• Intensive care medicine · Nov 1994

    Randomized Controlled Trial Clinical Trial

    Contribution of non-neurologic disturbances in acute physiology to the prediction of intensive care outcome after head injury or non-traumatic intracranial haemorrhage.

    • M M Niskanen, A Kari, J A Hernesniemi, M P Vapalahti, E Iisalo, L Kaukinen, V Rauhala, E Saarela, and P Nikki.
    • Department of Intensive Care, Kuopio University Hospital, Finland.
    • Intensive Care Med. 1994 Nov 1;20(8):562-6.

    ObjectiveTo study the additional contribution of non-neurologic disturbances in acute physiology and chronic health to the prediction of intensive care outcome in patients with head injury or non-traumatic intracranial haemorrhage.DesignA nationwide study in Finland with prospectively collected data on all adult patients admitted to intensive care after head trauma or non-traumatic intracranial haemorrhage during a 14-month period. Two-thirds of the patients were randomly selected to derive predictive models, and the remaining one third constituted the validation sample.SettingA total of 25 medical and surgical ICUs in Finland (13 in tertiary referral centers).Patients901 consecutive adult patients with head injury or non-traumatic intracranial haemorrhage.Measurements And ResultsVariables of the APACHE II including Glasgow Coma Score were collected at the time of ICU admission. Two predictive models were created to explain hospital mortality. The addition of variables describing acute physiology to a predictive model consisting of Glasgow Coma Score, age, diagnosis of head injury and the type of ICU admission did not increase its performance in discriminating between survivors and nonsurvivors, but the calibration accuracy of the predictive model especially at the high ranges of risk was improved.ConclusionsThe non-neurologic disturbances in acute physiology have prognostic significance in the prediction of intensive care outcome in patients with head injury or non-traumatic intracerebral haemorrhage. The created predictive model may supplement clinical judgement of this patient group.

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