; 95% confidence interval [CI], 5.42, 9.89), sex (male versus female, HR = 1.31; 95% CI, 1.15, 1.50), severity of the disease (critical versus mild, HR = 39.98; 95% CI, 29.52, 48.86), comorbidity (HR = 1.40; 95% CI, 1.23, 1.60), highest body temperature (>39°C versus <39°C, HR = 1.28; 95% CI, 1.09, 1.49), white blood cell counts (>10 × 10
    Language English
    Publishing date 2020-08-03
    Publishing country United States
    Document type Journal Article
    ISSN 2666-6758
    ISSN (online) 2666-6758
    DOI 10.1016/j.xinn.2020.100022
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Predictive model and risk factors for case fatality of COVID-19: a cohort of 21,392 cases in Hubei, China

    Wu, Ran / Ai, Siqi / Cai, Jing / Zhang, Shiyu / Qian, Zhengmin / Zhang, Yunquan / Wu, Yinglin / Chen, Lan / Tian, Fei / Li, Huan / Li, Mingyan / Lin, Hualiang

    The Innovation

    Abstract: ... however, risk factors for the case fatality of COVID-19 have not yet been well studied Methods A total of 21,392 COVID ... 19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and ... clinical symptoms, and laboratory factors were confirmed to be important determinants of fatality of COVID-19 ...

    Abstract Background An increasing number of patients are being killed by coronavirus disease 2019 (COVID-19);however, risk factors for the case fatality of COVID-19 have not yet been well studied Methods A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and followed up until March 18, 2020 We adopted Cox regression models to investigate the risk factors for the case fatality and predicted the death probability under specific combinations of key predictors Results Among the 21,392 patients, 1,020 (4 77%) died of COVID-19 Multivariable analyses showed that factors including age [≥ 60 years versus 39°C versus 10 ×109/L versus (4-10) ×109/L, HR: 1 69;95% CI: 1 35, 2 13), and lymphocyte counts (<0 8 ×109/L versus (0 8-4) ×109/L, HR: 1 26;95% CI: 1 06, 1 50) were significantly associated with case fatality of COVID-19 patients Individuals of an older age, who were male, with comorbidities, and had a critical illness had the highest death probability, with 21%, 36%, 46%, and 54% within 1-4 weeks after the symptom onset Interpretation Risk factors, including demographic characteristics, clinical symptoms, and laboratory factors were confirmed to be important determinants of fatality of COVID-19 Our predictive model can provide scientific evidence for a more rational, evidence-driven allocation of scarce medical resources to reduce the fatality of COVID-19
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #692819
    Database COVID19

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  3. Article ; Online: Predictive Model and Risk Factors for Case Fatality of COVID-19

    Wu, Ran / Ai, Siqi / Cai, Jing / Zhang, Shiyu / Qian, Zhengmin (Min) / Zhang, Yunquan / Wu, Yinglin / Chen, Lan / Tian, Fei / Li, Huan / Li, Mingyan / Lin, Hualiang

    The Innovation

    A Cohort of 21,392 Cases in Hubei, China

    2020  Volume 1, Issue 2, Page(s) 100022

    Keywords covid19
    Language English
    Publisher Elsevier BV
    Publishing country us
    Document type Article ; Online
    ISSN 2666-6758
    DOI 10.1016/j.xinn.2020.100022
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

  4. Article ; Online: Predictive Model and Risk Factors for Case Fatality of COVID-19

    Ran Wu / Siqi Ai / Jing Cai / Shiyu Zhang / Zhengmin (Min) Qian / Yunquan Zhang / Yinglin Wu / Lan Chen / Fei Tian / Huan Li / Mingyan Li / Hualiang Lin

    The Innovation, Vol 1, Iss 2, Pp 100022- (2020)

    A Cohort of 21,392 Cases in Hubei, China

    2020  

    Abstract: ... however, risk factors for the fatality of COVID-19 remain unclear. A total of 21,392 COVID-19 cases were recruited ... We adopted Cox regression models to investigate the risk factors for case fatality and predicted the death ... clinical symptoms, and laboratory factors were confirmed to be important determinants of fatality of COVID-19 ...

    Abstract Summary: An increasing number of patients are being killed by coronavirus disease 2019 (COVID-19), however, risk factors for the fatality of COVID-19 remain unclear. A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020, and followed up until March 18, 2020. We adopted Cox regression models to investigate the risk factors for case fatality and predicted the death probability under specific combinations of key predictors. Among the 21,392 patients, 1,020 (4.77%) died of COVID-19. Multivariable analyses showed that factors, including age (≥60 versus <45 years, hazard ratio [HR] = 7.32; 95% confidence interval [CI], 5.42, 9.89), sex (male versus female, HR = 1.31; 95% CI, 1.15, 1.50), severity of the disease (critical versus mild, HR = 39.98; 95% CI, 29.52, 48.86), comorbidity (HR = 1.40; 95% CI, 1.23, 1.60), highest body temperature (>39°C versus <39°C, HR = 1.28; 95% CI, 1.09, 1.49), white blood cell counts (>10 × 109/L versus (4–10) × 109/L, HR = 1.69; 95% CI, 1.35, 2.13), and lymphocyte counts (<0.8 × 109/L versus (0.8–4) × 109/L, HR = 1.26; 95% CI, 1.06, 1.50) were significantly associated with case fatality of COVID-19 patients. Individuals of an older age, who were male, with comorbidities, and had a critical illness had the highest death probability, with 21%, 36%, 46%, and 54% within 1–4 weeks after the symptom onset. Risk factors, including demographic characteristics, clinical symptoms, and laboratory factors were confirmed to be important determinants of fatality of COVID-19. Our predictive model can provide scientific evidence for a more rational, evidence-driven allocation of scarce medical resources to reduce the fatality of COVID-19.
    Keywords COVID-19 ; fatality ; risk factor ; Science (General) ; Q1-390
    Subject code 610
    Language English
    Publishing date 2020-08-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

    More links

    Kategorien

    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

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