An evidence-based score to detect prevalent peripheral artery disease (PAD)

Sue Duval, Joseph M. Massaro, Michael R. Jaff, William E. Boden, Mark J. Alberts, Robert M. Califf, Kim A. Eagle, Ralph B. D'Agostino, Alison Pedley, Gregg C. Fonarow, Joanne M. Murabito, P. Gabriel Steg, Deepak L. Bhatt, Alan T Hirsch

Research output: Contribution to journalReview articlepeer-review

11 Scopus citations

Abstract

Detection of peripheral artery disease (PAD) typically entails collection of medical history, physical examination, and noninvasive imaging, but whether a risk factor-based model has clinical utility in population screening is unclear. Our objective was to derive and validate a new score for estimating PAD probability in individuals or populations. PAD presence was determined by a history of previous or current intermittent claudication associated with an ankle-brachial index (ABI) of < 0.9 or previous lower extremity arterial intervention. Multivariable stepwise logistic regression identified cross-sectional correlates of PAD from demographic, clinical, and laboratory variables. Analyses were derived from 18,049 US REACH (REduction of Atherothrombosis for Continued Health) Registry outpatients with a complete baseline risk factor profile (enrolled from December 2003 to June 2004). Model performance was assessed internally using 10-fold cross validation, and effect estimates were used to generate the score. The model was externally validated using the Framingham Offspring Study. Age, sex, smoking, diabetes mellitus, body mass index, hypertension stage, and history of heart failure, coronary artery disease, and cerebrovascular disease were predictive of PAD prevalence. The model had reasonable discrimination on derivation and internal validation (c-statistic = 0.61 and 0.60, respectively) and external validation (c-statistic = 0.63 [ABI < 0.9] or 0.64 [clinical PAD]). The model-estimated PAD prevalence varied more than threefold from lowest to highest decile (range, 4.5-16.7) and corresponded closely with actual PAD prevalence in each population. In conclusion, this new tool uses clinical variables to estimate PAD prevalence. While predictive power may be limited, it may improve PAD detection in vulnerable, at-risk populations.

Original languageEnglish (US)
Pages (from-to)342-351
Number of pages10
JournalVascular Medicine (United Kingdom)
Volume17
Issue number5
DOIs
StatePublished - Oct 2012

Bibliographical note

Funding Information:
SD had a consultancy relationship with Abbott Vascular and Summit Doppler. JM (Dr Massaro) and AP had support from sanofi-aventis for the submitted work. MJ had a consultancy relationship with Abbott Vascular, Arsenal Medical, AtheroMed, Baxter Healthcare, Boston Scientific, Cordis Endovascular, LC Sciences, Medtronic, Micell Technologies, Nexeon MedSystems, and Takeda Pharmaceuticals. MJ has held stock/stock options in Access Closure, Hotspur Technologies, ICON Interventional, Setagon, Inc., Square One, TMI Group, and Vascular Therapies LLC. MJ has been a board member of VIVA Physicians. WB had a consultancy relationship with Gilead Scientific. WB has received grants/grants pending from Abbott Laboratories. WB has received payment for lectures including service on speakers’ bureaus from Abbott Laboratories, Gilead Scientific, and sanofi-aventis. WB has received payment for development of educational presentations from Gilead Scientific and sanofi-aventis. WB has had travel/accommodations/meeting expenses unrelated to activities listed with Abbott Laboratories, Gilead Scientific, and sanofi-aventis. RC had support from sanofi-aventis for the submitted work. RC had a consultancy relationship and travel/accommodations/meeting expenses unrelated to activities listed with sanofi-aventis. KE has received grant/research support from Biosite, Bristol-Myers Squibb, Cardiac Sciences, Blue Cross Blue Shield of Michigan, Hewlett Foundation, Mardigian Fund, Pfizer, sanofi-aventis, and the Varbedian Fund. KE had a consultancy relationship with the National Institutes of Health, the National Heart, Lung, and Blood Institute, Pfizer, sanofi-aventis, and the Robert Wood Johnson Foundation. GF had a consultancy relationship with and received payment for lectures including service on speaker’s bureaus with Bristol-Myers Squibb and sanofi-aventis. PGS had support from sanofi-aventis for the submitted work. PGS had a consultancy relationship with Astellas Pharma, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Daiichi Sankyo, Inc./Eli Lilly alliance, GlaxoSmithKline, Medtronic, Merck, Otsuka Pharmaceutical, Roche, sanofi-aventis, Servier, and The Medicines Company. PGS has received grants/grants pending from Servier. PGS has received payment for development of educational presentations including service on speakers’ bureaus from AstraZeneca, Boehringer Ingelheim, Merck, Pfizer, Roche, and Servier. PGS has held stock/stock options with Aterovax. DB had support from sanofi-aventis for the submitted work. DB has received grants/grants pending from AstraZeneca, Bristol-Myers Squibb, Eisai, sanofi-aventis, Amarin, Ethicon, Medtronic, and The Medicines Company. AH had support from Bristol-Myers Squibb and sanofi-aventis for the submitted work. AH had a consultancy relationship with Summit Doppler, ev3, and Talecris. AH has received grants from the National Heart, Lung, and Blood Institute, Cytokinetics, and Abbott Vascular.

Funding Information:
The REACH Registry is endorsed by the World Heart Federation. Financial support is provided by Bristol-Myers Squibb, sanofi-aventis, and the Waksman Foundation (Tokyo, Japan). Editorial support was funded by the Bristol-Myers Squibb/Sanofi Pharmaceutical Partnership. The statistical support provided by Drs D’Agostino Sr, Massaro, and Pedley was also funded by this partnership.

Keywords

  • ankle-brachial index
  • peripheral artery disease
  • prevalence
  • registry
  • risk score

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