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“People who experience a single random seizure, for instance, are 50 times more likely to become epileptic than someone who has never had one” Given that epile

“People who experience a single random seizure, for instance, are 50 times more likely to become epileptic than someone who has never had one” Given that epilepsy is diagnosed and treated based on the presence of recurrent seizures, this seems like a tautology - the set of “at least one seizure” contains the set of “at least two seizures” Like saying “playing at least one game of basketball was associated with a greatly increased chance of playing more than one basketball game in a lifetime, compared to those who had never played”

sdwr 5y ago
The phrasing might sound bad from a math perspective, but they're trying to convey something important about the nature of seizures. Seizures act more like a learned skill than a typical illness. The first one primes the brain, and repeated seizures reinforce the pattern, making it easier to trigger.
- harry8 5y ago
  Not just might sound bad. It sounds like utter garbage in support of a theory rather than evidence. Bad mathematical reasoning here really does negate the the claim as anything more than "I wonder if ..." Could be true. Let's find out. Turning it around the probability that you have one and only one seizure could be exactly the same as the probability that you have a first seizure and it is NOT epilepsy. Those could well be different ways of saying precisely the same thing.
- whatshisface 5y ago
  Model A: First seizure causes subsequent seizures. Model B: Factor X causes many seizures in a sequence that, as sequences usually do, begins with the first. Any reason they prefer A over B? Maybe there is some evidence of learning, or a statistical fact that is true of seizures causing seizures but not of factor X causing them independently?
  - drdeca 5y ago
    What I'm about to say is just hypothetical, I know basically nothing about medicine. Suppose that seizures at one point didn't have an influence on the probability of seizures later. Then, that seems to me like it would mean that seizures were a kind of independent point process? Like, suppose there's a model where, depending on a person's genetics, age, and, idk, let's say diet, predicts a given rate of seizures, and also that this rate varies continuously with age. In such a model, I don't think we would tend to see something where a person has no seizures until a certain point in their life, and then subsequently begins to have them at roughly a given rate for some period of time, but it would seem compatible with the "seizures causing seizures" idea. Note: I am not claiming that this is what the data actually shows. I have no idea. But, on the other hand, if there were some other invisible property which can at some random point change from state A to state B, and in state B seizures are more common, but seizures don't influence whether in state A or in state B, I'm not sure you could distinguish that from the "seizures cause more seizures" idea? But, if the causal influence wasn't just "have they ever had a seizure", but instead all seizures had an impact on chance of seizure in the near future, then I think that would have statistical effects? tl;dr: I don't know what I'm talking about, but I suspect you could at least in principle distinguish the two models using some statistical properties.
- andai 5y ago
  I hear similar things about psychosis, it changes the brain in a way to increase the risk of future psychosis.
- elric 5y ago
  This is an interesting point. It's pretty common for people to start getting migraines after a head injury (concussion etc). Apparently the genetic component might already be present, but the disease can be dormant until "activated". Perhaps this, too, could be "unlearnt" somehow.
Deestan 5y ago
This can explained by following the reference to the study: > Two large-scale randomized trials provided definitive estimates of the risk of recurrence after an untreated first unprovoked, seizure. These are the multicenter study from Italy, FIR.S.T (First Seizure Trial Group, 1993) and the European-wide Multicenter Epilepsy and Single Seizure study or MESS, which included both first seizures and newly recognized epilepsy (Marson et al., 2005). Based on 193 patients randomized to deferred treatment only in the event of a second seizure (i.e., initially untreated), the FIR.S.T study reported recurrence risks of 18%, 28%, 41%, and 51% at 3, 6, 12, and 24 months after the initial seizure. In the MESS study, 408 patients with a first unprovoked seizure were randomized to the deferred treatment group. Their risk of recurrence at 6 months, 2, 5, and 8 years after randomization was 26%, 39%, 51%, and 52%. On average, the observational studies, taken as a whole, provide an estimate of the 2-year recurrence risk in the range of 40%, depending on aspects of the study design (Berg & Shinnar, 1991). > Both of the randomized trials, especially the second, demonstrate a pattern seen in virtually all of the long-term observational studies of first seizures. Specifically, the risk of a recurrence is highest during the period immediately after the initial seizure. The rate, at which first recurrences occur, drops off with increasing time since the first seizure. Across a number of studies with prolonged follow-up periods, 80–90% of individuals who recur do so within 2 years of the initial seizure (Annegers et al., 1986; Hopkins et al., 1988; Boulloche et al., 1989; Hauser et al., 1990; Shinnar et al., 1996).
- zepto 5y ago
  > the risk of a recurrence is highest during the period immediately after the initial seizure. This still isn’t helpful in determining whether the seizure itself makes another seizure more likely, or whether this just means that whatever caused the first seizure is still present. If there is an external factor that triggered the initial seizure, presumably the closer you are in time to the presence of that factor, the more likely it is that another will be triggered by the same factor.

sdwr 5y ago

The phrasing might sound bad from a math perspective, but they're trying to convey something important about the nature of seizures. Seizures act more like a learned skill than a typical illness. The first one primes the brain, and repeated seizures reinforce the pattern, making it easier to trigger.

harry8 5y ago
Not just might sound bad. It sounds like utter garbage in support of a theory rather than evidence. Bad mathematical reasoning here really does negate the the claim as anything more than "I wonder if ..." Could be true. Let's find out. Turning it around the probability that you have one and only one seizure could be exactly the same as the probability that you have a first seizure and it is NOT epilepsy. Those could well be different ways of saying precisely the same thing.
whatshisface 5y ago
Model A: First seizure causes subsequent seizures. Model B: Factor X causes many seizures in a sequence that, as sequences usually do, begins with the first. Any reason they prefer A over B? Maybe there is some evidence of learning, or a statistical fact that is true of seizures causing seizures but not of factor X causing them independently?
- drdeca 5y ago
  What I'm about to say is just hypothetical, I know basically nothing about medicine. Suppose that seizures at one point didn't have an influence on the probability of seizures later. Then, that seems to me like it would mean that seizures were a kind of independent point process? Like, suppose there's a model where, depending on a person's genetics, age, and, idk, let's say diet, predicts a given rate of seizures, and also that this rate varies continuously with age. In such a model, I don't think we would tend to see something where a person has no seizures until a certain point in their life, and then subsequently begins to have them at roughly a given rate for some period of time, but it would seem compatible with the "seizures causing seizures" idea. Note: I am not claiming that this is what the data actually shows. I have no idea. But, on the other hand, if there were some other invisible property which can at some random point change from state A to state B, and in state B seizures are more common, but seizures don't influence whether in state A or in state B, I'm not sure you could distinguish that from the "seizures cause more seizures" idea? But, if the causal influence wasn't just "have they ever had a seizure", but instead all seizures had an impact on chance of seizure in the near future, then I think that would have statistical effects? tl;dr: I don't know what I'm talking about, but I suspect you could at least in principle distinguish the two models using some statistical properties.
andai 5y ago
I hear similar things about psychosis, it changes the brain in a way to increase the risk of future psychosis.
elric 5y ago
This is an interesting point. It's pretty common for people to start getting migraines after a head injury (concussion etc). Apparently the genetic component might already be present, but the disease can be dormant until "activated". Perhaps this, too, could be "unlearnt" somehow.

Deestan 5y ago

This can explained by following the reference to the study: > Two large-scale randomized trials provided definitive estimates of the risk of recurrence after an untreated first unprovoked, seizure. These are the multicenter study from Italy, FIR.S.T (First Seizure Trial Group, 1993) and the European-wide Multicenter Epilepsy and Single Seizure study or MESS, which included both first seizures and newly recognized epilepsy (Marson et al., 2005). Based on 193 patients randomized to deferred treatment only in the event of a second seizure (i.e., initially untreated), the FIR.S.T study reported recurrence risks of 18%, 28%, 41%, and 51% at 3, 6, 12, and 24 months after the initial seizure. In the MESS study, 408 patients with a first unprovoked seizure were randomized to the deferred treatment group. Their risk of recurrence at 6 months, 2, 5, and 8 years after randomization was 26%, 39%, 51%, and 52%. On average, the observational studies, taken as a whole, provide an estimate of the 2-year recurrence risk in the range of 40%, depending on aspects of the study design (Berg & Shinnar, 1991). > Both of the randomized trials, especially the second, demonstrate a pattern seen in virtually all of the long-term observational studies of first seizures. Specifically, the risk of a recurrence is highest during the period immediately after the initial seizure. The rate, at which first recurrences occur, drops off with increasing time since the first seizure. Across a number of studies with prolonged follow-up periods, 80–90% of individuals who recur do so within 2 years of the initial seizure (Annegers et al., 1986; Hopkins et al., 1988; Boulloche et al., 1989; Hauser et al., 1990; Shinnar et al., 1996).

zepto 5y ago
> the risk of a recurrence is highest during the period immediately after the initial seizure. This still isn’t helpful in determining whether the seizure itself makes another seizure more likely, or whether this just means that whatever caused the first seizure is still present. If there is an external factor that triggered the initial seizure, presumably the closer you are in time to the presence of that factor, the more likely it is that another will be triggered by the same factor.