Full of sound and fury, signifying nothing

It is quite possible to spend the entire ten minutes writing an answer to a SAQ and score zero. To avoid this, your SAQ (and viva) should consist of verifiable facts which are specific to the question asked.

Let us consider how we could achieve a zero score in the hypothetical question: “Write short notes on novifentanil”

We could start with a definition:

  • Drug: a medicine or other substance which has a physiological effect when ingested or otherwise introduced into the body.

Now we can segue into some value judgements:

  • Novifentanil is a useful drug.
  • I recommend it
  • It is cheap and readily available. (An answer often given in vivas: So are THC, crack and ice)
  • Novifentanil is potent

We will now conclude with some statements which are worthless because they could be applied to (almost) any drug.

  • The intravenous preparation is a sterile clear colourless solution
  • When given intravenously it has 100% bioavailability
  • When given orally it is absorbed in the gut and undergoes first pass metabolism
  • It is metabolised in the liver
  • Metabolites are excreted in the kidneys
  • It acts on receptors
  • Side effects include nausea, vomiting rash and rarely anaphylaxis
  • Contraindications include allergic reaction

We could alternatively score high marks by covering the same issues:

  • potent: Compare the potency with other drugs in this class. Does the potency have any other implications, such as altering time to peak effect?
  • useful: What is it particularly useful for compared with other drugs in the same class?
  • clear colourless solution: Why is it clear?
    • Is it intrinsically water soluble, is it an ionisable acid or base, is it dissolved in an additive such as propylene glycol?
    • What problems might the additives cause?
    • Is it safe to give it neuraxially?
    • Will it exhibit ion-trapping?
  • first pass metabolism: Does this imply anything about whether or not the drug is effective orally?
  • metabolism: It is very easy to get lost in the metabolic pathways. Some of the important things to figure out are:
    • are there any active metabolites
    • is there any genetic / drug interaction consequences of the pathways which are used? What will this imply in patients with liver disease? If it is metabolised by an enzyme such as CYP3A4 where you probably won’t see many interactions this is also important. (There are some exceptions to this such as St John’s Wort.)
  • excreted renally: Does it have active metabolites? Is it excreted unchanged renally? Is it reabsorbed or secreted? If none of these, how is it affected by renal failure?
  • receptors: state which ones and what effects these cause
  • Side effects:
    • are they different or the same as other drugs in the same class?
    • are there any specific side effects which you need to mention?
    • are there any class specific side effects that this drug does not exhibit?
  • I recommend it: are there any specific indications for which it is recommended?

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.

 

2018.1 SAQ 10 Myocardial oxygen balance

BT_PO 1.46

Describe the determinants of left ventricular myocardial oxygen supply and demand.

No prizes for guessing why this question is considered important!

The books spend a lot of time taking about heavy exercise, but you should realise that your cardiac output is quite variable in everyday life.

Under normal conditions it cannot be overstated that myocardial oxygen supply is auto-regulated. If you are unsure of the effect of a physiological or pharmacological challenge to myocardial oxygen supply, ask yourself, “Is the heart doing more or less work”?

The subject is covered in all the major books. The first 4 questions come from Power & Kam. Their subject material is basic and important.

T/F Oxygen consumption in the heart can rise nearly tenfold in heavy exercise.

T/F The increased oxygen demand on the heart during exercise can be met by increasing oxygen extraction.

T/F α receptors in the coronary vasculature cause coronary vasoconstriction during exercise.

T/F Most coronary blood flow occurs during systole

This question is more difficult. The answer may be found in Guyton & Hall.

T/F Adenosine antagonists block the coronary vasodilation caused by exercise

2018.1 SAQ 3 Mechanisms of anaesthesia

BT_GS 1.49

Outline the theories, both current and discredited, as to how volatile anaesthetic agents cause loss of consciousness.

This is an issue which is currently in the media. It also serves as a cautionary tale about how mathematics can be misused to prove what you wish to see. A log-log plot will often make variables appear to be linearly related, particularly if points which are not on the line are discarded.

Some questions inspired by common misconceptions in the SAQ:

T/F Mammals have cell walls, in which volatile anaesthetic agents dissolve

T/F The mechanism of anaesthesia is a combination of cerebral oedema, hypoxia and hypercarbia

And some more serious ones:

T/F volatile agents cause immobility by acting on the GABA receptor

T/F volatile agents cause effects at the 5HT3 receptor

T/F the effect of volatile agents on lipid bilayers can be mimicked by a change in temperature of 1°C

T/F volatile agents do not exhibit isomerism

T/F xenon and nitrous oxide induce unconsciousness by actions on the GABA receptor

Dantrolene

BT_RT 1.19

T/F dantrolene is prepared in a lipid emulsion

T/F dantrolene should be given as a slow intravenous infusion

T/F dantrolene should be given in conjunction with verapamil in resistant malignant hyperthermia

T/F high doses of dantrolene can cause complete paralysis

T/F plasma concentrations after a bolus dose of dantrolene remain in the therapeutic range for approximately 5 hours

DDAVP

BT_PO 1.91

The structure of DDAVP (Desmopressin) is shown below. Candidates who can reproduce this structure in the exam should have spent their time studying something more useful.

Desmopressin.svg

 

T/F Whilst usually used in Von Willebrand’s Disease, desmopressin is effective at reducing perioperative bleeding in most cases of massive blood loss

T/F After intravenous bolus peak levels of factor VIII and vWF occur between 3 and 6 hours

T/F The effect of demopressin on platelet function lasts for about twenty four hours

T/F Desmopressin reduces the risk of thrombosis in patients with type 2B Von Willibrand’s Disease

T/F Rapid administration of desmopressin intravenously may cause hypotension.

Dexmedetomidine

BT_GS 1.31

Fun fact: Direct instraspinal injection of dexmedetomidine apparently produces a dose-dependent elevation of pain thresholds in the Northern leopard frog.

Strangely this question is rarely asked in the primary vivas.

lithobates_pipiens

Photo by Brian Gratwicke.

T/F Dexmedetomidine has a potent amnestic effect

T/F Dexmedetomidine may reduce volatile agent requirements by up to 90%

T/F Rapid administration of dexmedetomidine may cause tachycardia

T/F Dexmedetomidine causes dose dependent myocardial depression

T/F Dexmedetomidine reduces tidal volume and increases respiratory rate

Therapeutic Drug Monitoring

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

bloodtest

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.