Variable diagnostic accuracy in reading ECGs in a nurse-led primary PCI pathway
Aleong, G., Bond, Raymond, Canning, Adam, Finlay, Dewar, Guldenring, Daniel and Peace, Aaron (2017) Variable diagnostic accuracy in reading ECGs in a nurse-led primary PCI pathway. In: International Society for Computerised Electrocardiology, St. Simons Island. Elsevier. Vol 50 (6) 1 pp. [Conference contribution]
URL: http://www.jecgonline.com/article/S0022-0736(17)30303-5/fulltext
DOI: 10.1016/j.jelectrocard.2017.08.058
The electrocardiogram (ECG) remains as the crucial tool to diagnose acute ST-elevation myocardial infarction (STEMI). Activation of the cardiac catheterization team to perform primary percutaneous coronary intervention (PPCI) largely depends on the interpretation of the ECG at the time of first medical contact with the patient. In Northern Ireland, if the referrer decides that the ECG shows a STEMI they would then transmit the ECG to a designated coronary care nurse who then decides whether to activate the PPCI pathway or to transfer the patient to the nearest emergency department (ED).ObjectiveWe sought to ascertain the impact, ECG based decisions has on the PPCI pathway and specifically on clinical outcomes.MethodsECG and clinical data were retrospectively reviewed for consecutive patients referred to the PPCI pathway over an 8-month period as part of a continuous audit. Patients were either accepted or turned down for PPCI by the nurse. All ECGs were retrospectively adjudicated upon with a final diagnosis made by a senior coronary care nurse and interventional cardiologist. ECG interpretation was evaluated in the referrer group, the machine, and the nurse activator.ResultsA total of 366 patients were referred to the PPCI pathway over the 8-month period. 118 (32%) were accepted for PPCI. All accepted patients met diagnostic ECG criteria with 100/118 (85%) having a final diagnosis of STEMI. 244 referrals (68%) were turned down for PPCI, predominantly on the basis of lack of diagnostic criteria. All turndowns were considered appropriate. Paramedics were the main referrers 218/361 (60%) with the remainder from ED. The ECG machine suggested an ischemic diagnosis in 95/99 (Sensitivity = 96%) of patients with STEMI and 178/244 (1-Specificity = 73%, Specificity = 27%) of the turndown cases. Of those referred for PPCI, 66% of the ED referrals were turned down. Of those referred by paramedics for PPCI 68% were turned down. The STEMI group were significantly younger that the turndown group (63 ± 12 vs. 68 ± 16, p = 0.0021) with higher mortality in the turndown group at 12 months 17.4% vs. 10.2% No STEMIs were missed.ConclusionsECG interpretation by referrers in this nurse-led primary PCI pathway is sub-optimal. The high rate of false positives in ECG machine diagnoses in the turndown group could be an influencing factor in the human-decision making. There is a need to find ways to improve ECG interpretation particularly in a time critical PPCI pathway.
Conference contribution (Poster)
ECG, medical informatics, cardiology, smartphones, mobile technology, heart attacks, STEMI
Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Faculty of Computing & Engineering > School of Engineering
Engineering Research Institute
Engineering Research Institute > Nanotechnology & Integrated BioEngineering Centre (NIBEC)
Computer Science Research Institute > Smart Environments
Computer Science Research Institute
Dr Raymond Bond