title: Prevalence and predictors of nonobstructive coronary artery disease identified with coronary angiography in contemporary clinical practice.
abstract: BACKGROUND
  Guidelines recommend noninvasive tests (NITs) to risk stratify and identify patients with higher likelihood of coronary artery disease (CAD) prior to elective coronary angiography. However, a high percentage of patients are found to have nonobstructive CAD. We aimed to understand the relationship between patient characteristics, NIT findings, and the likelihood of nonobstructive CAD.
  
  
  METHODS
  Patients undergoing elective catheterization without history of CAD were identified from 1,128 hospitals in National Cardiovascular Data Registry's CathPCI Registry between July 2009 and December 2011. Noninvasive tests included stress electrocardiogram, stress echocardiogram, stress radionuclide, stress cardiac magnetic resonance, and computed tomographic angiography. Patient demographics, risk factors, symptoms, and NIT results were correlated with the presence of nonobstructive CAD, defined as all native coronary stenoses <50%.
  
  
  RESULTS
  Of 661,063 patients undergoing elective angiography, 386,003 (58.4%) had nonobstructive CAD. Preprocedure NIT was performed in 64% of patients; 51.9% were reported to be abnormal, but only 9% had high-risk findings. Independent factors associated with nonobstructive CAD were younger age, female sex, atypical chest pain, and a low-risk NIT. Patients with high-risk findings on NIT were more likely to have obstructive CAD (adjusted odds ratio 3.03 [2.86-3.22]). Noninvasive test findings had minimal incremental value beyond clinical factors for predicting obstructive disease (C index = 0.75 for clinical factors vs 0.74 for NIT findings).
  
  
  CONCLUSIONS
  In current practice, about two-thirds of patients undergo NIT prior to elective cardiac catheterization, yet most patients have nonobstructive CAD. The weak correlation between most NIT results and the likelihood of obstructive CAD provides further impetus for improving preangiography assessment of likelihood of disease.
authors.affiliation: Duke Clinical Research Institute, Duke University, Durham, NC. Electronic address: manesh.patel@duke.edu.
authors.forename: Manesh R
authors.initials: MR
authors.lastname: Patel
authors.affiliation: Duke Clinical Research Institute, Duke University, Durham, NC.
authors.forename: David
authors.initials: D
authors.lastname: Dai
authors.affiliation: VA Eastern Colorado Health Care System/University of Colorado School of Medicine, Denver, CO.
authors.forename: Adrian F
authors.initials: AF
authors.lastname: Hernandez
authors.affiliation: VA Eastern Colorado Health Care System/University of Colorado School of Medicine, Denver, CO.
authors.forename: Pamela S
authors.initials: PS
authors.lastname: Douglas
authors.affiliation: VA Eastern Colorado Health Care System/University of Colorado School of Medicine, Denver, CO.
authors.forename: John
authors.initials: J
authors.lastname: Messenger
authors.affiliation: Northshore-LIJ/Lenox Hill Hospital, New York, NY.
authors.forename: Kirk N
authors.initials: KN
authors.lastname: Garratt
authors.affiliation: VA Eastern Colorado Health Care System/University of Colorado School of Medicine, Denver, CO.
authors.forename: Thomas M
authors.initials: TM
authors.lastname: Maddox
authors.affiliation: VA Eastern Colorado Health Care System/University of Colorado School of Medicine, Denver, CO.
authors.forename: Eric D
authors.initials: ED
authors.lastname: Peterson
authors.affiliation: Duke Clinical Research Institute, Duke University, Durham, NC.
authors.forename: Matthew T
authors.initials: MT
authors.lastname: Roe
mesh_terms: D000367:Age Factors; D000368:Aged; D060050:Angina, Stable / Q000453:epidemiology; D058070:Asymptomatic Diseases / Q000453:epidemiology; D006328:Cardiac Catheterization / Q000706:statistics & numerical data*; D017023:Coronary Angiography / Q000706:statistics & numerical data*; D003324:Coronary Artery Disease / Q000175:diagnosis / Q000000981:diagnostic imaging / Q000453:epidemiology*; D023921:Coronary Stenosis / Q000175:diagnosis / Q000000981:diagnostic imaging / Q000453:epidemiology*; D025401:Echocardiography, Stress / Q000706:statistics & numerical data; D004562:Electrocardiography / Q000706:statistics & numerical data; D005080:Exercise Test / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D055414:Myocardial Perfusion Imaging / Q000706:statistics & numerical data; D015995:Prevalence; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D012737:Sex Factors; D014057:Tomography, X-Ray Computed / Q000706:statistics & numerical data