This post is about a paper we published today in Heart – the result of more than 9 years of work – phew! Here’s a link to the paper (open access), which reports how we derived and externally validated the Manchester Acute Coronary Syndromes (MACS) decision rule. The MACS rule may help us to exclude ACS using a single blood test in the ED, while also ‘ruling in’ some patients and risk stratifying those who can’t yet have the diagnosis ‘ruled out’.
A long, long time ago I took a really important decision in my life. 2 days before Christmas in 2004 I had an interview for a job in the lovely city of Lancaster. The job was my way into higher specialist training in Emergency Medicine and I was the only person being interviewed. This was my ticket to becoming a consultant in Emergency Medicine within 4 years – what an opportunity! Just before that interview, I met with Kevin Mackway-Jones for some career advice. He looked at my CV and asked why I wasn’t doing a PhD instead. My first thought was something along the lines of: you’re crazy, why would I spend 3 years doing research in central Manchester when I could work in leafy Lancaster and be a consultant in 4 years?
But after a couple of sleepless nights and a couple of hours spent thinking during a great drive to Lancaster and back in the snow, I took his advice and cancelled my interview. This was, after all, my chance to really make a difference to Emergency Medicine. And so I worked in central Manchester and did a PhD deriving clinical decision rules for patients with suspected acute coronary syndromes. (I’d recommend this route to anyone working in EM – academic EM is an awesome career)
That was a long time ago and, after investing a lot of blood, sweat and tears and learning an awful lot, the Manchester Acute Coronary Syndromes decision rule – or MACS rule for short – is finally published in Heart today. Many things have changed since we started out on this project – notably the biomarkers – so it was lucky that we made plans to freeze plasma and serum samples, which were later tested for newer markers like high sensitivity troponin T.
[DDET So what was the aim here?]
We (Kevin, Simon, Garry McDowell and Chris Wibberley and I) set out with an idea to derive a clinical decision rule that would allow ACS to be immediately excluded in the ED based on information that was immediately available at the time of arrival, including the results of a single blood test. We wanted to combine clinical features with biomarkers, since neither of these are ever really used alone. What’s more, we wanted to not only identify patients who could immediately go home from the ED, but to risk stratify the others so that we can make more judicious use of inpatient resources and ‘rule in’ the highest risk patients so that they can benefit from early treatment.
Ultimately, we aimed to derive and then (in a separate study) externally validate the decision rule.
[DDET What did we actually do?]
In the derivation study we recruited 804 patients with suspected cardiac chest pain (of whom 698 could be included in this final analysis), recorded their clinical details using a proforma, and drew blood for biomarker testing. As a reference standard for AMI, all patients had a troponin test at least 12 hours after symptom onset. We also followed them up after 30 days for our primary outcome – MACE (AMI, death or revascularisation including new coronary stenoses on angiography). We repeated the same method in the validation study, at a different centre (Stockport).
We derived the decision rule by logistic regression, including all the variables that (by themselves) were both reliable (kappa score >0.6) and made MACE either significantly more or less likely. One novel aspect of the decision rule is that biomarker levels are treated as continuous variables – i.e. there’s no cut-off. The higher the level, the greater the risk. As cut-offs are essentially arbitrary, isn’t that how we should be using them, after all?!
[DDET What did we find?]
The final decision rule contains 8 things, as shown below.
You basically just use a computer calculator, enter values for each of these, and the computer will calculate the probability of MACE. Based on that, it will put patients into one of 4 risk groups:
Very low risk – Go straight home
Low risk – Go to ED observation ward
Moderate risk – Go to Acute Medical Ward
High risk – Go to high dependency/specialist area, e.g. CCU
Here’s how it worked…
So, the rate of MACE in the ‘very low risk’ group is pretty low and over a quarter of patients could go straight home just after a single blood test at the time of arrival. Meanwhile, just under 10% of patients were ‘high risk’ and would go to CCU – making the best use of those resources.
[DDET What is H-FABP?]
H-FABP, or heart-type fatty acid binding protein, is an early marker of myocardial ischaemia/necrosis. It rises as early as half an hour after the onset of myocardial necrosis so is theoretically ideal for our purposes in the ED. This link will take you to a manufacturer’s website – so you’ll expect that it won’t be impartial – but it actually gives you a good summary of what H-FABP is and its potential value.
[DDET How does the MACS rule make the best use of hs-troponin?]
Every week we see more and more papers published telling us of the potential benefits of using hs-troponin. The assays have some real advantages – they give more reliable results (especially at lower levels) and they can detect smaller concentrations of troponin – including levels in >50% of healthy individuals. With a hs-troponin assay we can also detect 90% of AMIs using a single test at the time of arrival, which is much better than standard assays.
One of the limitations for us in the ED is that a single hs-troponin level can’t ‘rule out’ ACS and, unless the level is very high, it can’t ‘rule in’ ACS either. The MACS rule handles hs-troponin as a continuous variable – so it takes account of all of the richness of the diagnostic information it brings, rather than dichotomising the result at what’s essentially an arbitrary cut-off (the 99th percentile). As such, the lower your hs-troponin level the less risk you are at. This makes perfect sense – and it seems to allow hs-troponin to really flourish as a biomarker, even before you undertake serial sampling. The MACS rule takes account of other information too – such as the ECG, the patient’s symptoms and other biomarkers (we found H-FABP to be the most useful additional marker of those we looked at) – to really get the best out of the biomarkers.
Of course, as I’m the first author, this is a biased opinion – but you can see from the results that it appears to work well!
[DDET What does this mean?]
Potentially you could use the decision rule now. It’s been derived and externally validated. But one or two things will stop us. First, we need to know how it actually works in practice. Will docs actually be happy to send patients home? Will patients want to go home? Will it perform as well when doctors have to use the rule in practice to guide decisions? These questions can only be answered in an RCT, and that’s what we’ve already started – as you can see at this link and from Shweta Gidwani’s tweet below…
— Shweta Gidwani (@Global_EM) November 7, 2012
Second, this report tells us how the MACS rule works with a semi-automated ELISA assay for H-FABP. You might be able to get results in a couple of hours but it would be a lot of hard work – and a real push (I ran some of the tests myself!). The test might work slightly differently when we use a fully automated assay that can get us a result fast enough to influence care in the ED. We need to prove that the rule will work with such an assay – and we’ll have to watch this space for those results.
[DDET What other questions remain unanswered?]
Will the rule work with other troponin assays? We need to know – because not all assays are the same. How essential is H-FABP to the rule? How does it compare to the HEART score? And what happens when we add in serial sampling over 1 to 2 hours? All these questions now need to be answered.
Thanks for reading! Please get in touch if you want to know more about the MACS rule or if you’re interested in getting involved with our future work. We’re on the look out for potential sites for the next phase of our research!