2019.1 SAQ 11 – TCI propofol

Describe the principles of how a computer-controlled infusion device targets and maintains a constant effect site concentration of propofol.

This is an important topic unfortunately not covered well in many of the standard texts. Miller’s Anaesthesia Ch 28 discusses the topic and there is a BJA Education article discussing the topic.

BT_GS 1.59 Describe the pharmacological principles of and sources of error with target controlled infusion

TCI devices operate on a three compartmental model T/F

The effect site is an extra compartment of very tiny volume connected to the central compartment T/F

Drug is administered into, and eliminated from, the central compartment T/F

Rate of movement into the effect site compartment is described by the rate constant keo T/F

Infusion rates take into account redistribution and elimination of the drug

Bolus and rate of infusion are determined reach and maintain either a plasma or effect site concentration T/F

The time to peak effect following the bolus administration is independent of the dose given T/F

The rate constants and volume of the compartments depend on the TCI model used T/F

The Marsh model adjust the programme based on patient age T/F

In the Marsh model V1 is a fixed volume T/F

Next time you are using a TCI on a patient, take a close look at what the machine is doing. How does the initial bolus dose compare to what you would normally give? What happens when you adjust the rate up/down? What is the infusion rate at 9 mins vs 90 mins if you keep the target stable? How would these answers differ if you used a different model?

BT_GS 1.8 Drug absorption

I find it hard to believe that there have been no posts yet on this topic. Here is a link to the a post on transdermal absorption of drugs which as asked in an SAQ in 2018. I can’t see any others

You will find the answer to these in any pharmacology book. Here is an article on PK in general from BJA Education

BT_GS 1.8Describe absorption and factors that will influence it with reference to clinically utilised sites of administration

Bioavailability depends on both absorption and metabolism T/F

By definition, bioavailability of a drug is 100% if given via the intravenous route T/F

The stomach is the major site of absorption for orally administered drugs T/F

Lipophilic drugs will be preferentially absorbed by the GIT T/F

Low cardiac output states will increase drug absorption and this is why onset of inhalational anaesthesia is faster in low cardiac ouput states T/F

The gut wall is a site of signicant drug metabolism for drugs such as dopamine limiting absorption into the portal circulation T/F

All absorption in the GIT occurs through passive diffusion T/F

BT_GS 1.42 and BT_PM 1.17 Describe the pharmacokinetics of intravenous opioids

I visited the Escher X Nendo exhibition at the NGV on Friday. The work was amazing, but my phone died almost as I walked in the door Here is the one image I managed to capture – a lino cut produced as a 19yr old.

I find it hard to believe that this has not already been covered elsewhere, but it is still in the list of “left over” LOs, so just in case I’ll cover it today.

I think there is very little point memorising a huge list of pharmacokinetic numbers for drugs. The only reason to know these numbers is to enable you to predict how the body will handle the drug, influencing a drug’s behaviour both in states of normal, and abnormal, physiology. As most traditional opioids have very similar pharmacodynamic effects, pharmacokinetic factors usually influence drug selection.

Some standout numbers may be worthwhile committing to memory, but only to help illustrate the clinical implication. Otherwise, you just need to know ball park figures.

There are plenty of tables where you can find the pharmacokinetic numbers. It takes a little bit more thought to work out how they affect drug’s clinical behaviour

Most of the answers to today’s post can be found in the new edition of the Hemmings and Egan book (which I would have to say I am quite partial too…)

BT_GS 1.42 Describe the pharmacokinetics of intravenous opioids

BT_PM1.17 Pharmacokinetics of intravenous opioids and clinical relevance (I knew that this important topic couldn’t have been neglected – it wasn’t and here is my previous post under a duplicate LO)

All opioids are weak bases, so will be more ionised at a pH lower than their pKa T/F

The rapid onset of effect of alfentanil, can be largely attributed to its low pKa T/F

Fentanyl’s relatively rapid onset of effect is also due to a low pKa T/F

Both morphine and tramadol have metabolites active at the mu opioid receptor, with longer half lives than the parent drug T/F

For those opioids which are metabolised in the liver, hepatic blood flow is the main factor which limits the rate of metabolism T/F *

Morphine has a prolonged action when given intrathecally due to its low lipid solubility T/F

Fentanyl’s high lipid solubility helps account for a relatively rapid offset of effect after an single bolus T/F

* this one is actually a bit trickier than it may seem ( and not the same for all patients – hint, hint)

BT_GS 1.24 Describe the uptake, distribution and elimination of inhalational anaesthetic agents and the factors which influence induction and recovery from inhalational anaesthesia ….

T/F “MAC awake” is clinically meaningful, and should be targeted as the intended end-point during emergence

T/F patients need the same concentration of volatile agents during wound closure as they do during the middle of the operation

T/F While you are waking your patient up, you notice the monitor says “Fi sevo 0.0% ET sevo 1.0%”. Increasing the FGF from 6 L/min to 10 L/min will help speed washout.

T/F hypoventilation will slow washout

T/F high cardiac output will slow washout

T/F morbidly obese patients have an increase in both muscle and fat tissue – both can act as a reservoir of volatile anaesthetic especially after long cases

T/F the amount of volatile which is likely to have been taken up into fat (for a given partial pressure) is approximated by the oil:gas partition coefficient (the original experiment was done with olive oil)

Discussion Points

  • Are inhalational agents “context sensitive”?
  • Why is CSHT unhelpful for volatiles, but useful for propofol, remifentanil etc?
  • What context sensitive decrement time would be useful for volatiles?


  1. Miller 8th edition, Chapter 26
  2. Bailey J. Context sensitive half times and other decrement times of inhaled anesthetics. Anesth Analg 1997, 85: 681-686.

BT_GS 1.9 Describe factors influencing the distribution of drugs (for example …. pH, pKa) ….

T/F all drugs are either weak acids or weak bases

T/F the degree to which a given weak acid or weak base will ionise (dissociate) at a given pH is determined by its pKa — this is -log(10) of the acid dissociation constant (Ka)

T/F weak bases all have pKa higher than 7

T/F opioids are weak bases, therefore at pH 7.4

  • fentanyl has pKa 8.4 so the ionised to unionised ratio will be 10:1
  • alfentanil has pKa 6.4 so the ionised to unionised ratio will be 1:10

T/F in order to get a weak base to dissolve in water in an ampoule, the pH needs to be made acidic by adding hydrochloric acid (three pH units below pKa will give ionised to unionised ratio of 1000:1)

T/F thiopentone is a weak acid — in an acidotic patient the unionised fraction will be increased, thereby increasing the potency of a given dose

Some Simple Maths

You can use the 2 last equations below to work out the answers to some of the above questions. Read through the derivation steps to ensure you understand what the last 2 equations actually mean.


Rang & Dale 7th edition, Chapter 8

BT_GS 1.12 Effect Site Modelling

BT_GS 1.12

If you read PS51 on medication safety, you will notice that it recommends the use of “Smart pumps”. Pharmacokinetic models are considered a fundamental part of modern anaesthetic practice, and you should understand their characteristics well.

The following question is important: 

This graph shows the curves calculated for individual patients in a Midazolam pharmacokinetics study. You will note that one of the curves looks strange. I suspect there was a transcription error with one of the constants. Apart from this patient though, this is neither a best, nor a worst case graph.

• T/F The predictive accuracy of a pharmacokinetic model is ±10%

The following concept is fundamental. You should be able to explain both what happens and why.

You can see here the effect of haemorrhagic shock on effect site concentrations after a bolus dose of propofol.  These graphs are based on pharmacokinetics from a pig study. You will note that pigs have different pharmacokinetics to humans. All the pigs were bled to a specific blood pressure, so the effect in a shocked patient might be less or more than this example.

Scroll down and look at the differences in the graphical representations of the control and shocked models. See if you can figure out why the curves are different.

• T/F Paradoxically the dose of propofol should be increased in haemorrhagic shock

The next concept is something you should understand.

Which of Schnider & Marsh has the larger central compartment? Now look at the difference between effect site and plasma concentrations with the Schnider and Marsh models.

• T/F The ratio of maximum plasma concentration to maximum effect site concentration is greater in models with a larger central volume of distribution

This is important because if you are using a model targeting plasma concentration, the initial bolus will be proportional to the size of the central compartment. Another issue to be aware of is that the central compartment size in the Schnider model is fixed. This means that all patients, regardless of size, would be given the same initial bolus if you used plasma concentration mode with the Schnider model.

This concept is interesting but less important.

Look at the difference between effect site and plasma concentrations with a model for vecuronium and for dexmedetomidine. Both have roughly the same central volume of distribution. Look at their times to peak effect. Try shortening the TTPE for dexmedetomidine and see what happens to the maximum plasma concentration.

• T/F The ratio of maximum plasma concentration to maximum effect site concentration is greater in drugs with a long time to peak effect

The last question tests your understanding of how these models work.

Take a look again at the time course of plasma concentration and effect site concentrations in the Schnider model for propofol. Take a look at some of the other drugs and see if it is the same.

• T/F Plasma concentration is equal to effect site concentration at ln(2) x the time to peak effect

I have put the following in small print because it is not a pass/fail concept.
When we look at the relationship between plasma concentration and effect, we notice that the effect lags the concentration in both onset and offset. We can correct for this by introducing a mathematical lag. The ‘effect’ site concentration is therefore a lag corrected plasma concentration rather than a real entity. If we could actually measure the concentration at the effect site, what would it be? The experiment is actually possible with microdialysis catheters. In this study, they found the actual tissue concentrations of cefazolin were about an order of magnitude less than the plasma concentrations.

It is not possible to simulate this using a standard mammillary model, as the effect site concentration in these models will always eventually approximate that of the central compartment.. How can you explain this discrepancy?

Context Sensitive Half Time

BT_GS 1.12 Explain and describe the clinical application of concepts related to intravenous and infusion kinetics including: Concept of context sensitive half time

Context sensitive half time (CSHT) is a very important concept, and one which you should be prepared to discuss at length. This post discusses where these numbers come from.

All the textbooks show the same graph for CSHT of anaesthetic drugs. The graph comes from a paper by Hughes et al in 1992. You might be surprised to know that this graph is not of actual patient data, but the results of a simulation. The links in this post will allow you to reproduce these results, and also to see what happens if you use different pharmacokinetic models, or extend the time period.

This is the CSHT graph for midazolam using the data from Hughes’ paper. Click on the button labelled t75%. This will show you the context sensitive time to fall to 1/4 of the original concentration.  t87.5% shows the time to fall to 1/8 of the original concentration and t93.5% the time to fall to 1/16. How do these times compare to the half time? How do they compare to the terminal elimination half life? (You can see it here).

• T/F The time to fall to 1/4 of the original concentration is equal to twice the CSHT

Look at the graph for fentanyl. Now change the timescale of the graph from 8 hours to 16 or 24 hours and see what happens.

• T/F The CSHT for fentanyl continues to increase indefinitely with length of infusion.

Have a think and see if you can answer this question:

• T/F Drugs with a very variable CSHT are inappropriate to administer as a bolus.

The minimum standard for a pass would be to know and be able to discuss the CSHT graphs which are in the textbooks. The following is for more advanced understanding.

Here is Hughes’ graph for propofol. Look at the CSHT at 4-8hours.  Now look at the same graphs using the Schnider and Marsh models. What do you notice? Which do you think correlates better with what we see clinically?

• T/F The CSHT for propofol after a 8 hour infusion is around 50 minutes

This is the graph for thiopentone. Have a look and see what happens with the prediction for 24 or 48 hour infusion. This certainly does not correspond with what we know clinically about thiopentone. See if you can work out the answer to the following question:

• T/F In Hughes’ graph, the CSHT for thiopentone increases steeply because it changes to zero order kinetics

The following is more of a question for a viva, as it does not have a simple answer:

Remifentanil is a better drug than oxycodone because it has a much shorter CSHT

BT_GS 1.30 Compartmental Modelling

BT_GS 1.30 Describe and compare the pharmacokinetics of intravenous induction and sedative agents, the factors which affect recovery from intravenous anaesthesia and the clinical implications of these differences

Pharmacokinetics of intravenous drugs is an important topic in the Primary. The following questions are based on standard compartmental modelling. You should have a solid understanding of the basic models, even if real life is more complicated.

The links are to an interactive page for compartmental models. If you can’t see the whole graph on the page, try making the page narrower.

Effect Site Concentrations, (Basic, Important)

These two questions are basic and important.

Here is a graph of “Effect site concentrations” after a bolus dose of propofol. Click on the 2x dose button to see what happens if you give a bigger dose.

• T/F Doubling the dose of propofol raises the effect site concentration by a factor of ln(2)

• T/F Doubling the dose of propofol speeds the time to peak effect

Compartment Modelling (Basic, Important)

A three compartment model can be expressed by the equation

Ct = Ae-αt + Be-βt + Ce-ɣt

Look at the graphs here. Display them as both linear and semi-log graphs. How can the constants α, β & ɣ be calculated?

• T/F The constants α, β & ɣ are best calculated using a linear graph.

Look at the plasma concentration time graphs for two different models of Ketamine. Now look at the graphical display of the two models, Perrson and Olofson. You have probably not seen a 2D graphical comparison of models before, but the following concept is also basic and important.

• T/F The compartments in compartmental models refer to physical body compartments.

ke0 (Hard, Important)

ke0 is quite a difficult concept.  t1/2ke0 is confusing because it has no simple relationship to any time that we use clinically. Do not conflate this with Time to Peak Effect!

Look at the different ke0 values for the Schnider and Marsh model for propofol.

• T/F The value for t1/2ke0 is a constant for any given drug

So why is it called t1/2ke0 if it doesn’t tell you the time to peak effect? It is the half life of the movement of drug to the hypothetical effect site. This movement is also affected by the plasma concentration, which in turn is affected by the other half lives. The calculation of time to peak effect involves a complicated function of all of them. TTPE is obviously a fixed property of the drug, so this means the ke0 is affected by the other half lives. Each ke0 is therefore specific to the model it has been calculated for. You cannot compare them between models.


BT_GS 1.10 Describe the mechanisms of drug clearance and how physiological and pathological disturbance may effect these

T/F Liver cirrhosis have little effect on the clearance of drugs with a high extraction ratio.

T/F In the obstetric patient, the placenta contributes to clearance of certain drugs.

T/F The infusion rate to maintain a given drug concentration = clearance x volume of distribution.

T/F Drug clearance is the product of cardiac output and hepatic extraction ratio.

T/F Cytochrome P450 enzymes are membrane-bound proteins found in fragments of endoplasmic reticulum.

Therapeutic Drug Monitoring

BT_GS 1.13, Explain clinical drug monitoring with regard to peak and trough concentrations, minimum therapeutic concentration and toxicity


Quite a difficult topic to find good references for in the referenced texts. See here for some suggestions for reading.

T/F Therapeutic drug monitoring is useful for drugs being given for prophylaxis rather than treatment

T/F For therapeutic drug monitoring to be useful there should be a relationship between plasma concentration and effect

T/F It is the total plasma concentration of a drug which correlates best with side effects and toxicity

T/F Therapeutic drug monitoring is useful when it is difficult to distinguish between lack of therapeutic effect and toxicity

T/F Therapeutic drug monitoring is useful when the predominant action of a drug is through an active metabolite.