Literature DB >> 22937488

Choices in the use of ICD-9 codes to identify stroke risk factors can affect the apparent population-level risk factor prevalence and distribution of CHADS2 scores.

James A Rothendler, Adam J Rose, Joel I Reisman, Dan R Berlowitz, Lewis E Kazis.   

Abstract

While developed for managing individuals with atrial fibrillation, risk stratification schemes for stroke, such as CHADS2, may be useful in population-based studies, including those assessing process of care. We investigated how certain decisions in identifying diagnoses from administrative data affect the apparent prevalence of CHADS2-associated diagnoses and distribution of scores. Two sets of ICD-9 codes (more restrictive/ more inclusive) were defined for each CHADS2-associated diagnosis. For stroke/transient ischemic attack (TIA), the more restrictive set was applied to only inpatient data. We varied the number of years (1-3) in searching for relevant codes, and, except for stroke/TIA, the number of instances (1 vs. 2) that diagnoses were required to appear. The impact of choices on apparent disease prevalence varied by type of choice and condition, but was often substantial. Choices resulting in substantial changes in prevalence also tended to be associated with more substantial effects on the distribution of CHADS2 scores.

Entities:  

Keywords:  CHADS2; ICD-9-CM codes; Stroke; atrial fibrillation; risk stratification

Year:  2012        PMID: 22937488      PMCID: PMC3427978     

Source DB:  PubMed          Journal:  Am J Cardiovasc Dis        ISSN: 2160-200X


  26 in total

1.  Co-morbidity data in outcomes research: are clinical data derived from administrative databases a reliable alternative to chart review?

Authors:  K H Humphries; J M Rankin; R G Carere; C E Buller; F M Kiely; J J Spinelli
Journal:  J Clin Epidemiol       Date:  2000-04       Impact factor: 6.437

2.  Inaccuracy of the International Classification of Diseases (ICD-9-CM) in identifying the diagnosis of ischemic cerebrovascular disease.

Authors:  C Benesch; D M Witter; A L Wilder; P W Duncan; G P Samsa; D B Matchar
Journal:  Neurology       Date:  1997-09       Impact factor: 9.910

3.  Warfarin use among ambulatory patients with nonvalvular atrial fibrillation: the anticoagulation and risk factors in atrial fibrillation (ATRIA) study.

Authors:  A S Go; E M Hylek; L H Borowsky; K A Phillips; J V Selby; D E Singer
Journal:  Ann Intern Med       Date:  1999-12-21       Impact factor: 25.391

4.  Validation of clinical classification schemes for predicting stroke: results from the National Registry of Atrial Fibrillation.

Authors:  B F Gage; A D Waterman; W Shannon; M Boechler; M W Rich; M J Radford
Journal:  JAMA       Date:  2001-06-13       Impact factor: 56.272

5.  Accuracy of ICD-9-CM codes for identifying cardiovascular and stroke risk factors.

Authors:  Elena Birman-Deych; Amy D Waterman; Yan Yan; David S Nilasena; Martha J Radford; Brian F Gage
Journal:  Med Care       Date:  2005-05       Impact factor: 2.983

6.  Stroke: who's counting what?

Authors:  D M Reker; B B Hamilton; P W Duncan; S C Yeh; A Rosen
Journal:  J Rehabil Res Dev       Date:  2001 Mar-Apr

7.  Identifying hypertension-related comorbidities from administrative data: what's the optimal approach?

Authors:  Ann M Borzecki; Ashley T Wong; Elaine C Hickey; Arlene S Ash; Dan R Berlowitz
Journal:  Am J Med Qual       Date:  2004 Sep-Oct       Impact factor: 1.852

8.  Who has diabetes? Best estimates of diabetes prevalence in the Department of Veterans Affairs based on computerized patient data.

Authors:  Donald R Miller; Monika M Safford; Leonard M Pogach
Journal:  Diabetes Care       Date:  2004-05       Impact factor: 19.112

9.  Selecting patients with atrial fibrillation for anticoagulation: stroke risk stratification in patients taking aspirin.

Authors:  Brian F Gage; Carl van Walraven; Lesly Pearce; Robert G Hart; Peter J Koudstaal; B S P Boode; Palle Petersen
Journal:  Circulation       Date:  2004-10-11       Impact factor: 29.690

10.  Regional comparisons of inpatient and outpatient patterns of cerebrovascular disease diagnosis in the province of Alberta.

Authors:  Nikolaos Yiannakoulias; Lawrence W Svenson; Michael D Hill; Donald P Schopflocher; Robert C James; Andreas T Wielgosz; Thomas W Noseworthy
Journal:  Chronic Dis Can       Date:  2003
View more
  13 in total

1.  Sex-Specific Comparative Effectiveness of Oral Anticoagulants in Elderly Patients With Newly Diagnosed Atrial Fibrillation.

Authors:  Ghanshyam Palamaner Subash Shantha; Prashant D Bhave; Saket Girotra; Denice Hodgson-Zingman; Alexander Mazur; Michael Giudici; Elizabeth Chrischilles; Mary S Vaughan Sarrazin
Journal:  Circ Cardiovasc Qual Outcomes       Date:  2017-04

2.  Effect of race on outcomes (stroke and death) in patients >65 years with atrial fibrillation.

Authors:  Rajesh Kabra; Peter Cram; Saket Girotra; Mary Vaughan Sarrazin
Journal:  Am J Cardiol       Date:  2015-04-16       Impact factor: 2.778

3.  Underuse of Oral Anticoagulants and Inappropriate Prescription of Antiplatelet Therapy in Older Inpatients with Atrial Fibrillation.

Authors:  Lorette Averlant; Grégoire Ficheur; Laurie Ferret; Stéphane Boulé; François Puisieux; Michel Luyckx; Julien Soula; Alexandre Georges; Régis Beuscart; Emmanuel Chazard; Jean-Baptiste Beuscart
Journal:  Drugs Aging       Date:  2017-09       Impact factor: 3.923

4.  Impact of Heart Failure Type on Thromboembolic and Bleeding Risk in Patients With Atrial Fibrillation on Oral Anticoagulation.

Authors:  Amgad Mentias; Alexandros Briasoulis; Ghanshyam Shantha; Paulino Alvarez; Mary Vaughan-Sarrazin
Journal:  Am J Cardiol       Date:  2019-02-28       Impact factor: 2.778

5.  Refining Stroke Prediction in Atrial Fibrillation Patients by Addition of African-American Ethnicity to CHA2DS2-VASc Score.

Authors:  Rajesh Kabra; Saket Girotra; Mary Vaughan Sarrazin
Journal:  J Am Coll Cardiol       Date:  2016-08-02       Impact factor: 24.094

6.  Trends in antithrombotic therapy for atrial fibrillation: Data from the Veterans Health Administration Health System.

Authors:  Joshua Buck; Peter Kaboli; Brian F Gage; Peter Cram; Mary S Vaughan Sarrazin
Journal:  Am Heart J       Date:  2016-06-21       Impact factor: 4.749

7.  Role of diabetes and insulin use in the risk of stroke and acute myocardial infarction in patients with atrial fibrillation: A Medicare analysis.

Authors:  Amgad Mentias; Ghanshyam Shantha; Oluwaseun Adeola; Geoffrey D Barnes; Bharat Narasimhan; Konstantinos C Siontis; Deborah A Levine; Rajan Sah; Michael C Giudici; Mary Vaughan Sarrazin
Journal:  Am Heart J       Date:  2019-05-10       Impact factor: 4.749

8.  Risk of cardiovascular events among patients with HIV treated with atazanavir-containing regimens: a retrospective cohort study.

Authors:  Lisa Rosenblatt; Amanda M Farr; Ella T Nkhoma; James K Nelson; Corey Ritchings; Stephen S Johnston
Journal:  BMC Infect Dis       Date:  2016-09-19       Impact factor: 3.090

9.  Increased Hemoglobin A1c Time in Range Reduces Adverse Health Outcomes in Older Adults With Diabetes.

Authors:  Julia C Prentice; David C Mohr; Libin Zhang; Donglin Li; Aaron Legler; Richard E Nelson; Paul R Conlin
Journal:  Diabetes Care       Date:  2021-06-14       Impact factor: 17.152

10.  Risk of Cardiovascular Events Among Patients Initiating Efavirenz-Containing Versus Efavirenz-Free Antiretroviral Regimens.

Authors:  Lisa Rosenblatt; Amanda M Farr; Stephen S Johnston; Ella T Nkhoma
Journal:  Open Forum Infect Dis       Date:  2016-03-30       Impact factor: 3.835

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.