| Summary: | Jennifer Davidson,1 Amitava Banerjee,2 Rutendo Muzambi,1 Liam Smeeth,1 Charlotte Warren-Gash1 1Faculty of Epidemiology & Population Health, London School of Hygiene and Tropical Medicine, London, UK; 2Institute of Health Informatics, University College London, London, UKCorrespondence: Jennifer Davidson Email Jennifer.Davidson@lshtm.ac.ukBackground: Electronic health records are widely used in cardiovascular disease research. We appraised the validity of stroke, acute coronary syndrome and heart failure diagnoses in studies conducted using European electronic health records.Methods: Using a prespecified strategy, we systematically searched seven databases from dates of inception to April 2019. Two reviewers independently completed study selection, followed by partial parallel data extraction and risk of bias assessment. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value estimates were narratively synthesized and heterogeneity between sensitivity and PPV estimates were assessed using I2.Results: We identified 81 studies, of which 20 validated heart failure diagnoses, 31 validated acute coronary syndrome diagnoses with 29 specifically recording estimates for myocardial infarction, and 41 validated stroke diagnoses. Few studies reported specificity or negative predictive value estimates. Sensitivity was ≤ 66% in all but one heart failure study, ≥ 80% for 91% of myocardial infarction studies, and ≥ 70% for 73% of stroke studies. PPV was ≥ 80% in 74% of heart failure, 88% of myocardial infarction, and 70% of stroke studies. PPV by stroke subtype was variable, at ≥ 80% for 80% of ischaemic stroke but only 44% of haemorrhagic stroke. There was considerable heterogeneity (I2 > 75%) between sensitivity and PPV estimates for all diagnoses.Conclusion: Overall, European electronic health record stroke, acute coronary syndrome and heart failure diagnoses are accurate for use in research, although validity estimates for heart failure and individual stroke subtypes were lower. Where possible, researchers should validate data before use or carefully interpret the results of previous validation studies for their own study purposes.Keywords: validation, myocardial infarction, heart failure, stroke; routinely collected health data
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