Brent A. Williams

Prognostic Value of Stress Myocardial Perfusion Positron Emission Tomography: Results From a Multicenter Observational Registry

OBJECTIVESnThe primary objective of this multicenter registry was to study the prognostic value of positron emission tomography (PET) myocardial perfusion imaging (MPI) and the improved classification of risk in a large cohort of patients with suspected or known coronary artery disease (CAD).nnnBACKGROUNDnLimited prognostic data are available for MPI with PET.nnnMETHODSnA total of 7,061 patients from 4 centers underwent a clinically indicated rest/stress rubidium-82 PET MPI, with a median follow-up of 2.2 years. The primary outcome of this study was cardiac death (n = 169), and the secondary outcome was all-cause death (n = 570). Net reclassification improvement (NRI) and integrated discrimination analyses were performed.nnnRESULTSnRisk-adjusted hazard of cardiac death increased with each 10% myocardium abnormal with mildly, moderately, or severely abnormal stress PET (hazard ratio [HR]: 2.3 [95% CI: 1.4 to 3.8; p = 0.001], HR: 4.2 [95% CI: 2.3 to 7.5; p < 0.001], and HR: 4.9 [95% CI: 2.5 to 9.6; p < 0.0001], respectively [normal MPI: referent]). Addition of percent myocardium ischemic and percent myocardium scarred to clinical information (age, female sex, body mass index, history of hypertension, diabetes, dyslipidemia, smoking, angina, beta-blocker use, prior revascularization, and resting heart rate) improved the model performance (C-statistic 0.805 [95% CI: 0.772 to 0.838] to 0.839 [95% CI: 0.809 to 0.869]) and risk reclassification for cardiac death (NRI 0.116 [95% CI: 0.021 to 0.210]), with smaller improvements in risk assessment for all-cause death.nnnCONCLUSIONSnIn patients with known or suspected CAD, the extent and severity of ischemia and scar on PET MPI provided powerful and incremental risk estimates of cardiac death and all-cause death compared with traditional coronary risk factors.

Influence of Sex on Risk Stratification With Stress Myocardial Perfusion Rb-82 Positron Emission Tomography: Results From the PET (Positron Emission Tomography) Prognosis Multicenter Registry

OBJECTIVESnThe aim of the current analysis was to compare sex differences in the prognostic accuracy of stress myocardial perfusion rubidum-82 (Rb-82) positron emission tomography (PET).nnnBACKGROUNDnThe diagnostic evaluation of women presenting with suspected cardiac symptoms is challenging with reported reduced accuracy, attenuation artifact, and more recent concerns regarding radiation safety. Stress myocardial perfusion Rb-82 PET is a diagnostic alternative with improved image quality and radiation dosimetry. Currently, the prognostic accuracy of stress Rb-82 PET in women has not been established.nnnMETHODSnA total of 6,037 women and men were enrolled in the PET Prognosis Multicenter Registry. Patients were followed for the occurrence of coronary artery disease (CAD) mortality, with a median follow-up of 2.2 years. Cox proportional hazards modeling was used to estimate CAD mortality. The net re-classification improvement index (NRI) was calculated.nnnRESULTSnThe 5-year CAD mortality was 3.7% for women and 6.0% for men (p < 0.0001). Unadjusted CAD mortality ranged from 0.9% to 12.9% for women (p < 0.0001) and from 1.5% to 17.4% for men (p < 0.0001) for 0% to ≥15% abnormal myocardium at stress. In multivariable models, the percentage of abnormal stress myocardium was independently predictive of CAD mortality in women and men. An interaction term of sex by the percentage of abnormal stress myocardium was nonsignificant (p = 0.39). The categorical NRI when Rb-82 PET data was added to a clinical risk model was 0.12 for women and 0.17 for men. Only 2 cardiac deaths were reported in women <55 years of age; accordingly the percentage of abnormal myocardium at stress was of borderline significance (p = 0.063), but it was highly significant for women ≥55 years of age (p < 0.0001), with an increased NRI of 0.21 (95% confidence interval: 0.09 to 0.34), including 17% of CAD deaths and 3.9% of CAD survivors that were correctly re-classified in this older female subset.nnnCONCLUSIONSnStress Rb-82 PET provides significant and clinically meaningful effective risk stratification of women and men, supporting this modality as an alternative to comparative imaging modalities. Rb-82 PET findings were particularly helpful at identifying high-risk, older women.

Prognostic Value of PET Myocardial Perfusion Imaging in Obese Patients

OBJECTIVESnThis study sought to determine and compare the prognostic and incremental value ofxa0positron emission tomography (PET) in normal, overweight, and obese patients.nnnBACKGROUNDnCardiac rubidium 82 (Rb-82) PET is increasingly being used for myocardial perfusion imaging (MPI). A strength of PET is its accurate attenuation correction, thereby potentially improving its diagnostic accuracy in obese patients. The prognostic value of PET in obese patients has not been well studied.nnnMETHODSnA total of 7,061 patients who had undergone Rb-82 PET MPI were entered into a multicenter observational registry. All patients underwent pharmacologic Rb-82 PET and were followed for cardiac death and all-cause mortality. Based on body mass index (BMI), patients were categorized as normal (<25 kg/m(2)), overweight (25 to 29.9 kg/m(2)), or obese (≥30 kg/m(2)). Using a 17-segment model and 5-point scoring system, the percentage of abnormal myocardium was calculated for stress and rest patients categorized as normal (0%), mild (0.1% to 9.9%), moderate (10% to 19.9%), and severe (≥20%).nnnRESULTSnA total of 6,037 patients were followed for cardiac death (median: 2.2 years) and the mean BMI was 30.5 ± 7.4 kg/m(2). A total of 169 cardiac deaths were observed. PET MPI demonstrated independent and incremental prognostic value over BMI. Normal PET MPI conferred an excellent prognosis with very low annual cardiac death rates in normal (0.38%), overweight (0.43%), and obese (0.15%) patients. As well, both moderately and severe obese patients with a normal PET MPI had excellent prognosis (0.20% and 0.10%, respectively). The net reclassification improvement of PET was 0.46 (95% confidence interval [CI]: 0.31 to 0.61), and appeared similar in the moderately and severe obese patients which were 0.44 (95% CI: 0.12 to 0.76) and 0.63 (95% CI: 0.27 to 0.98), respectively.nnnCONCLUSIONSnRb-82 PET has incremental prognostic value in all patients irrespective of BMI. Inxa0the obese population, where other modalities may have reduced diagnostic accuracy, cardiac PETxa0appears toxa0be a promising noninvasive modality with prognostic value.

Prevalence of Heart Failure Signs and Symptoms in a Large Primary Care Population Identified Through the Use of Text and Data Mining of the Electronic Health Record

BACKGROUNDnThe electronic health record (EHR) contains a tremendous amount of data that if appropriately detected can lead to earlier identification of disease states such as heart failure (HF). Using a novel text and data analytic tool we explored the longitudinal EHR of over 50,000 primary care patients to identify the documentation of the signs and symptoms of HF in the years preceding its diagnosis.nnnMETHODS AND RESULTSnRetrospective analysis consisted of 4,644 incident HF cases and 45,981 group-matched control subjects. Documentation of Framingham HF signs and symptoms within encounter notes were carried out with the use of a previously validated natural language processing procedure. A total of 892,805 affirmed criteria were documented over an average observation period of 3.4xa0years. Among eventual HF cases, 85% had ≥1 criterion within 1 year before their HF diagnosis, as did 55% of control subjects. Substantial variability in the prevalence of individual signs and symptoms were found in both case and control subjects.nnnCONCLUSIONSnHF signs and symptoms are frequently documented in a primary care population as identified through automated text and data mining of EHRs. Their frequent identification demonstrates the rich data available within EHRs that will allow for future work on automated criterion identification to help develop predictive models for HF.

Prognostic significance of impaired chronotropic response to pharmacologic stress Rb-82 PET

BackgroundAn impaired chronotropic response to exercise is an accepted risk marker but the relationship between heart rate reserve (HRR) with pharmacologic stress is less well-established. The primary aim of this analysis was to evaluate the prognostic significance of HRR in patients undergoing rest/stress myocardial perfusion positron emission tomography (PET) in estimating coronary artery disease (CAD) mortality.MethodsThis subset analysis from the PET Prognosis Multicenter Registry includes a total of 2,398 patients undergoing rest/stress Rb-PET from three participating sites. The HRR from rest to peak stress was categorized into tertiles of ≤4, 5-14, and ≥15 beats per minute (bpm). At stress, the % abnormal myocardium was categorized as <5xa0%, 5-9.9xa0%, and ≥10xa0%. We estimated CAD mortality using univariable and multivariable Cox proportional hazard models.ResultsCAD mortality was 12.8xa0%, 3.4xa0%, and 0.8xa0%, respectively, for HRR measurements of ≤4, 5-14, and ≥15xa0bpm (Pxa0<xa00.0001). In a multivariable model, the HRR was independently predictive of CAD mortality (Pxa0<xa00.0001) with adjusted hazard ratios elevated 3.5- and 8.4-fold for HRR of 5-14 and ≤4 versus ≥15xa0bpm. In a multivariable model, both the HRR and stress MPI % abnormal myocardium were independently and highly predictive of CAD mortality. Moreover, the net reclassification improvement was 0.18 for the HRR when compared to a model including risk factors, symptoms, rest HR, and PET variables (Pxa0=xa00.0008). For those with ≥10xa0% abnormal myocardium on stress PET, there was a graded relationship between HRR and CAD mortality with adjusted hazards exceeding 50-fold for measurements of 5-14 and ≤4xa0bpm (Pxa0<xa00.0001) compared to stress MPI with <5xa0% abnormal myocardium and a HRR ≥15xa0bpm.ConclusionA diminished HRR to vasodilator stress is a novel but increasingly important predictor of CAD mortality. HRR measurements of ≤4, 5-14, and ≥15xa0bpm were independently predictive of CAD mortality and underscore the importance of optimizing readily available novel markers of risk as highly relevant to identifying high and low risk patient subsets.

Prognostic significance of blood pressure response during vasodilator stress Rb-82 positron emission tomography myocardial perfusion imaging

BackgroundA drop in blood pressure (BP) or blunted BP response is an established high-risk marker during exercise myocardial perfusion imaging (MPI); however, data are sparse regarding the prognostic value of BP response in patients undergoing vasodilator stress rubidium-82 (Rb-82) Positron Emission Tomography (PET) MPI.Methods and ResultsFrom the PET Prognosis Multicenter Registry, a cohort of 3413 patients underwent vasodilator stress Rb-82 PET MPI with dipyridamole or adenosine. We used multivariable Cox proportional hazard regression to analyze the association with mortality of four BP variables: stress minus rest systolic BP (∆SBP), stress minus rest diastolic BP (∆DBP), resting systolic BP (rSBP), and resting diastolic BP (rDBP). Covariates that had univariate P valuesxa0<.10 were entered into the multivariable model. After median 1.7xa0years follow-up, 270 patients died. In univariate analyses, ∆SBP (Pxa0=xa0.082), rSBP (Pxa0=xa0.008), and rDBP (Pxa0<xa0.001) were of potential prognostic value (Pxa0<xa0.10), but ∆DBP was not (Pxa0=xa0.96). After adjustment for other clinical and MPI variables, ∆SBP no longer independently predicted mortality (Pxa0=xa0.082); only lower rSBP (Pxa0=xa0.026) and lower rDBP (Pxa0=xa0.045) remained independently prognostic.ConclusionsIn patients undergoing vasodilator stress MPI, only lower resting BP is an independent predictor of mortality along with other clinical and MPI variables; BP response does not appear to add to risk stratification in these patients.

Prognostic value of Rb-82 positron emission tomography myocardial perfusion imaging in coronary artery bypass patients.

AIMSnWe sought to determine the prognostic value of positron emission tomography (PET) myocardial perfusion imaging (MPI) in patients with prior coronary artery bypass graft (CABG) surgery. PET MPI has recently been shown to provide incremental risk stratification for patients with suspected coronary artery disease (CAD), but the prognostic utility of PET MPI in CABG patients has not been well studied.nnnMETHODS AND RESULTSnA multi-centre PET registry of 7061 patients who underwent Rb-82 PET MPI from four participating centres was screened. Nine hundred and fifty-three CABG patients were identified and their images were analysed. Outcomes of all-cause mortality and cardiac death were collected. With a mean follow-up of 2.4 ± 1.4 years, 128 (13.4%) all-cause deaths and 44 (4.6%) cardiac deaths were observed. Multivariable analyses, adjusted for clinical variables, demonstrated that the summed stress score (SSS) was a significant independent predictor of both all-cause mortality [HR: 1.60 (per 1 category increase in SSS); 95% CI: 1.34-1.92; P < 0.001] and cardiac death (HR: 1.80; 95% CI: 1.33, 2.44; P < 0.001). The receiver-operator characteristic (ROC) curves showed that the addition of SSS increased the area under the curve (AUC) from 0.645 to 0.693 (P = 0.014) for all-cause mortality, and from 0.612 to 0.704 (P = 0.027) for cardiac death. SSS also improved the net reclassification improvement (NRI) for all-cause mortality (category-free NRI = 0.422; 95% CI: 0.240-0.603; P < 0.001) and cardiac death (category-free NRI = 0.552; 95% CI: 0.268-0.836; P < 0.001).nnnCONCLUSIONSnPET MPI provides independent and incremental prognostic value to clinical variables in predicting all-cause mortality and cardiac death in CABG patients.

Prognostic value of vasodilator response using rubidium-82 positron emission tomography myocardial perfusion imaging in patients with coronary artery disease

BackgroundPrognostic value of positron emission tomography (PET) myocardial perfusion imaging (MPI) is well established. There is paucity of data on how the prognostic value of PET relates to the hemodynamic response to vasodilator stress. We hypothesize that inadequate hemodynamic response will affect the prognostic value of PET MPI.Methods and resultsUsing a multicenter rubidium (Rb)-82 PET registry, 3406 patients who underwent a clinically indicated rest/stress PET MPI with a vasodilator agent were analyzed. Patients were categorized as, “responders” [increase in heart rateu2009≥u200910 beats per minute (bpm) and decrease in systolic blood pressure (SBP) ≥10xa0mmHg], “partial responders” (either a change in HR or SBP), and “non-responders” (no change in HR or SBP). Primary outcome was all-cause death (ACD), and secondary outcome was cardiac death (CD). Ischemic burden was measured using summed stress score (SSS) and % left ventricular (LV) ischemia. After a median follow-up of 1.68xa0years (interquartile rangeu2009=u20091.17- 2.55), there were 7.9% (nu2009=u2009270) ACD and 2.6% (nu2009=u200954) CD. Responders with a normal PET MPI had an annualized event rate (AER) of 1.22% (SSS of 0–3) and 1.58% (% LV ischemiau2009=u20090). Partial and non-responders had higher AER with worsening levels of ischemic burden. In the presence of severe SSS ≥12 and LV ischemia of ≥10%, partial responders had an AER of 10.79% and 10.36%, compared to non-responders with an AER of 19.4% and 12.43%, respectively. Patient classification was improved when SSS was added to a model containing clinical variables (NRI: 42%, pu2009<u20090.001) and responder category was added (NRI: 61%, pu2009<u20090.001). The model including clinical variables, SSS and hemodynamic response has good discrimination ability (Harrell C statistics: 0.77 [0.74–0.80]).ConclusionHemodynamic response during a vasodilator Rb-82 PET MPI is predictive of ACD. Partial and non-responders may require additional risk stratification leading to altered patient management.

External validation of the TIMI risk score for secondary cardiovascular events among patients with recent myocardial infarction

BACKGROUND AND AIMSnRisk stratification of patients with recent myocardial infarction (MI) for subsequent cardiovascular (CV) events helps identify patients most likely to benefit from secondary prevention therapies. This study externally validated a new risk score (TRS2˚P) for secondary events derived from the TRA2°P-TIMI 50 trial among post-MI patients from two large health care systems.nnnMETHODSnThis retrospective cohort study included 9618 patients treated for acute MI at either the Cleveland Clinic (CC) or Geisinger Health System (GHS) between 2008 and 2013. Patients with a clinic visit within 2-52 weeks of MI were included and followed for CV death, repeat MI, and ischemic stroke through electronic medical records (EMR). The TRS2˚P is based on nine factors determined through EMR documentation. Discrimination and calibration of the TRS2˚P were quantified in both patient populations.nnnRESULTSnMI patients at CC and GHS were older, had more comorbidities, received fewer medications, and had higher 3-year event rates compared to subjects in the TRA2°P trial: 31% (CC), 33% (GHS), and 10% (TRA2°P-TIMI 50). The proposed risk score had similar discrimination across the three cohorts with c-statistics of 0.66 (CC), 0.66 (GHS), and 0.67 (TRA2°P-TIMI 50). A strong graded relationship between the risk score and event rates was observed in all cohorts, though 3-year event rates were consistently higher within TRS2°P strata in the CC and GHS cohorts relative to TRA2˚P-TIMI 50.nnnCONCLUSIONSnThe TRS2˚P demonstrated consistent risk discrimination across trial and non-trial patients with recent MI, but event rates were consistently higher in the non-trial cohorts.

Predicting Survival From Large Echocardiography and Electronic Health Record Datasets: Optimization With Machine Learning

OBJECTIVESnThe goal of this study was to use machine learning to more accurately predict survival after echocardiography.nnnBACKGROUNDnPredicting patient outcomes (e.g., survival) following echocardiography is primarily based on ejection fraction (EF) and comorbidities. However, there may be significant predictive information within additional echocardiography-derived measurements combined with clinical electronic health record data.nnnMETHODSnMortality was studied in 171,510 unselected patients who underwent 331,317 echocardiograms in a large regional health system. The authors investigated the predictive performance of nonlinear machine learning models compared with that of linear logistic regression models using 3 different inputs: 1) clinical variables, including 90 cardiovascular-relevant International Classification of Diseases, Tenth Revision, codes, and age, sex, height, weight, heart rate, blood pressures, low-density lipoprotein, high-density lipoprotein, and smoking; 2) clinical variables plus physician-reported EF; and 3)xa0clinical variables and EF, plus 57 additional echocardiographic measurements. Missing data were imputed with a multivariate imputation by using a chained equations algorithm (MICE). The authors compared models versus each other and baseline clinical scoring systems by using a mean area under the curve (AUC) over 10 cross-validation folds and across 10xa0survival durations (6 to 60 months).nnnRESULTSnMachine learning models achieved significantly higher prediction accuracy (all AUC >0.82) over common clinical risk scores (AUCxa0= 0.61 to 0.79), with the nonlinear random forest models outperforming logistic regression (pxa0< 0.01). The random forest model including all echocardiographic measurements yielded the highest prediction accuracy (pxa0< 0.01 across all models and survival durations). Only 10 variables were needed to achieve 96% of the maximum prediction accuracy, with 6 of these variables being derived from echocardiography. Tricuspid regurgitation velocity was more predictive of survival than LVEF. In a subset of studies with complete data for the top 10 variables, multivariate imputation by chained equations yielded slightly reduced predictive accuracies (difference in AUC of 0.003) compared with the original data.nnnCONCLUSIONSnMachine learning can fully utilize large combinations of disparate input variables to predict survival after echocardiography with superior accuracy.