Marian J Vermeulen1, Jack V Tu, Michael J Schull. 1. Institute for Clinical Evaluative Sciences, Department of Health Policy, Management and Evaluation, University of Toronto, Ontario, Canada.
Abstract
OBJECTIVE: To derive and validate an International Classification of Diseases-10 (ICD-10) version of the Ontario Acute Myocardial Infarction (AMI) mortality prediction rules, used to adjust for case-mix differences in studies of AMI patients using administrative data. STUDY DESIGN AND SETTING: We linked the records of all Ontario patients admitted with AMI (2002-2004) with mortality data. The original ICD-9 codes were mapped to ICD-10-CA (Canada) codes using both a translation produced by coding experts and a manual search of codes; the final codes were determined by consensus. Comorbidity prevalence and mortality rates were calculated. Multivariable logistic regression models were used to predict 30-day and 1-year mortality and the C-statistic was used to evaluate the discrimination of the models. RESULTS: We identified 37,271 AMI patients. The most common comorbidities were heart failure and dysrhythmias; 30-day and 1-year mortality rates were 12.3% and 21.8%, respectively; and mortality rates were highest among patients with shock, cancer, and acute renal failure. The C-statistics were 0.77 and 0.80, compared with 0.78 and 0.79 in the ICD-9 version, for 30-day and 1-year mortality, respectively. CONCLUSION: An ICD-10 version of the AMI mortality prediction rules predicted 30-day and 1-year mortality as well as the original ICD-9 version.
OBJECTIVE: To derive and validate an International Classification of Diseases-10 (ICD-10) version of the Ontario Acute Myocardial Infarction (AMI) mortality prediction rules, used to adjust for case-mix differences in studies of AMI patients using administrative data. STUDY DESIGN AND SETTING: We linked the records of all Ontario patients admitted with AMI (2002-2004) with mortality data. The original ICD-9 codes were mapped to ICD-10-CA (Canada) codes using both a translation produced by coding experts and a manual search of codes; the final codes were determined by consensus. Comorbidity prevalence and mortality rates were calculated. Multivariable logistic regression models were used to predict 30-day and 1-year mortality and the C-statistic was used to evaluate the discrimination of the models. RESULTS: We identified 37,271 AMI patients. The most common comorbidities were heart failure and dysrhythmias; 30-day and 1-year mortality rates were 12.3% and 21.8%, respectively; and mortality rates were highest among patients with shock, cancer, and acute renal failure. The C-statistics were 0.77 and 0.80, compared with 0.78 and 0.79 in the ICD-9 version, for 30-day and 1-year mortality, respectively. CONCLUSION: An ICD-10 version of the AMI mortality prediction rules predicted 30-day and 1-year mortality as well as the original ICD-9 version.
Authors: Geoffrey H Tison; Alanna M Chamberlain; Mark J Pletcher; Shannon M Dunlay; Susan A Weston; Jill M Killian; Jeffrey E Olgin; Véronique L Roger Journal: Int J Med Inform Date: 2018-09-19 Impact factor: 4.046
Authors: Deborah A Randall; Louisa R Jorm; Sanja Lujic; Aiden J O'Loughlin; Timothy R Churches; Mary M Haines; Sandra J Eades; Alastair H Leyland Journal: BMC Public Health Date: 2012-04-10 Impact factor: 3.295
Authors: Husam Abdel-Qadir; Paaladinesh Thavendiranathan; Kinwah Fung; Eitan Amir; Peter C Austin; Geoffrey S Anderson; Douglas S Lee Journal: JAMA Netw Open Date: 2019-09-04
Authors: Ole Ahlehoff; Jesper Lindhardsen; Gunnar H Gislason; Jonas B Olesen; Mette Charlot; Lone Skov; Christian Torp-Pedersen; Peter R Hansen Journal: BMC Cardiovasc Disord Date: 2012-09-24 Impact factor: 2.298
Authors: Ditte-Marie Bretler; Peter Riis Hansen; Jesper Lindhardsen; Ole Ahlehoff; Charlotte Andersson; Thomas Bo Jensen; Jakob Raunsø; Christian Torp-Pedersen; Gunnar Hilmar Gislason Journal: PLoS One Date: 2012-12-17 Impact factor: 3.240