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Gro Egholm,1,2,* Morten Madsen,2,* Troels Thim,1 Morten Schmidt,2,3 Evald Høj Christiansen,1 Hans Erik Bøtker,1 Michael Maeng1 1Department of Cardiology, 2Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, 3Department of Internal Medicine, Regional Hospital of Randers, Denmark *These authors contributed equally to this work Background: Registry-based monitoring of the safety and efficacy of interventions in patients with ischemic heart disease requires validated algorithms.Objective: We aimed to evaluate algorithms to identify acute myocardial infarction (AMI) in the Danish National Patient Registry following percutaneous coronary intervention (PCI).Methods: Patients enrolled in clinical drug-eluting stent studies at the Department of Cardiology, Aarhus University Hospital, Denmark, from January 2006 to August 2012 were included. These patients were evaluated for ischemic events, including AMI, during follow-up using an end point committee adjudication of AMI as reference standard.Results: Of 5,719 included patients, 285 patients suffered AMI within a mean follow-up time of 3 years after stent implantation. An AMI discharge diagnosis (primary or secondary) from any acute or elective admission had a sensitivity of 95%, a specificity of 93%, and a positive predictive value of 42%. Restriction to acute admissions decreased the sensitivity to 94% but increased the specificity to 98% and the positive predictive value to 73%. Further restriction to include only AMI as primary diagnosis from acute admissions decreased the sensitivity further to 82%, but increased the specificity to 99% and the positive predictive value to 81%. Restriction to patients admitted to hospitals with a coronary angiography catheterization laboratory increased the positive predictive value to 87%.Conclusion: Algorithms utilizing additional information from the Danish National Patient Registry yield different sensitivities, specificities, and predictive values in registry-based detection of AMI following PCI. We were able to identify AMI following PCI with moderate-to-high validity. However, the choice of algorithm will depend on the specific study purpose. Keywords: Danish National Patient Registry, registry, percutaneous coronary intervention, validity, sensitivity, specificity

Leif Thuesen,1 Lisette Okkels Jensen,2 Hans Henrik Tilsted,3 Michael Mæng,1 Christian Terkelsen,1 Per Thayssen,2 Jan Ravkilde,3 Evald Høj Christiansen,1 Hans Erik Bøtker,1 Morten Madsen,4 Jens F Lassen1 1Department of Cardiology, Aarhus University Hospital, Skejby, Denmark; 2Department of Cardiology, Odense University Hospital, Odense, Denmark; 3Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark; 4Department of Clinical Epidemiology, Aarhus University Hospital, Skejby, Denmark Aim: To describe a new research tool, designed to reflect routine clinical practice and relying on population-based health care databases to detect clinical events in randomized clinical trials. Background: Randomized clinical trials often focus on short-term efficacy and safety in a controlled environment. Trial follow-up may be linked with study-related investigations and differ from routine clinical practice. Because treatment and control in randomized trials differ from daily practice, trial results may have reduced general applicability and may be of limited value in clinical decision-making. Further, it is economically very costly to conduct randomized clinical trials. Methods and results: Population-based health care databases collect data continuously and prospectively, and make it possible to monitor lifelong outcomes of cardiac interventions in large numbers of patients. This strengthens external validity by eliminating the effects of study-related monitoring or diagnostic tests. Further, follow-up data can be obtained at low expense. Importantly, data sources encompassing a complete population are likely to reflect clinical practice. Because population-based health care databases collect data for quality-control and administrative purposes unrelated to scientific investigations, certain biases, such as nonresponse bias, recall bias, and bias from losses to follow-up, can be avoided. Conclusion: Event detection using population-based health care databases is a new research tool in interventional cardiology that may allow large, low-cost, randomized clinical trials to reflect daily clinical practice, covering a broad range of patients and end points with complete lifelong follow-up. Keywords: clinical study, national registries, event detection, PCI, coronary stents