An evidence-based score to detect prevalent peripheral artery disease (PAD).
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.
Lillehei Clinical Research Unit, Cardiovascular Division, University of Minnesota Medical School, Minneapolis, MN 55455, USA. duval002@umn.edu
Sue
S
Duval
Joseph M
JM
Massaro
Michael R
MR
Jaff
William E
WE
Boden
Mark J
MJ
Alberts
Robert M
RM
Califf
Kim A
KA
Eagle
Ralph B
RB
D'Agostino
Alison
A
Pedley
Gregg C
GC
Fonarow
Joanne M
JM
Murabito
P Gabriel
PG
Steg
Deepak L
DL
Bhatt
Alan T
AT
Hirsch
D000368:Aged; D000369:Aged, 80 and over; D055109:Ankle Brachial Index; D016009:Chi-Square Distribution; D015897:Comorbidity; D016002:Discriminant Analysis; D019317:Evidence-Based Medicine; D005260:Female; D006801:Humans; D007383:Intermittent Claudication / Q000175:diagnosis / Q000453:epidemiology; D016015:Logistic Models; D008297:Male; D008403:Mass Screening / Q000379:methods*; D008875:Middle Aged; D015999:Multivariate Analysis; D049451:Nomograms; D058729:Peripheral Arterial Disease / Q000175:diagnosis* / Q000453:epidemiology*; D011237:Predictive Value of Tests; D015995:Prevalence; D011336:Probability; D011379:Prognosis; D011446:Prospective Studies; D012042:Registries; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D014481:United States / Q000453:epidemiology