Abstract 12225: Effects of Obesity on Noninvasive Testing and Angiography Results in Patients With Suspected Cardiac Ischemia: Insights From the PROMISE Trial
Background: Evaluation of obese patients with suspected CAD is challenging because obesity is a CV risk factor, but adiposity itself may mimic symptoms of CAD and reduce the accuracy of diagnostic testing. Optimal testing strategies in obese patients are not known. Methods: Patients with stable symptoms suggestive of cardiac ischemia from the PROMISE trial (n=9230) were classified according to BMI. Providers specified a functional test modality prior to stratified randomization to functional (stress testing) or anatomical (CTA) testing. We assessed relationships between BMI, physician’s preference of functional test, test positivity and results of catheter angiography (cath) using logistic regression. Results: Providers were more likely to choose SPECT over other functional tests as BMI increased (OR 1.04 per unit increase in BMI above 27, p<0.001). In patients with BMI ≥ 35 vs. < 35, the rate of positivity with CTA was similar (10% vs. 12%; see Table). The same was true for stress echo and stress ECG (positivity 8-13%, p>0.8 for both). In contrast, SPECT was significantly more likely to be positive in those with BMI ≥ 35 vs. <35 (18% vs. 13%; p=0.001). The likelihood of finding obstructive CAD at cath did not differ with BMI ≥ 35 vs. <35 in patients having CTA (59% vs. 52%, p=0.22), but among SPECT patients, positivity was only 29% with BMI ≥ 35 compared to 52% with BMI < 35 (p=0.005; Table). Conclusions: Increasing levels of obesity were associated with stronger physician preference for SPECT over other noninvasive tests. In patients receiving SPECT, higher levels of obesity were associated with a higher rate of positive results, but a lower cath yield for obstructive CAD. In contrast, in patients receiving CTA, positivity rates and cath yield did not vary by BMI. Obesity appears to significantly influence provider decision-making with regard to noninvasive test choice, probability of abnormal test results and probability of finding obstructive disease at cath.
Discordances between predicted and actual risk in obese patients with suspected cardiac ischaemia
Objectives To test the relationship between increasing severity of obesity, calculated risk and observed outcomes. Methods Patients with symptoms suggestive of coronary artery disease (CAD) (n=10 003) were stratified according to body mass index (BMI). We compared risk factors, pooled risk scores and physicians’ perception of risk. Cox regression tested the association between BMI and (1) presence of obstructive CAD and (2) composite clinical endpoints (death, cardiovascular death, unstable angina hospitalisation and myocardial infarction). Results BMI was ≥30 kg/m2 in 48% of patients and ≥35 in 20%. Increasingly obese patients were younger, female and non-smoking but with higher prevalence of hypertension, diabetes, black race and sedentary lifestyle. Pooled risk estimates of CAD were highest in those with mid-range BMI. In contrast, physicians’ estimation of the likelihood of significant CAD based on clinical impression increased progressively with BMI. For a 10% increase in the Diamond-Forrester probability of CAD, the adjusted OR for obstructive CAD was 1.5 (95% CI 1.4 to 1.5) in patients with BMI <35, but only 1.2 (95% CI 1.1 to 1.3) in those with BMI ≥35 (interaction p<0.001). Framingham Risk Score increased across increasing BMI categories. However, there was a strong and consistent inverse relationship between degree of obesity and all three composite clinical endpoints over a median 25 months of follow-up. Conclusions Despite perceptions of higher risk and higher risk scores, increasingly obese patients had obstructive CAD less frequently than predicted and had fewer adverse clinical outcomes. There is a need for risk assessment tools and guidelines that account for obesity. Trial registration number NCT01174550.
P884Can biomarkers be used to predict cardiopulmonary exercise test performance in patients with chronic heart failure?
Impact of Diabetes Mellitus on the Evaluation of Stable Chest Pain Patients: Insights From the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) Trial
Background The impact of diabetes mellitus on the clinical presentation and noninvasive test ( NIT ) results among stable outpatients presenting with symptoms suggestive of coronary artery disease ( CAD ) has not been well described. Methods and Results The PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) trial enrolled 10 003 patients with known diabetic status, of whom 8966 were tested as randomized and had interpretable NIT results (1908 with diabetes mellitus, 21%). Differences in symptoms and NIT results were evaluated using logistic regression. Patients with diabetes mellitus (versus without) were similar in age (median 61 versus 60 years) and sex (female 54% versus 52%), had a greater burden of cardiovascular comorbidities, and had a similar likelihood of nonchest pain symptoms (29% versus 27%). The Diamond‐Forrester/Coronary Artery Surgery Study score predicted that patients with diabetes mellitus (versus without) had similar likelihood of obstructive CAD (low 1.8% versus 2.7%; intermediate 92.3% versus 92.6%; high 5.9% versus 4.7%). Physicians estimated patients with diabetes mellitus to have a higher likelihood of obstructive CAD (low to very low: 28.3% versus 40.1%; intermediate 63.9% versus 55.9%; high to very high 7.8% versus 4.0%). Patients with diabetes mellitus (versus without) were more likely to have a positive NIT result (15% versus 11%; adjusted odds ratio, 1.23; P =0.01). Conclusions Stable chest pain patients with and without diabetes mellitus have similar presentation and pretest likelihood of obstructive CAD ; however, physicians perceive that patients with diabetes mellitus have a higher pretest likelihood of obstructive CAD , an assessment supported by increased risk of a positive NIT . Further evaluation of diabetes mellitus's influence on CAD assessment is required. Clinical Trial Registration URL : https://www.clinicaltrials.gov . Unique identifier: NCT 01174550.