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Crowding of our hospitals and emergency departments (EDs) is not a new issue, but the COVID-19 pandemic has now taken it to another level. The recent pressures highlight the importance of sparing vital inpatient resources for those who really need them. They help us to appreciate the dangers of allowing those resources to be consumed by patients undergoing diagnostic evaluation for a condition that they probably do not have, especially when they would not otherwise require any inpatient care.
Fortunately, we now have numerous evidence-based pathways that can help us. Following a single blood test in the ED, some patients could be immediately discharged, either using low troponin cut-offs1 2 or a decision aid.3 4 For those who have not been discharged after a single blood test, the second blood test can now be drawn much earlier (1 to 3 hours after the first sample) than was previously possible.5 6 This eliminates the need for prolonged inpatient waits for late troponin sampling. It may also obviate the need for routine cardiac imaging or stress testing in health systems where that has previously taken place.
While it is now clear that the second troponin sample can be taken 1 to 3 hours after the first one, deciding exactly which pathway to use in your local hospital can be challenging. There are so many options. Should you use the 1 hour algorithm, the High-Sensitivity Troponin in the Evaluation of patients with suspected Acute Coronary Syndrome (High-STEACS) algorithm or should you incorporate clinical features by adopting the HEART pathway or Emergency Department Assessment of Chest Pain (EDACS) decision aid? In this issue, Stopyra et al 7 used real-world data to compare the accuracy of the HEART pathway and the EDACS decision aid for predicting major adverse cardiac events (MACEs) within 30 days (REF). Patients underwent cardiac troponin sampling on arrival and 3 hours later with one of two contemporary troponin assays. The HEART pathway had superior sensitivity (98.4% vs 94.2%) but would allow fewer patients to be discharged following the 3-hour sample (38.4% vs 58.1%).
This leaves us with an important question. Is it preferable to have a more accurate rule-out test to avoid unanticipated MACE or to have greater efficiency so that fewer patients are admitted to hospital unnecessarily? At the moment, we have little guidance on how to strike this balance. We know that clinicians tend to be risk averse and demand very high negative predictive values.8 But is it appropriate to strive to achieve this without considering the risks of hospital admission, false-positive (or negative) imaging results, unnecessary angiography, unnecessary treatment as well as the inconvenience and anxiety caused to a large number of patients and their families? Should we consider cost-effectiveness (price per quality adjusted life year) when determining which pathway to use?
At the moment there is no universal approach. Local decisions must therefore be made by carefully balancing all the available evidence and asking a number of important questions. Has the pathway been validated with the same cardiac troponin assay that will be used locally? Has it been validated in a similar patient group to your own? What is the nature of the events that were missed by the different pathways? (Coronary revascularisation, for example, is a much less serious outcome than an unexpected cardiac death.)
It is also important to consider the patient’s perspective. There is evidence that patients who are allowed to engage in shared decision-making with their clinician are more likely to choose to leave the hospital without further investigations than those who receive standard, clinician-guided care.9 All these factors must be considered when determining which patient pathway is most appropriate for local implementation. Whatever you decide, setting up a system to collect data and compare your chosen approach with alternatives (just as Stopyra et al 7 have so commendably done) will enable you to ensure that, whatever you decide, you are always using the best available data to guide the care of your local patients.
Contributors RB is the sole author of this work.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests Research grants to my institution: Abbott Point of Care Advisory boards: Abbott Point of Care; Roche; Siemens Healthineers; LumiraDx; Creavo.
Patient and public involvement Patients and/or the public were not involved in the design, conduct, reporting or dissemination plans of this research.
Patient consent for publication Not required.
Provenance and peer review Commissioned; internally peer reviewed.
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