Missing things: Addisons

Recently missed an Addisonian crisis.  Here’s a brief summary of the case.

61 y o female attended the ED after seeing her GP with vaginal bleeding.  GP sent the patient to the ED for an inappropriate official reason (vaginal bleeding in a post menopausal lady unless torrential should be managed as a two week wait), but the lady looked unwell, and I think that was why the GP fabricated a reason.

This lady had a PMH of psychotic illness, rectal prolapse, and that was pretty much it.  She was seen with a family member who looked after her.  The history was vague.  She wouldn’t talk much, she said she had felt unwell for a few days, tired, and lethargic.  She had noticed the bleeding intermittently for the last few months.  She had a grey waxy sheen to her skin, and her hair was matted and unkempt.  Was this because of her mental health problem?

Systemic examination was unremarkable apart from a large rectal prolapse which I reduced, it was probably also the source of the blood.  Her results were phoned through:

Na 129, K6.9 Urea 17.2 Creat 152.  She had an elevated neutrophilia.  ECG showed sinus tachy with what were on reflection tented t-waves.  Her VBG showed a normal pH, slightly reduced HCO3- 15, and a BE of -5.

She was dry.  She had a high K+.  I started her on insulin/dex.  Started a septic screen and began rehydrating her with normal saline.  I did not giver her steroids but the medical SpR did about 1 hour after I saw her.

So why didn’t I think of Addisons? (apart from me being a bit thick).

The patient arrived in the ED by ambulance.  The history was confused.  The reason for attendance was really ‘unwell ?cause’ that the GP had recognised but then put more emphasis on the symptom of vaginal bleeding.  I think this led me down a strange path.  Possibly slowing my decision making with an anchoring bias.  I’d found a pathology with the rectal prolapse, and solved it (premature closure).  Did I think that this could explain the GI symptoms, AKI and dehydration?  Possibly, given the mental health problems and poor communication, this lady was likely to present late enough to cause these things if she’d avoided nutrition and fluid because toileting was painful.

Did I also fall prey to confirmation bias?  I think so.  I had a theory, I’d found something to confirm this.  I think I stopped looking for or considering differentials, despite the fact that I was thinking renal failure in someone with a normal venous pH, and only slightly disturbed bicarb.  .  I think there was also an element of fundamental attribution error (stereotyping), I probably placed too much emphasis on this woman’s serious mental health problem, as I tried to fit my theory together.

I may have rejected a new diagnosis of Addisons as a form of availability bias – I’ve never diagnosed primary Addisons, which means it’s not an explanation I often examine or reach for.  This is also called Zebra Retreat.  My normal cue for thinking about Hypoadrenalism is if people are on long term steroids and this lady wasn’t.

So how do we mitigate against cognitive errors?

Well there’s a good article on that here, along with a list of other cognitive errors you can make here.  The biggest step is being aware that they can happen, and what they are.

One way I normally work is I try to write down my differential, weighing the relative merits of each one as best I can.  However the time when I do this is when I’m less busy, and I know that when I am juggling a few Resus patients simultaneously I neglect my documentation, but those are probably exactly the times it needs to be done!  Especially as writing my working out is so important to my ‘cognitive process’.

When I miss something I also like to read up on the thing I missed, as well as trying to understand why I missed it.  Sometimes I write a reflection, sometimes (more often) I chat to my wife about it (she’s an ICU doc).  I just wish more time was allowed for this kind of thing at work.

Some notes on Addisons.

Incidence 0.8 per 100 000 of population.  More common in women than men.

The commonest cause of glucocorticoid deficiency is Iatrogenic, this technically isn’t Addisons.  Consider replacement if patients have been on 7.5mg pred/day (30mg Hydrocortisone/day) for longer than one month.  The mechanism here as I’m sure you know is suppression of the adrenal axis by negative feedback, causing adrenal atrophy.

Classically the causes are usually infection (TB, HIV), trauma, anything causing adrenal haemorrhage, and malignancy (mets like the adrenal glands as they are highly vascular).

Clinical Features:

Vague, frustrating and insidious.  Tiredness is the commonest symptom.  Skin hyperpigmentation (secondary to excess ACTH) looks quite subtle to me.  It’s more pronounced in areas of increased friction like palms, knuckles and scars.  GI symptoms can be severe enough to mimic an acute abdomen.

ED presentations are mostly crises, so you get hypotension, alongside the hyperkalaemia and hyponatraemia.  You can also get hypoglycemia.  On reflection I wonder how many potential mild cases we send back to GPs.

In summary

Mistakes and errors are common, especially with rare conditions and vague presentations. The ED environment sometimes feels like it’s designed to cause and not mitigate cognitive error, with multiple distractions and heavy time pressure.  We all need to develop our own strategies for limiting our own cognitive errors as we develop as clinicians.


Don’t miss an Addisonian crisis. [Low Na, High K –> Give steroids]



Suspicious Histories

Ask any medical student (when they are sober) the clinical features of an Acute Coronary Syndrome they’ll look at you funny for a bit, then talk of  severe, left sided chest pain radiating through to the arm, they might add in diaphoresis, or pulmonary oedema.  If you’ve got a real nugget that might carry on talking about risk factors, relief from GTN and ‘pain like previous MI’ making a cardiac cause more likely.

You’d probably tell them they were right.

I remember hearing the first description of a chest pain history in a big lecture theatre as a first year medical student, and it was pretty much that.

We’ve always been taught that Histories Are Important, we are taught these by rote, by repetition and by  exposure to lots of real world cases.  They are the narrative that gives us the pathology our patients experience. So it’s implicit that the clinical features of those histories are equally important, and give us a sense of the probability of the disease in question.  I doubt I’m alone in labouring to commit ‘red flag symptoms’ to memory for exams, or general day to day work.

Now in my last post I got in a bit of a tiz about the HEART score, and about how the definition of a suspicious history was a little vague.  Now the history component of the HEART score is just worth 0,1, or 2 points out of 10.  So if histories were as important as my old professor said why does the component only make up a maximum of 20% of the score?

Thats because the classical chest pain history is not a very good predictor of ACS.

Let that sink in.  You have been taught that histories are important, they’re the key to finding the pathology.  Sometimes when the diagnosis is essentially a clinical one (eg appendicitis) that still holds true.  However when you have a good quality gold-standard test (eg a Troponin) things become different.  You can test the history, and the chest pain history is not very good at all.

In 2001 Prof Steve Goodacre published a study looking at the clinical features of people with low risk chest pain (normal ECG, no initial trop rise), seeing if any particular features had a predictive effect.  Previous research up to this point suggested left arm pain, diaphoresis, a 3rd heart sound and hypotension predicted acute myocardial infarction, but these studies were done prior to the advent of Troponin.

He conducted a big single centre prospective trial of patients over 25 with chest pain, no known CAD, and a normal initial workup.    He followed his patients up over 6 months looking for AMI and MACE.  He had a ACS rate of 9.1% in his cohort of 893 patients.

If I were to ask you ‘where do most people who have an NSTEMI complain there pain is coming from?’ You’d probably point somewhere over the left side of your chest.

Site Odds Ratio CI P
Both arms 6.0 2.8-12.8 >0.0001
Shoulder 3.4 1.5-7.8 0.004
Right arm 2.5 0.5-11.9 0.24
Throat 2.0 0.4-9.4 0.37
Left arm 1.7 0.9-3.1 0.084
Neck 0.8 0.3-2.5 0.74

Taken from table 4 – Univariate Analysis of Predictors of ACS (Goodacre 2001)

Would you suggest pain in both arms?   What about pain in the right arm being more suggestive of AMI than pain in the left?  That’s what Prof Goodacre found, though his confidence intervals are wide, and some of his findings were not statistically significant.

Now if we look at some his multivariate analysis results we can see that he only really found 3 good predictors.  Pain in both arms, exertional pain and a tender chest wall (this was a good negative predictor).  How many people have you admitted because ‘they had pain at rest’?

Pain in both arms 4.07 4.9 1.3-19.4 0.02
Exertional pain 2.35 3.3 1.3-8.4 0.014
Tender chest wall (as negative predictor) 0.3 0.2 0.05-0.97 0.045

He concludes

“We also found no evidence that the site of pain, the presence of nausea, vomiting, or diaphoresis, and the duration of the pain were at all useful in predicting whether the pain was likely to be cardiac or not”

Despite him having a pretty big sample of low risk, non cardiac chest pain he probably still didn’t have a big enough sample to look at what he wanted to look at.  This dataset was taken from another study primarily looking at the feasibility of a rapid chest pain assessment service.  I guess thats why theres no sample size calculation.

Lets look at my next study.  I love this study, it’s come out of manchester.  Prof Body included everyone over 25 who attended with suspected cardiac chest pain, treating clinicians completed a standard form with tick boxes for clinical features.  All patients had a 12 hour troponin and follow up at 48 hours, 30 days and 6 months.  His primary outcome measure was AMI and secondary outcome was MACE at 6 months.  So we’ve got a slightly different risk profile to the Goodacre study.

They analysed the results from 796 patients, and got 100% follow up.  I feel they had a slightly higher AMI rate of 18.6% (n=148) for initial presentation.  At 6 months they had a MACE rate of 22.9% (n=179).

The Odds ratios for AMI for individual clinical features are below.

bodygraph A few things to point out.  Sweating and abdominal pain seemed to be good predictors of AMI, as did reported N+V (which was not predictive in Prof Goodacres cohort).  Pain location that was in both arms predicted AMI more than pain in the left (and pain in the right was slightly better than left).    My favourite one though is that if the pain was described as ‘like their previous MI’ patients were less likely to have AMI.

Body didn’t find any excellent predictors of AMI.  His best ones were observed sweating, both arm/shoulder pain, and hypotension.

Predictor Sensitivity Specificity PPV NPV LR+ LR-
Sweating Observed 36.5 (28.7-44.8) 94.3 (92.2 – 96.0) 59.3 (48.5 – 69.5) 86.7 (83.9 – 89.1) 6.39 (4.38 – 9.33) 0.67 (0.28 – ).46)
Reported Vomiting 16.2 (10.7 – 23.2) 94.8 (92.7 – 96.3) 41.4 (28.6 – 55.1) 83.2 (80.3 – 85.8) 3.09 (1.89 – 5.05) 0.88 (0.82 – 0.95)
Pain in both shoulders 13.5 (8.5 – 20.1) 94.8 (92.7 – 96.3) 37.0 (24.3 – 51.3) 82.8 (79.8-85.4) 2.58 (1.53-4.34) 0.91 (0.85-0.96)
Same as previous ischemia 22.3 (15.9-29.9) 69.4 (65.7 – 73.0) 14.3 (10-19.5) 79.7 (76.1 – 82.3) 0.73 (0.53-1.01) 1.12 (1.01-1.24)
Right arm/shoulder pain 18.9 (13.0 – 26.2) 91.8 (89.4 – 93.8) 34.6 (24.4 -46.0) 83.2 (80.3 – 85.9) 2.31 (1.52 – 3.53) 0.88 (0.81 – 0.96)

Taken from Table 3 of Body (2010)  Characteristics of each predictive clinical feature as a diagnostic test for AMI

So in two good quality studies of chest pain characteristics we get right arm pain more predictive of AMI than left arm pain.  We can’t with any degree of accuracy state that someones epigastric burning pain isn’t cardiac in origin, and a classical heavy central pain radiating to the jaw or arm isn’t predictive of AMI or 6 month MACE at all.

Caveats.  You’ve got lots of hypothesis tests going in both of these studies.  Maybe too many, given the sample size and the rarity of the condition we are looking for.  A bigger sample would increase the accuracy certainly.

So should we stop talking to people about their chest pain?  Of course not, however we need to be very careful at excluding ACS based on the chest pain history alone.  Using something like the HEART score is probably more accurate, safer for your patient and safer for your registration.


My department has just started using the HEART score to help risk stratify chest pain patients.  Now chest pain/ACS rule out is a large portion of the ED’s workload, with that workload spilling out over to the acute medics, as we wait for 12 hour troponins.  Now your own department will have it’s own ways of sorting through all this chaff, and of course you should follow your own local protocols.

HEART Score allows us to risk stratify low risk chest pain patients and get them out of our department with a single troponin measurement taken at triage.  Here it is in all it’s glory.



Now the original derivation study is available here.

The first thing that strikes me is the size of the initial study.  The ED it was performed in was a 265 bed community hospital.  The cohort size was small as well (only 122 patients).

The authors basically sat down and came up with a scoring system based on the components of the chest pain assessment that we normally do.  They didn’t derive their score by complex regression analysis they literally thought it up.

Most of it is pretty objective, and therefore repeatable and reliable.  Apart from one bit.  That’s the history.

Heres what the authors wrote about the history.

“For the purpose of this study, patient history was classified by two investigators, based on the narrative in the hospital charts written in the emergency room and not allowing for risk factors, ECGs, laboratory results and later developments. In the absence of specific elements in terms of pattern of the chest pain, onset and duration, relation with exercise, stress or cold, localisation, concomitant symptoms and the reaction to sublingual nitrates, the history was classified as ‘nonspecific’ and granted zero points. If the patient history contained both nonspecific and suspicious elements, the history was classified as ‘moderately suspicious’ and granted one point. If the history contained primarily specific elements, the history was classified highly suspicious and granted two points “

So – if the history had ‘bits’ that made the investigator think it was cardiac then they got 2 points, if they had bits that were ‘a bit cardiac’ and ‘a bit not cardiac’ they got 1 point.  If there was no parts of the history that was suggestive you got 0 points.

Now the problem I have here is that what one of us thinks is ‘definitely cardiac’ someone else might think was a bit soft.  They’ve not broken this down much.

They’ve talked about pattern, onset,  duration, relation with exercise, stress, cold, localisation, concomitant symptoms, and the reaction to sublingual nitrates.  They’ve not given more detail as to exactly what feature of the the pain, onset, duration etc.

They’ve also not checked to see if there is any agreement or disagreement between people using the score (kappa).  So we don’t know what the inter-rater reliability is.

The people who decided how suspect a history were experienced ED clinicians.  So surely they are going to have a slightly different opinion to an F2 whose just started their first rotation.  These two senior ED clinicians worked in the same department, that doesn’t see STEMIs.  So is there experience going to be skewed?  We have no way of knowing.  We also have no way of knowing if they’d agree with my (or your) assessment of chest pain as ‘highly’ or ‘moderately’ suspicious.

AND if there was nothing in the history that was suspicious then why the hell are you doing a cardiac workup?

Lets look at their results.

So the authors recruited 122 patients over a 3 month period, and followed them up for a minimum of about 300 days.  They looked for ‘end points’ which they defined as AMI, PCI, CABG, Death or all together.  They managed 98.3% follow up rate.

24.1% or 29 patients got to one of the end points.  This was how their scores broke down.

HEART SCORE Number Number of reached any Endpoint
0-3 (low risk) 39 1 2.5%
4-6 (med risk) 59 12 20.3%
7-10 (high risk) 22 16 72.7%

The authors conclude that if their TINY study is correct it might be possible to discharge people with a HEART score of 3 or less without further investigation as the risk of MACE is <2.5%.

From ED and AMU perspectives that would be wonderful.  Chest pain rule outs take up a massive proportion of ED and Acute Medical Unit time, so by allowing us to discharge people prior to that 12 hour trop we might save ourselves a lot of work, and our patients a lot of time, and unnecessary tests.

This is a tiny study!  It was retrospective.  It is possible to have a Trop >3x normal and non-specific ECG changes and be classified as low risk.  I do find that worrying, and I’d feel uncomfortable sending those people home, as I’m sure you would.

I’m going to look at the first validation study, then I’m going to run through a few others.  First validation study is available here.

This was a multicentre prospective validation study.

Patients were enrolled aged 21+ if they were having a cardiac workup in one of 10 hospitals in the Netherlands.  They had a proforma filled in, which was entered into a database along with their initial ECG and initial troponin result.  The database calculated GRACE, TIMI and HEART score.  ECGs were blinded and read by two cardiologists using the Minnesota criteria.  Ambiguous ECG’s were arbitrated by a third cardiologist.  The primary endpoint was MACE at 6 weeks (ACS, PCI, CABG, or Death), which was collected by trawling patient records, phoning the GP, or contacting the patient.

They recruited 2440 patients, lost 7 due to incomplete form filling in, and lost 45 to follow up.  This left 2338.  408 patients had MACE at 6 weeks.  155 AMIs, 251 PCIs, 67 CABGs, 44 Medical Mx, and 16 deaths.

Their results are below:

HEART SCORE n(%) of study population Number who reached end point  6/52 mace
0-3 (low risk) 870 (36.4%) 15 1.7%
4-6 (med risk) 1101(46.1%) 183 16.6%
7-10 (high risk) 417(17.5%) 209  50.1%

The authors report

“The average HEART score was 3.96+/−2.0 in the non-MACE group and 6.54+/−1.7 in the MACE group.”

Now the standard deviations do OVERLAP.  So i’m not entirely sure that they can ascribe significance to their finding.  The c-statistic (now this is like area under curve, so the closer to 1 the better) was 0.83, which is damn good really.  They didn’t do a sample size calculation.  So I’m not sure they’ve got enough participants to robustly test this test.

Good things:  they’ve reproduced the results on a larger scale, using a computer to calculate the scores (less chance of fudging).  I’d have loved a look at their standard clerking form however.  As I’m still a bit concerned about the HISTORY segment, as this is enough to move someone from a low to high risk category.

Bad things:  Again theres little information about the HISTORY segment of scoring. If they used a computer then either the form MUST have asked for a gut feeling, or got the database to calculate it based on ticked boxes.  Again no assessment of inter-rater reliability.


Well the HEART score has been derived in a small ED based on a undifferentiated sample of patients presenting with chest pain.  It’s certainly useful, but it does have limitations especially when it comes to history, and if some of the more objective measures change.  I do however like how it allows you to consider a minuscule frustrating trop rise that you know is a false positive and still allow discharge.

As with most scores, they shouldn’t replace the grey squashy stuff between your ears, but maybe they’ll help us all risk stratify a little better.

Next time – So I guess what we should talk about next is features of a chest pain history actually increase the likelihood of ACS?  What makes a ‘suspicious’ history?



Off it! Part 4: Synthetic Cannabinoids

Synthetic Cannabinoids

Mental Model – [  ‘UP ‘ – A bad trip ]

There are over 150 different molecules in circulation under this class.  They are sprayed onto plant matter and smoked in a similar way to cannabis, thats pretty much where the similarities end.  They can also be dissolved and injected in their powdered form, snorted, inhaled, or cooked into food.

Synthetic cannabinoids were first produced to investigate the pharmacological potential of the endogenous cannabinoid receptor. They were first found in recreational products in 2008.   They are all analogues of 9-tertrahydrocannabinol (9-THC) the active ingredient in ‘normal’ cannabis, which is a partial CB1 and CB2 agonist.  Newer agonists have much greater affinities for the THC receptors, (being complete rather than partial agonists).  They also seem to last longer than normal cannabis.  CB1 and CB2 receptors are EVERYWHERE in your CNS, and as each molecule in circulation has a different affinity for different receptors, in different locations the toxidrome can be highly variable.

‘Spice’ is the second most popular drug in the US (after cannabis), and it is estimated that the spice industry is worth something like $5 billion.  Its popularity grew initially because of a perception that it is ‘legal’, ‘safe’ and ‘undetectable’.

Patients who come in intoxicated from a synthetic cannabinoid (K2, spice, Kronic etc) are agitated, confused, and paranoid.  There are no generally agreed signs to look for, some case series talk about dilated pupils, conjunctival injection, and hyper-reflexia, but these probably depend on dose, and type taken.  Patients normally seem  tachycardic and diaphoretic.   They may often be brought in by ambulance following ‘seizure-like’ activity, or by the police for erratic behaviour.

16 Cases of AKI reported in the US associated with synthetic cannabis use.  Convulsions have been reported but not proved to be related to synthetic cannabinoids.


Again, this is supportive.  Use titrated IV benzopdiazepines to calm agitation.  IV fluids for dehydration.  Check a CK and a U and E if they are unwell.   If you can get close an ECG is useful for completeness, though no arrhythmia have been reported (but hypokalaemia HAS).


I witnessed synthetic cannabinoid withdrawal first hand whilst working in ED in New Zealand over the weekend that a nationwide ban came into force.  Patients attend with psychosis, sweating, paranoia and delusions.  Patients were treated with benzodiazepines.


Harris, Carson R., and Ashley Brown. “Synthetic cannabinoid intoxication: a case series and review.” The Journal of emergency medicine 44.2 (2013): 360-366.

Spaderna, Max, Peter H. Addy, and Deepak Cyril D’Souza. “Spicing things up: synthetic cannabinoids.” Psychopharmacology 228.4 (2013): 525-540.

Off it! Part 3: GHB

GammaHydroxybutyric Acidghb

[ – Mental model: – Benzos,  ‘DOWN’]

Legal Status:  Class C

Think of GHB as a possibility in patients who are often male, body building and appear ‘drunk’.  GHB patients get VERY flat, very quickly if they get the dose wrong, and alcohol potentiates this.

Other signs of acute toxicity – LOW RR, GCS, BP and Hypersalivation

They are really hard to wake up (no matter what ‘trick’ you use).

GHB binds to GABA and inhibits the release of action potentials from the synapse.  In high enough concentrations GHB gets converted to GABA.  You may hear that someone has taken GBL (or gamma butyrolactone) that’s the precursor and has a delayed affect, especially when take with alcohol.

It seems to be used in social circles of gym fanatics.  There is a belief that it increases human growth hormone release, and improves muscle repair, AND is a calorie free way of getting the buzz people want from alcohol.  It’s also been used as a date rape drug.



These patients sometimes require airway protection.  They will wake up on ICU the next day, thank no one, and leave.   Deaths occur when patients lose their airway control outside of hospital.


Some people take GHB a lot, if they get their recreational dosing correct can re-dose, and re-dose night after night (or regularly for work outs), when their supply runs out, or changes they can get a rebound effect which is like an alcohol withdrawl, symptoms start 6 hours after the last dose.  It can last much longer (weeks), and is more resistant to benozodiazepines.

The autonomic features are present, but slightly reduced, however the syndrome can last longer (up to two weeks).  Control it with benzodiazepines and baclofen (GABA agonists), and titrate down slowly like with alcohol withdrawl.

Early features – insomnia, tremor, confusion, nausea and vomiting

Late features – tachycardia, hypertension, agitation, seizures and/or myoclonic jerks and hallucinations

Off it! Part 2: Synthetic Cathinones

MCAT/Mephedrone/Bath Salts

[- mental model – amphetamines , ‘UP’]

Legal status: Class B

You will not have spent long in the ED before coming across someone who is off their face on MCAT.  This drug isn’t well described in the literature as it’s only been in the UK since 2008(1).

khatIt is a synthetic derivative of Khat (Catha edulis).  Which is a leafy green plant which in it’s natural form acts as a mild stimulant.  If the leaves are chewed, or put into tea it delivers a feeling somewhere between a big coffee and a small dose of speed.

MCAT comes as a powder, or is sprayed onto dead plant matter.  It can be eaten, smoked, snorted, or injected.  With onset times and length of action fluctuating depending on the method.  Dosage depends on delivery, but most people ‘bomb’ (MCAT wrapped in a rizla)  up to a gram.  They may take more than one bomb a night.

Information on the toxidrome for MCAT is limited because nearly all of the published material is from patients reporting what they think they may have taken.   When someone says they have taken MCAT, they may have taken MCAT, or a derivative (there are over 30 described in recent review articles(2).

synthetic cathinones


The derivatives have different attributes, mostly in their ability to cross the BBB, but their affinity to certain parts of the brain seems to be different too.  Most commercially available preparations that people seem to buy contain a mixture of lots of different molecules.  So when someone says they’ve taken MCAT what they’ve actually taken is a mixture of random cathinone derivatives.

Cathinone derivatives are thought to work by increasing the concentration of dopamine, serotonin, and noradrenaline in the synaptic cleft(1,3).  They do this by upregulating secretion, and blocking MAO (which breaks them down).  It is therefore theoretically possible I suppose that people on SSRIs and TCAs might get more than they bargained for.

Clinical Features

Patients attend the ED with paranoia, anxiety, agitation, aggression, they can hallucinate.   Look for tachydysrhythmias, diaphoresis and tremor.   Patients on MCAT have HUGE pupils.   One of the metabolites is thought to be an ephedrine derivative, and causes vasoconstriction so in theory you could get all of the sequelae associated with vasospasm (ACS, Dissection, ICH).

Rhabdomyolysis has been reported with mephedrone toxicity so a CK is probably worth sending if you think they are bad enough to require bloods.

A malignant hyperthermia like affect has also been reported probably due to it’s serotonergic effect.  I’ve found a handful of confirmed deaths, some due to renal failure, some due to arrhythmia.  However we are very much in case series territory.

Treatment (consensus)

Agitation – Benzodiazepines (3)

Tachycardia – Beta blockade (3)

Renal Impairment – Fluids and dialysis


Not been studied well,  most information comes from research on Khat.  People who have become habituated to it, can get anhedonia, paranoia, and psychosis, but little is known about withdrawl from synthetic cathinones.


  1. Zaitsu, Kei, et al. “Recently abused synthetic cathinones, α-pyrrolidinophenone derivatives: a review of their pharmacology, acute toxicity, and metabolism.”Forensic Toxicology 32.1 (2014): 1-8.
  2. Valente, Maria João, et al. “Khat and synthetic cathinones: a review.” Archives of toxicology 88.1 (2014): 15-45.
  3. Richards, John R., et al. “Treatment of toxicity from amphetamines, related derivatives, and analogues: A systematic clinical review.” Drug and alcohol dependence 150 (2015): 1-13.


Off it! A practical guide to people who are off their face in the ED


What medical school, the foundation programme, and by and large the ACCS curriculum does not prepare you for is how to manage the patient who is mashed (I think it should be a major presentation).  These people who attend at a time when the department is at it’s busiest, and when we are at our weakest. These patients are clinically complex with an added legal dimension in terms of consent,  and mental capacity, which sucks up a lot of ED resource.

drugsIn the coming few weeks I’m going to take you through a basic approach to patients who are intoxicated, and talk about some of the less well known/understood intoxicants.  Much of the teaching and learning on the subject is based around the particular drug the patient has taken.  This makes it difficult to apply at 3 am when ‘Harry’ has backed into the corner of one of your cubicles because he is convinced the Dynamap is going to devour him.  He does not know what he has taken.  He is not sure of his own name.

In the ED there are 2 syndromes that you can slide people into, this will give you an idea of what to expect, what to watch out for, and for how long.  The key is often to be relaxed, have an easy friendly manner, and de-escalate as much as you can.  Use the ‘up/down’ as a mental model, gain control/safety, and then go searching for causes.  Know that time is normally on your side, most patients will finish their trip, and some will even apologise for wasting your time.


  • ‘Just’ drunk / high / tripping is a diagnosis of exclusion.
  • People do stupid things when drunk/high/tripping too, and may have injuries.  Look for them.

Excited delirium (up)

These are the patients that can come in being held down by 2-3 police officers and couple of paramedics.  The history is normally non-existent or vociferously denied by the individual who just wants to go.  You can’t assume they have capacity, which is frustrating for them, and for you.


  • ABCs, de-escalate.
  • Glucose and a 12 lead is a good idea, but may be impractical.  A temperature is also useful.
  • D look at the pupils (BIG: amphetamines, MCAT, anticholinergics, serotinergic, neuroleptics. SMALL: opiates, alcohol)
  • If de-escalation, bargaining, and brute force aren’t working consider something to make the situation a little calmer – midazolam, diazepam, or propofol all work well when used in experienced hands.  This lets you work out if there is anything wrong, and also keeps you and your colleagues safe.

People who are screaming and shouting and fighting off police officers and nurses may have serious pathology (I have found a frontal lobe tumour in a guy fighting off police officers).  Rapidly expanding space occupying lesions can make some people get very fighty.  Don’t assume they are just being annoying.

If someone can’t calm down enough for you to have a conversation with them, they probably don’t have capacity.

Hypoactive delirium (down)

These patients are brought in cold often being ‘found’ by some unlucky member of the general public.  Sometimes the police bring them in, sometimes ‘friends’.

  • ABCs
  • Glucose, 12 lead, temp.
  • GCS – A GCS of <8 only counts if it’s done by an ED sister or ED spr.  We are brutal.  We will teach you our tricks if you ask nicely, or give us cake.
  • Pupils: BIG: amphetamines, MCAT, anticholinergics, serotinergic, neuroleptics. SMALL: opiates, alcohol

Be more concerned with patients with big pupils and hypoactive delirium, this means they’ve taken A LOT, and are closer to the final common pathway of all toxicology which is SEIZURE->COMA->DEATH.


Next week MCAT!

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