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On Sat, 6 Jul 1996 19:05:43 -0700 (PDT), you wrote:
>Rich,
>
>My purpose here is not to add *unknown*, or more accurately unquantifiable
>variables to the algorithms of nitrogen absorption, but to add a *known*
>variable, using straightforward pharmacokinetic principles.
>Over the past twenty years, the science of pharmacokinetics, the study of
>distribution and elimination of drugs has entered into the mainstream of
>medical care. Most drugs we ingest (like nitrogen) have some leeway
>between the therapeutic and toxic doses.
I dont think you can apply this analogy in this way.The comparison of
N2 absorption/elimination to drug absorption /elimination has some
validity,but in the case of DCS,arent we talking about a mechanical
process instead of a chemical one?In the case of DCS,if you want to
consider symptoms as a "toxic" reaction,these do not occur until you
enter the elimination phase of the profile.For drugs,the toxic
reaction occurs when you reach a range of accumulation or
concentration in the tissues or blood.I think maybe there may be some
comparison if you think in terms of non-linear pharmacokinetics;that
is,when some parameter of the elimination equation exceeds a certain
value,elimination characteristics change drastically.An example of
this would be a carrier-mediated elimination,as in the case of a drug
like phenytoin (an anti-convulsant used in treatment of epilepsy).When
the carrier medium reaches saturation,the drug cannot be eliminated
any faster,and concentration goes up rapidly with any additional dose.
Chaos math may have some
>application in determining stochastic events (like sudden, life
>threatening allergy to a drug) but most of the time, pharmacokinetic
>modeling (just like N2 absorption algorithms) deal with what happens to
>most folks.
>
>
>The Navy and other tables for NDL were developed empirically,
>tested and modified by actual experience. This is analogous to Phase I
>testing of a new drug. DAN is collecting data and profiles on a million
>"sport" dives. This is similar to post-marketing testing of a drug; N2 in
>this case.
Just a bit of nitpicking here.The above corresponds to phase 2-4 of
clinical testing .In phase I,a drug is first tested as a single dose
on a single healthy volunteer.This is then expanded to 20-25
individuals,with increasing dosages until either a pharmacological
effect is achieved or a toxicity is observed.Phase II is a further
expansion to include 100 to 300 individuals with the appropriate
disease states,and Phase III is a further expansion to 1,000 to 3,000
individuals,where they try and test the drug on various demographic
groups,such as age,gender,race,etc.Phase IV is the post-marketing
testing.
Now if you believe that all DCI events are stochastic then the
>latter type of study or analyses of the data will not be helpful in
>preventing them. Similarly, we can postulate all sorts and types of other
>variables that *may* affect the incidence of DCI. But the
>pharmacokinetics of nitrogen is what the tables (and algorithms) are all
>about. This is not a *new* variable like, say the effect of complement on
>bubble mechanics.
>
>
>My point is this: You cannot accurately model the distribution and
>elimination of a drug without knowing the volume of distribution (Vd) in
>the body of that drug. You can't determine the Vd unless
>you know something about the size of that "body" i.e.,person. If the
>relative concentration of the drug is small in relationship to the volume
>of distribution, big variations in body mass can occur without
>changing the concentration greatly. A two fold increase in Vd halves the
>concentration, but if it goes from 0.008 mg/dl to 0.004 mg/dl, it probably
>won't have much biologic/pharmacologic effect.
Depends on the drug some drugs have a *very* narrow therapeutic window
(the range between efficacy and toxicity)like digoxin,where the normal
serum levels are .001 to .002 mg/dl
But nitrogen is present in
>high concentration in our bodies (~79%, maybe less). So differences in
>body size and so Vd are likely to play a *great* role in N2 elimination.
yes,but other factors may be as important or more so.If you want to
use analogies,a more appropriate one might be protein binding.In this
case,the drug as a greater affinity for a particular type of
tissue/molecule.Binding reduces the amount of free drug in the
system,causing a very large APPARENT volume of distribution.Factors
that affect binding can cause a large change in the apparent volume of
distribution,and therefor the amount of drug in the circulation.
>It wasn't taken into account in the tables, because without some way of
>measuring the number of breaths taken at a given depth, not just the total
>gas breathed, it is almost impossible to know whether you were on-gassing
>or off-gassing a compartment at that moment. But now with air integrated
>computers, it is possible.
>
>I still think that the tables can be improved through the application of
>other medical disciplines, anesthesiology, physiology, pharmacology. I may
>be wrong, but I'll learn a lot trying.
>
>Safer diving through wiser physiology
>
>Peter Heseltine
>
>--
>Send mail for the `techdiver' mailing list to `techdiver@terra.net'.
>Send subscription/archive requests to `techdiver-request@terra.net'.
John L. Dunk
Tallahassee,Fl.
screwloose@ne*.co*
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