Study for the Improvement of Long-Term Outcome Prediction in Patients in Coma After Cardiac Arrest
Condition: Anoxic-Ischemic Encephalopathy
MeSH terms: Brain Diseases; Brain Ischemia; Hypoxia-Ischemia, Brain
Study type: Observational [Patient Registry]

Summary: 
      The primary objective of HOPE is to improve the accuracy of outcome prediction in
      anoxic-ischemic encephalopathy following cardiac arrest by bringing under close scrutiny some
      of the existing methods used for this purpose (e.g. somato-sensory evoked potentials). HOPE
      is the first multicenter prospective cohort study on coma prognosis to control for the effect
      of a possible self-fulfilling prophecy at the ICU and to cover the acute and
      neurorehabilitation phases with a long-term follow-up longer than the usual three or six
      months.
    

Detailed description: 
      HOPE conducts a 2.5-year multicenter prospective cohort study in Germany on outcome
      prediction in the early stages of coma caused by cerebral hypoxia-ischemia.

      The main features of the project are:

        -  Control for a self-fulfilling prophecy

        -  Long-term follow-up (12 months) covering acute and neurorehabilitation phases

        -  Use of sensitive measures of level of consciousness

        -  Further in-depth and systematic examination of the predictive value of somato-sensory
           evoked potentials (SSEP)

      Using as a reference existing guidelines and previous research, we consider the following
      factors to be predictors of a negative outcome with a high specificity of > 90% with small
      95% confidence intervals: loss of cortical N20 SEP potentials, loss of more than one brain
      stem reflex, non-reactive EEG, or a NSE above 33 mcg/L. We refer to the presence of any of
      these specific unfavourable test results during the ICU treatment as a "negative predictor".
      Therefore, our null hypothesis is that the probability of a favourable outcome, despite the
      presence of a negative predictor, is < 10%. We will use Simon's two-stage design. The null
      hypothesis will be tested against a one-sided alternative. In the first stage, we will accrue
      72 patients. If there are 8 or fewer good outcomes in these 72 patients, the study will be
      discontinued because the null hypothesis could not be rejected. Otherwise, we will recruit
      100 additional patients to gather a total of 172. The null hypothesis will be rejected if 28
      or more favourable outcomes are observed in these 172 patients. This design yields a type I
      error rate of 0.05 and power of 80% if the true response rate is 25%, i.e. if indeed 25% or
      more patients have a favourable outcome despite a negative predictor. This calculation is
      based on the assumption that 25% of the enrolled patients have at least one negative
      predictor.

      HOPE has seven data entry points (i.e. study visits).The primary endpoints are completion of
      the follow-up period or patient death. HOPE collects clinical and demographic data in
      accordance to Utstein-style recommendations. The most crucial part of the study is
      determining the current level of consciousness by means of the revised version of the Coma
      Recovery Scale (CRS-R). The CRS-R allows a precise categorization of the current level of
      consciousness based on a structured and systematic clinical examination of auditory, visual,
      motor, oromotor, communication and arousal functions. Other assessment instruments employed
      yield information about functional outcome/ADL, neuropsychological performance, and
      health-related quality of life.

      Study centers will collect data prospectively following a data acquisition timeline (e.g. t0
      to t6). Visits t0 to t2 will take place at acute-setting ICUs; visits t3 to t5 at
      neurorehabilitation centers; and visit t6 at the patients' location of residence 12 months
      after day 0. A manual and data dictionary will be provided to all centres along with the case
      report forms (CRF). All study centers will send pseudonymized data weekly by certified mail
      to the Central Study Centre (CSC) located at the Department of Neurology of the University of
      Munich. All study centres, including the CSC, will check the data for completeness,
      plausibility, accuracy, consistency and outliers. Legal representatives of coma patients, who
      decline to participate, will be asked to provide data on socio-demographic variables and
      reason for declining. The CSC will store the data at a database and will be responsible for
      safeguarding and analysing it. Patients/Legal representatives will be asked to remain in the
      study for a further follow-up. After completion of the follow-up period, datasets will be
      irreversibly anonymised.

      We will analyze the positive predictive value of a dichotomous prognostic marker (favorable
      or unfavourable SSEP). For this purpose, we will use two definitions of favorable outcome,
      i.e. a functional and a behavioral one. If outcome is defined with respect to independence in
      daily life, we will use a modified Rankin Scale score of 0-3 (no symptoms - moderate
      disability, but able to walk independently) to categorize a favorable functional outcome. In
      the context of a catastrophic event such as cardiac arrest with high likelihood of permanent
      VS, it is our experience that some patients and families consider regaining functional
      communications skills also a favourable outcome. In a separate analysis, we will therefore
      use the recovery of full consciousness as measured by the CRS-R to define a favorable
      behavioral outcome. To analyse the effect of covariates on functional and behavioral
      outcomes, we will use mixed effects regression models, including both fixed and random
      effects. This method of analyzing longitudinal data is highly effective to examine change
      trajectories with several unequally spaced waves of data. Covariates will be sociodemographic
      variables, prognostic variables and treatment factors (e.g. use of therapeutic hypothermia),
      adjusted for age and sex.
    

Observational model: Cohort
Time perspective: Prospective
Sampling method: Probability Sample
Study population: 
        Patients with anoxic-ischemic encephalopathy following cardiac arrest.
      
Keywords: Outcome Prediction; Anoxic-Ischemic Encephalopathy; Coma; Vegetative State; Minimally Conscious State; Chronic Disorders of Consciousness