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Methodological issues on prediction of clinical outcomes in patients with aneurysmal subarachnoid hemorrhage using computed tomography

  • Reza Fatahian
    Affiliations
    Clinical Research Development Centre, Taleghani and Imam Ali Hospital, Kermanshah University of Medical Sciences, Kermanshah, Islamic Republic of Iran
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  • Mehdi Naderi
    Correspondence
    Corresponding author at: Shahid Beheshtiv Blvd, Clinical Research Development Centre, Taleghani and Imam Ali Hospital, Kermanshah University of Medical Sciences, Kermanshah 6715847167, Islamic Republic of Iran.
    Affiliations
    Clinical Research Development Centre, Taleghani and Imam Ali Hospital, Kermanshah University of Medical Sciences, Kermanshah, Islamic Republic of Iran
    Search for articles by this author
Published:January 13, 2020DOI:https://doi.org/10.1016/j.jocn.2020.01.011

      Highlights

      • Methodological flaws in predicting clinical outcome can be catastrophic.
      • Correct prediction of clinical outcome of patients with subarachnoid hemorrhage using computed tomography.
      • How to predict a clinical outcome?

      Keywords

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      References

        • Kanazawa T.
        • Takahashi S.
        • Minami Y.
        • Jinzaki M.
        • Toda M.
        • Yoshida
        Early prediction of clinical outcomes in patients with aneurysmal subarachnoid hemorrhage using computed tomography texture analysis.
        J Clin Neurosci. 2020; 71: 144-149
        • Grobbee D.E.
        • Hoes A.W.
        Clinical epidemiology: principles, methods, and applications for clinical research.
        Jones & Bartlett Learning, 2009
        • Moons K.G.M.
        • Royston P.
        • Vergouwe Y.
        • Grobbee D.E.
        • Altman D.G.
        Prognosis and prognostic research: what, why, and how?.
        BMJ. 2009; 338
        • Szklo M.
        • Nieto F.J.
        Epidemiology beyond the basics.
        3rd ed. Jones and Bartlett Publisher, Manhattan, New York2014
        • Abbasi M.
        • Naderi M.
        What does need to know about developing clinical prediction models?.
        J Geriatr Oncol. 2019; 10: 369
        • Abbasi M.
        • Naderi M.
        Methodological issues on prediction of hepatocellular carcinoma after sustained virologic responses.
        Clin Gastroenterol Hepatol. 2019; 17: 1419