In view of the increasing need for organ transplants( possibly because of the greater ability of the surgeons and physicians to both execute the transplant, prevent a rejection, and/or diagnose the need to transplant) how could one minimize the Type I statistical error (the possibility that while the patient is not brain dead he is diagnosed as such) when testing for brain death?

It is a waste of resources to wait for metabolic death clinging to a life that cannot be saved thence omitting the duty to save people.

Nonetheless the duty to omit killing people actively/intently is even greater. This is exactly what we are doing when we remove the life support of someone in a chronic vegetative state( we will not go to jail only because at that time as medical standards mandate we wrongly assumed/believed they were brain dead, i.e We acted according to the medical standards but nonetheless came to a wrong conclusion/diagnosis).

Being a layman( I studied(partialy, uncomplete course) medicine aspiring to be a radiation oncologist and devote myself to proton therapy and carbon-ion radiation therapy for the brain probably due to my own PMA) I am absolutely terrified in the thought of being mistakenly diagnosed brain dead while being in vegetative state. I want my body to be useful even after I die I am just reluctant to sign up for organ donation because it might put even more stress on the already hectic life of physicians and increase the probability of a False Positive. Albeit being a cancer patient I could not even donate blood.

Therefore could a straight 48-hour or 72-hour recording of an EEG with as many non-redundant and carrefuly placed electrodes prove useful in reducing false positives? Is there a better alternative. Being a sufficient condition( or as close to it as possible) with the least necessary conditions.

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    $\begingroup$ I think you mean a Type I error: the null hypothesis is that the patient is alive. A Type I error would be concluding that someone is brain dead despite them being alive: a rejection of the null hypothesis when it should not be rejected. Also called a False Positive. Is there any evidence that the type I error rate for diagnosis of brain death is anything more than negligible using current methodology? $\endgroup$
    – Bryan Krause
    Commented Jan 10, 2020 at 22:49
  • $\begingroup$ And of course we want the probability of incorrectly determining death to be as small as possible, but you are asking about reducing false positives. If the false positive rate is already vanishingly low, there is no way to measure whether an intervention intended to reduce the false positive rate actually does so. $\endgroup$
    – Bryan Krause
    Commented Jan 10, 2020 at 23:14
  • $\begingroup$ @BryanKrause Probably having studied so many diverse things I got confused. First Economics then Medicine now Law. Regardless we could just interchange the null and the alternative in order to use the correct terminology. Forgive me for insisting on my error. If the null is brain death I am concerned with a false negative and if the null is not brain death I am concerned with a false positive. $\endgroup$ Commented Jan 10, 2020 at 23:46
  • $\begingroup$ @BryanKrause The importance of theory is exactly that explaining and predicting. We theoretically; with a pencil and a paper, math models( chemical models, physicall models), thought experiments, can predict that if we do X and the result is Y then it is sufficient to conclude Z. Conditon Y is necessary to observe Z. If Z is true as a logical consequence Y must also be true. Therefore X is a good Test a good Criterion. $\endgroup$ Commented Jan 10, 2020 at 23:51
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    $\begingroup$ False positive is correct for your situation. But a false positive is a type I error, not type II. So you are looking for "theory" to tell you how to reduce false positives in brain death? That's fine for developing a hypothesis, but then you have to test your hypothesis. You are asking in your question "Could doing X reduce false positives?" The only way to answer that is empirically, by doing an experiment. What I am telling you is that experiment is likely impossible. $\endgroup$
    – Bryan Krause
    Commented Jan 11, 2020 at 0:27


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