OBJECTIVE: To investigate the predictive value of acute coronary syndrome (ACS) diagnoses, including unstable angina pectoris, myocardial infarction, and cardiac arrest, in the Danish National Patient Registry. STUDY DESIGN AND SETTING: We identified all first-time ACS diagnoses in the Danish National Patient Registry among participants in the Danish cohort study "Diet, Cancer and Health" through the end of 2003. We retrieved and reviewed medical records based on current European Society of Cardiology criteria for ACS. RESULTS: We reviewed hospital medical records of 1,577 out of 1,654 patients (95.3%) who had been hospitalized with a first-time ACS diagnosis. The overall positive predictive value for ACS was 65.5% (95% confidence interval [CI]=63.1-67.9%). Stratification by sub-diagnosis and hospital department produced significantly higher positive predictive values for myocardial infarction diagnoses (81.9%; 95% CI=79.5-84.2%) and among patients who received an ACS diagnosis in a ward (80.1%; 95% CI=77.7-82.3%). CONCLUSION: The ACS diagnoses contained in hospital discharge registries should be used with caution. If validation is not possible, restricting analyses to patients with myocardial infarction and/or patients discharged from wards might be a useful alternative.
OBJECTIVE: To investigate the predictive value of acute coronary syndrome (ACS) diagnoses, including unstable angina pectoris, myocardial infarction, and cardiac arrest, in the Danish National Patient Registry. STUDY DESIGN AND SETTING: We identified all first-time ACS diagnoses in the Danish National Patient Registry among participants in the Danish cohort study "Diet, Cancer and Health" through the end of 2003. We retrieved and reviewed medical records based on current European Society of Cardiology criteria for ACS. RESULTS: We reviewed hospital medical records of 1,577 out of 1,654 patients (95.3%) who had been hospitalized with a first-time ACS diagnosis. The overall positive predictive value for ACS was 65.5% (95% confidence interval [CI]=63.1-67.9%). Stratification by sub-diagnosis and hospital department produced significantly higher positive predictive values for myocardial infarction diagnoses (81.9%; 95% CI=79.5-84.2%) and among patients who received an ACS diagnosis in a ward (80.1%; 95% CI=77.7-82.3%). CONCLUSION: The ACS diagnoses contained in hospital discharge registries should be used with caution. If validation is not possible, restricting analyses to patients with myocardial infarction and/or patients discharged from wards might be a useful alternative.
Authors: Ulla Vogel; Majken K Jensen; Karen Margrete Due; Eric B Rimm; Håkan Wallin; Michael R S Nielsen; Anne-Pernille T Pedersen; Anne Tjønneland; Kim Overvad Journal: Atherosclerosis Date: 2011-06-17 Impact factor: 5.162
Authors: Majken K Jensen; Sarah A Aroner; Kenneth J Mukamal; Jeremy D Furtado; Wendy S Post; Michael Y Tsai; Anne Tjønneland; Joseph F Polak; Eric B Rimm; Kim Overvad; Robyn L McClelland; Frank M Sacks Journal: Circulation Date: 2017-11-21 Impact factor: 29.690
Authors: Manja Koch; Jeremy D Furtado; Gordon Z Jiang; Brianna E Gray; Tianxi Cai; Frank Sacks; Anne Tjønneland; Kim Overvad; Majken K Jensen Journal: J Lipid Res Date: 2017-04-01 Impact factor: 5.922
Authors: Allyson M Morton; Manja Koch; Carlos O Mendivil; Jeremy D Furtado; Anne Tjønneland; Kim Overvad; Liyun Wang; Majken K Jensen; Frank M Sacks Journal: JCI Insight Date: 2018-02-22
Authors: Ulla Vogel; Stine Segel; Claus Dethlefsen; Anne Tjønneland; Anne Thoustrup Saber; Håkan Wallin; Majken K Jensen; Erik B Schmidt; Paal Skytt Andersen; Kim Overvad Journal: BMC Med Genet Date: 2009-06-07 Impact factor: 2.103