Literature DB >> 26058719

Effect of the Lookback Period's Length Used to Identify Incident Acute Myocardial Infarction on the Observed Trends on Incidence Rates and Survival: Cardiovascular Disease in Norway Project.

Gerhard Sulo1, Jannicke Igland2, Stein Emil Vollset2, Ottar Nygård2, Grace M Egeland2, Marta Ebbing2, Enxhela Sulo2, Grethe S Tell2.   

Abstract

BACKGROUND: In studies using patient administrative data, the identification of the first (incident) acute myocardial infarction (AMI) in an individual is based on retrospectively excluding previous hospitalizations for the same condition during a fixed time period (lookback period [LP]). Our aim was to investigate whether the length of the LP used to identify the first AMI had an effect on trends in AMI incidence and subsequent survival in a nationwide study. METHODS AND
RESULTS: All AMI events during 1994 to 2009 were retrieved from the Cardiovascular Disease in Norway project. Incident AMIs during 2004 to 2009 were identified using LPs of 10, 8, 7, 5, and 3 years. For each LP, we calculated time trends in incident AMI and subsequent 28-day and 1-year mortality rates. Results obtained from analyses using the LP of 10 years were compared with those obtained using shorter LPs. In men, AMI incidence rates declined by 4.2% during 2004 to 2009 (incidence rate ratio, 0.958; 95% confidence interval, 0.935-0.982). The use of other LPs produced similar results, not significantly different from the LP of 10 years. In women, AMI incidence rates declined by 7.3% (incidence rate ratio, 0.927; 95% confidence interval, 0.901-0.955) when an LP of 10 years was used. The decline was statistically significantly smaller for the LP of 5 years (6.2% versus 7.3%; P=0.02) and 3 years (5.9% versus 7.3%; P=0.03). The choice of LP did not influence trends in 28-day and 1-year mortality rates.
CONCLUSIONS: The length of LP may influence the observed time trends in incident AMIs. This effect is more evident in older women.
© 2015 American Heart Association, Inc.

Entities:  

Keywords:  hospitalization; incidence; lookback period; time trends

Mesh:

Year:  2015        PMID: 26058719     DOI: 10.1161/CIRCOUTCOMES.114.001703

Source DB:  PubMed          Journal:  Circ Cardiovasc Qual Outcomes        ISSN: 1941-7713


  6 in total

1.  Prognostic Impact of In-Hospital and Postdischarge Heart Failure in Patients With Acute Myocardial Infarction: A Nationwide Analysis Using Data From the Cardiovascular Disease in Norway (CVDNOR) Project.

Authors:  Gerhard Sulo; Jannicke Igland; Ottar Nygård; Stein Emil Vollset; Marta Ebbing; Neil Poulter; Grace M Egeland; Charlotte Cerqueira; Torben Jørgensen; Grethe S Tell
Journal:  J Am Heart Assoc       Date:  2017-03-15       Impact factor: 5.501

2.  Impact of age on excess risk of coronary heart disease in patients with familial hypercholesterolaemia.

Authors:  Liv J Mundal; Jannicke Igland; Marit B Veierød; Kirsten Bjørklund Holven; Leiv Ose; Randi Marie Selmer; Torbjorn Wisloff; Ivar S Kristiansen; Grethe S Tell; Trond P Leren; Kjetil Retterstøl
Journal:  Heart       Date:  2018-04-05       Impact factor: 5.994

3.  Impact of the Look-Back Period on Identifying Recurrent Myocardial Infarctions in the Danish National Patient Registry.

Authors:  Søren Korsgaard; Christian Fynbo Christiansen; Morten Schmidt; Henrik Toft Sørensen
Journal:  Clin Epidemiol       Date:  2021-11-03       Impact factor: 4.790

4.  A nationwide registry study on heart failure in Norway from 2008 to 2018: variations in lookback period affect incidence estimates.

Authors:  Kristina Malene Ødegaard; Sandre Svatun Lirhus; Hans Olav Melberg; Jonas Hallén; Sigrun Halvorsen
Journal:  BMC Cardiovasc Disord       Date:  2022-03-05       Impact factor: 2.298

5.  The effects of different lookback periods on the sociodemographic structure of the study population and on the estimation of incidence rates: analyses with German claims data.

Authors:  Jelena Epping; Siegfried Geyer; Juliane Tetzlaff
Journal:  BMC Med Res Methodol       Date:  2020-09-11       Impact factor: 4.615

6.  Validation of an algorithm based on administrative data to detect new onset of atrial fibrillation after cardiac surgery.

Authors:  Jonathan Bourgon Labelle; Paul Farand; Christian Vincelette; Myriam Dumont; Mathilde Le Blanc; Christian M Rochefort
Journal:  BMC Med Res Methodol       Date:  2020-04-05       Impact factor: 4.615

  6 in total

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