Implications of the Use of Artificial Intelligence Predictive Models in Health Care Settings : A Simulation Study.

BACKGROUND: Substantial effort has been directed toward demonstrating uses of predictive models in health care. However, implementation of these models into clinical practice may influence patient outcomes, which in turn are captured in electronic health record data. As a result, deployed models may affect the predictive ability of current and future models. OBJECTIVE: To estimate changes in predictive model performance with use through 3 common scenarios: model retraining, sequentially implementing 1 model after another, and intervening in response to a model when 2 are simultaneously implemented. DESIGN: Simulation of model implementation and use in critical care settings at various levels of intervention effectiveness and clinician adherence. Models were either trained or retrained after simulated implementation. SETTING: Admissions to the intensive care unit (ICU) at Mount Sinai Health System (New York, New York) and Beth Israel Deaconess Medical Center (Boston, Massachusetts). PATIENTS: 130 000 critical care admissions across both health systems. INTERVENTION: Across 3 scenarios, interventions were simulated at varying levels of clinician adherence and effectiveness. MEASUREMENTS: Statistical measures of performance, including threshold-independent (area under the curve) and threshold-dependent measures. RESULTS: At fixed 90% sensitivity, in scenario 1 a mortality prediction model lost 9% to 39% specificity after retraining once and in scenario 2 a mortality prediction model lost 8% to 15% specificity when created after the implementation of an acute kidney injury (AKI) prediction model; in scenario 3, models for AKI and mortality prediction implemented simultaneously, each led to reduced effective accuracy of the other by 1% to 28%. LIMITATIONS: In real-world practice, the effectiveness of and adherence to model-based recommendations are rarely known in advance. Only binary classifiers for tabular ICU admissions data were simulated. CONCLUSION: In simulated ICU settings, a universally effective model-updating approach for maintaining model performance does not seem to exist. Model use may have to be recorded to maintain viability of predictive modeling. PRIMARY FUNDING SOURCE: National Center for Advancing Translational Sciences.

Functional Effects of Cardiomyocyte Injury in COVID-19.

COVID-19 affects multiple organs. Clinical data from the Mount Sinai Health System show that substantial numbers of COVID-19 patients without prior heart disease develop cardiac dysfunction. How COVID-19 patients develop cardiac disease is not known. We integrated cell biological and physiological analyses of human cardiomyocytes differentiated from human induced pluripotent stem cells (hiPSCs) infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the presence of interleukins (ILs) with clinical findings related to laboratory values in COVID-19 patients to identify plausible mechanisms of cardiac disease in COVID-19 patients. We infected hiPSC-derived cardiomyocytes from healthy human subjects with SARS-CoV-2 in the absence and presence of IL-6 and IL-1ß. Infection resulted in increased numbers of multinucleated cells. Interleukin treatment and infection resulted in disorganization of myofibrils, extracellular release of troponin I, and reduced and erratic beating. Infection resulted in decreased expression of mRNA encoding key proteins of the cardiomyocyte contractile apparatus. Although interleukins did not increase the extent of infection, they increased the contractile dysfunction associated with viral infection of cardiomyocytes, resulting in cessation of beating. Clinical data from hospitalized patients from the Mount Sinai Health System show that a significant portion of COVID-19 patients without history of heart disease have elevated troponin and interleukin levels. A substantial subset of these patients showed reduced left ventricular function by echocardiography. Our laboratory observations, combined with the clinical data, indicate that direct effects on cardiomyocytes by interleukins and SARS-CoV-2 infection might underlie heart disease in COVID-19 patients. IMPORTANCE SARS-CoV-2 infects multiple organs, including the heart. Analyses of hospitalized patients show that a substantial number without prior indication of heart disease or comorbidities show significant injury to heart tissue, assessed by increased levels of troponin in blood. We studied the cell biological and physiological effects of virus infection of healthy human iPSC-derived cardiomyocytes in culture. Virus infection with interleukins disorganizes myofibrils, increases cell size and the numbers of multinucleated cells, and suppresses the expression of proteins of the contractile apparatus. Viral infection of cardiomyocytes in culture triggers release of troponin similar to elevation in levels of COVID-19 patients with heart disease. Viral infection in the presence of interleukins slows down and desynchronizes the beating of cardiomyocytes in culture. The cell-level physiological changes are similar to decreases in left ventricular ejection seen in imaging of patients' hearts. These observations suggest that direct injury to heart tissue by virus can be one underlying cause of heart disease in COVID-19.

Uncommon spectral Doppler findings in patients with heart failure.

Spectral Doppler examination is necessary for full hemodynamic assessment of patients with systolic heart failure. It is fully incorporated into comprehensive echocardiographic examination. In this manuscript, we describe two uncommon findings in patients with established severe left ventricular systolic dysfunction: notched aortic regurgitation and merged mitral regurgitation.

Prognostic significance of incorporating exercise tissue doppler mitral annular early diastolic velocity in exercise diastolic dysfunction assessment.

BACKGROUND: The existing algorithm for defining exercise-induced diastolic dysfunction incorporates resting e' velocity as a surrogate of myocardial relaxation. The additive prognostic value of incorporating post-exercise e' velocity in definition of exercise-induced diastolic dysfunction is poorly studied. AIM: To define the additive prognostic value of post-exercise e' septal velocity in the assessment of exercise-induced diastolic dysfunction compared to the traditional approach. METHODS: This retrospective study included 1409 patients undergoing exercise treadmill echocardiography with available full set of diastolic variables. Doppler measures of diastolic function included resting septal e' velocity, post-exercise septal e' velocity, post-exercise E/e' ratio, and post-exercise tricuspid regurgitant jet velocity. Approaches incorporating resting septal e' velocity and post-exercise septal e' velocity were compared in defining exercise-induced diastolic dysfunction, and for association with adverse cardiovascular outcomes. RESULTS: The mean age of study subjects was 56.3 ± 16.5 years and 791 (56%) patients were women. A total of 524 patients had disagreement between resting and post exercise septal e' velocities, and these values showed only weak agreement (kappa statistics: .28, P = .02). All categories of the traditional exercise-induced DD approach incorporating resting septal e' velocity witnessed reclassification when exercise septal e' velocity was used. When both approaches were compared, increased event rates were only evident when both approaches agreed on exercise-induced diastolic dysfunction (HR: 1.92, P < .001, 95% CI: 1.37-2.69). This association persisted after multivariable adjustment and propensity score matching for covariates. CONCLUSION: Incorporation of post-exercise e' velocity into the set of variables defining exercise-induced diastolic dysfunction can improve the prognostic utility of diastolic function assessment.

Tissue Doppler derived biphasic velocities during the pre and post-ejection phases: patterns, concordance and hemodynamic significance in health and disease.

BACKGROUND: Pre-(PRE) and post-ejection (POE) velocities by mitral annular tissue Doppler (TD) are biphasic and may be related to myocardial deformations. We investigated the predominance and concordance of TD-PRE and POE velocities and their effect on myocardial functions in controls and in heart failure (HF) patients. METHODS: Retrospectively, 84 HF patients [57.6 years, 28(33%) females, NYHA: 2.3 ± 0.6, EF: 55 ± 15%, 52(62%) preserved EF, and 32(38%) reduced EF], 42 normal young controls, and 26 asymptomatic age matched controls were included. Echocardiography was done and from mitral annular tissue Doppler recordings, the biphasic PRE and POE velocity signals were identified and compared between groups. RESULTS: While controls had almost always predominantly positive PRE and negative POE, HF had more negative PRE and positive POE. Moreover, almost all controls exhibited normal concordance (positive PRE and negative POE). HF exhibited more abnormal concordance which was significantly associated with worse NYHA, and parameters of diastolic and systolic functions. Opposite PRE and POE velocities correlated significantly in all groups (PREp vs POEn: young:r = 0.52, p < 0.001, age controls:r = 0.79, p < 0.001, HFpEF: r = 0.56, p < 0.001, HFrEF: r = 0.42, p = 0.018; PREn vs POEp: young: r = 0.25,p = 0.1, age controls: r = 0.42, p = 0.04, HFpEF: r = 0.43, p = 0.004, HFrEF: r = 0.61, p < 0.001) and the ratios PRE-P/N and POE-N/P correlated significantly with E/e' in HF only. CONCLUSIONS: In physiological state, TD signals are predominantly positive during PRE and negative during POE. Opposite PRE and POE velocities corelate, representing the PRE-generation and POE-reversal of shortening-stretch relationships, the attenuation of which in HF may be related to elevated LV filling pressures. In HF, partially or completely reversed concordance of PRE and POE is associated with progressive worsening of clinical and hemodynamic profiles.

Deep learning and the electrocardiogram: review of the current state-of-the-art.

In the recent decade, deep learning, a subset of artificial intelligence and machine learning, has been used to identify patterns in big healthcare datasets for disease phenotyping, event predictions, and complex decision making. Public datasets for electrocardiograms (ECGs) have existed since the 1980s and have been used for very specific tasks in cardiology, such as arrhythmia, ischemia, and cardiomyopathy detection. Recently, private institutions have begun curating large ECG databases that are orders of magnitude larger than the public databases for ingestion by deep learning models. These efforts have demonstrated not only improved performance and generalizability in these aforementioned tasks but also application to novel clinical scenarios. This review focuses on orienting the clinician towards fundamental tenets of deep learning, state-of-the-art prior to its use for ECG analysis, and current applications of deep learning on ECGs, as well as their limitations and future areas of improvement.

Insights into functional mitral regurgitation using transillumination rendering.

Secondary mitral regurgitation has been originally explained by tethering of the structurally normal mitral leaflets or by mitral annular dilation after atrial remodeling. Advances in echocardiography have provided more insights into functional anatomy of the mitral valve leaflets as active participants in this entity.

Prognostic significance of exercise-induced diastolic dysfunction: A systematic review.

BACKGROUND: Recent guidelines recommend diastolic stress testing among patients with unexplained dyspnea. Previous studies have reported exercise related change in diastolic parameters as a prognostic marker for worse outcomes. However, the role of exercise-induced diastolic dysfunction (DD) in predicting adverse outcomes has not been fully established. METHOD: We conducted a meta-analysis to explore the prognostic significance of exercise-induced DD. PUBMED/EMBASE/SCOPUS databases were searched for studies reporting adverse outcomes in patients undergoing exercise echocardiography based on diastolic response during exercise. Exercise-induced DD was defined as an increase in E/e' or E/A ratio with stress. Outcomes of interest were cardiovascular mortality or hospitalizations. RESULTS: A total of 8 studies were identified, including 4,462 patients who underwent exercise stress echocardiography. The follow-up ranged from 13 months to 5 years. The major indication for stress testing was exertional dyspnea. All studies reported cardiac mortality and hospitalization in the composite outcome. Meta-analysis conducted using random-effects model showed that exercise-induced DD was associated with a higher likelihood of cardiovascular mortality or hospitalization (HR = 1.32, P < .05). Significant heterogeneity was noted among the studies. CONCLUSIONS: Exercise-induced DD is associated with worse cardiovascular outcomes. Changes in echocardiographic parameters such as e' with exercise might be useful for risk stratification and identification of high-risk patients.

Unsupervised clustering for phenotypic stratification of clinical, demographic, and stress attributes of cardiac risk in patients with nonischemic exercise stress echocardiography.

INTRODUCTION AND AIM: Patients undergoing exercise echocardiography with no evidence of myocardial ischemia are considered a low-risk group; however, this group is likely heterogeneous in terms of short-term adverse events and subsequent cardiac testing. We hypothesized that unsupervised cluster modeling using clinical and stress characteristics can detect heterogeneity in cardiovascular risk and need for subsequent cardiac testing among these patients. METHODS: We retrospectively studied 445 patients who had exercise echocardiography results negative for myocardial ischemia. All patients were followed for adverse cardiovascular events, subsequent cardiac testing, and nonacute coronary syndrome (ACS) revascularization. The heterogeneity of the study subjects was tested using computational clustering, an exploratory statistical method designed to uncover invisible natural groups within data. Clinical and stress predictors of adverse events were extracted and used to construct 3 unsupervised cluster models: clinical, stress, and combined. The study population was split into training (357 patients) and testing sets (88 patients). RESULTS: In the training set, the clinical, stress, and combined cluster models yielded 5, 4, and 3 clusters, respectively. Each model had 1 high-risk and 1 low-risk cluster while other clusters were intermediate. The combined model showed a better predictive ability compared to the clinical or stress models alone. The need for future testing mirrored the pattern of adverse cardiovascular events. A risk score derived from the combined cluster model predicted end points with acceptable accuracy. The patterns of risk and the calculated risk scores were preserved in the testing set. CONCLUSIONS: Patients with no evidence of ischemia on exercise stress echocardiography represent a heterogeneous group. Cluster-based modeling using combined clinical and stress characteristics can expose this heterogeneity. The findings can help better risk-stratify this group of patients and aid cost-effective healthcare utilization toward better diagnostics and therapeutics.

Echocardiography in Patients with HIV Infection.

PURPOSE OF REVIEW: This review aims to outline the important echocardiographic findings observed in patients with human immunodeficiency virus (HIV) infection in the current era of treatment. RECENT FINDINGS: HIV infection has a wide spectrum of cardiac manifestations. Myocardial and pericardial involvement were the primary cardiac manifestations in HIV patients early during the epidemic in the developed countries. In the current era of effective antiretroviral therapy, the spectrum has shifted to metabolic abnormalities (hyperlipidemia, hypertension, etc.), accelerated atherosclerotic disease, and cardiac sequelae related to these abnormalities. Dramatic improvement in life expectancy of patients with HIV infection has resulted in a shift in the developed nations in the spectrum of cardiac manifestations, currently dominated by diastolic dysfunction and coronary artery disease. Echocardiography and advanced echocardiographic techniques play a major role in diagnosis and screening of HIV patients with underlying cardiovascular abnormalities.

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.

BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. OBJECTIVE: The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. METHODS: We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. RESULTS: Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. CONCLUSIONS: We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.

Association of the V122I Hereditary Transthyretin Amyloidosis Genetic Variant With Heart Failure Among Individuals of African or Hispanic/Latino Ancestry.

Importance: Hereditary transthyretin (TTR) amyloid cardiomyopathy (hATTR-CM) due to the TTR V122I variant is an autosomal-dominant disorder that causes heart failure in elderly individuals of African ancestry. The clinical associations of carrying the variant, its effect in other African ancestry populations including Hispanic/Latino individuals, and the rates of achieving a clinical diagnosis in carriers are unknown. Objective: To assess the association between the TTR V122I variant and heart failure and identify rates of hATTR-CM diagnosis among carriers with heart failure. Design, Setting, and Participants: Cross-sectional analysis of carriers and noncarriers of TTR V122I of African ancestry aged 50 years or older enrolled in the Penn Medicine Biobank between 2008 and 2017 using electronic health record data from 1996 to 2017. Case-control study in participants of African and Hispanic/Latino ancestry with and without heart failure in the Mount Sinai BioMe Biobank enrolled between 2007 and 2015 using electronic health record data from 2007 to 2018. Exposures: TTR V122I carrier status. Main Outcomes and Measures: The primary outcome was prevalent heart failure. The rate of diagnosis with hATTR-CM among TTR V122I carriers with heart failure was measured. Results: The cross-sectional cohort included 3724 individuals of African ancestry with a median age of 64 years (interquartile range, 57-71); 1755 (47%) were male, 2896 (78%) had a diagnosis of hypertension, and 753 (20%) had a history of myocardial infarction or coronary revascularization. There were 116 TTR V122I carriers (3.1%); 1121 participants (30%) had heart failure. The case-control study consisted of 2307 individuals of African ancestry and 3663 Hispanic/Latino individuals; the median age was 73 years (interquartile range, 68-80), 2271 (38%) were male, 4709 (79%) had a diagnosis of hypertension, and 1008 (17%) had a history of myocardial infarction or coronary revascularization. There were 1376 cases of heart failure. TTR V122I was associated with higher rates of heart failure (cross-sectional cohort: n = 51/116 TTR V122I carriers [44%], n = 1070/3608 noncarriers [30%], adjusted odds ratio, 1.7 [95% CI, 1.2-2.4], P = .006; case-control study: n = 36/1376 heart failure cases [2.6%], n = 82/4594 controls [1.8%], adjusted odds ratio, 1.8 [95% CI, 1.2-2.7], P = .008). Ten of 92 TTR V122I carriers with heart failure (11%) were diagnosed as having hATTR-CM; the median time from onset of symptoms to clinical diagnosis was 3 years. Conclusions and Relevance: Among individuals of African or Hispanic/Latino ancestry enrolled in 2 academic medical center-based biobanks, the TTR V122I genetic variant was significantly associated with heart failure.

Stress cardiomyopathy: Provoked chaotic T-wave lability.

Potentially lethal arrhythmia, occurring at presentation or during hospitalization, are a part of the clinical spectrum of stress cardiomyopathy. There is significant association between the catecholamine provoked nonalternating beat to beat fluctuations in T-wave morphology, termed T-wave lability (TWL), and the clinical risk of arrhythmia. We report four patients with diagnosis of stress cardiomyopathy, in whom serial electrocardiography showed macrovoltage nonalternating fluctuations in T-wave morphology.

Echocardiographic 3D-guided 2D planimetry in quantifying left-sided valvular heart disease.

Echocardiographic 3D-guided 2D planimetry can improve the accuracy of valvular disease assessment. Acquisition of 3D pyramidal dataset allows subsequent multiplanar reconstruction with accurate orthogonal plane alignment to obtain the correct borders of an anatomic orifice or flow area. Studies examining the 3D-guided 2D planimetry approach in left-sided valvular heart disease were identified and reviewed. The strongest evidence exists for estimating mitral valve area in patients with rheumatic mitral valve stenosis and vena contracta area in patients with mitral regurgitation (both primary and secondary). 3D-guided approach showed excellent feasibility and reproducibility in most studies, as well as time efficiency and good correlation with reference and comparator methods. Therefore, 3D-guided 2D planimetry can be used as an important clinical tool in quantifying left-sided valvular heart disease, especially mitral valve disorders.

Comparison of the current reasons for undergoing pharmacologic stress during echocardiographic and radionuclide stress testing.

BACKGROUND: Symptom-limited exercise is the preferred method of cardiac stress testing, but pharmacologic testing has been increasing over time. The exact reasons for pharmacologic stress testing have not been rigorously categorized. Thus, we systematically explored the reasons for pharmacologic stress testing in patients referred for cardiac stress imaging. METHODS: We studied consecutive patients referred for stress imaging [stress echocardiography or radionuclide myocardial perfusion imaging (MPI)] at Mount Sinai St Luke's hospital between August 2013 and April 2014. Baseline information was obtained using a standardized questionnaire and a trained physician triaged the patient for symptom-limited exercise stress testing or pharmacologic stress testing. RESULTS: In total, 551(48%) of our entire stress cohort underwent cardiac imaging following initial exercise testing and 589 (52%) underwent imaging with initial pharmacologic stress testing. Deconditioning and inability to walk (primarily due to musculoskeletal conditions) constituted the top two reasons for performing pharmacologic stress, followed by frailty, left bundle branch block (for MPI), resting wall motion abnormality (for echocardiography), and failed exercise attempts. The reasons for performing pharmacologic stress testing were similar in the MPI and echocardiography patients, despite a much higher level of disease acuity in the MPI group. CONCLUSIONS: We have applied a systematic approach for categorizing the reasons for pharmacologic stress. These reasons are heterogeneous, but similar across MPI and echo stress laboratories.

Comparative effectiveness of coronary CT angiography vs stress cardiac imaging in patients following hospital admission for chest pain work-up: The Prospective First Evaluation in Chest Pain (PERFECT) Trial.

BACKGROUND: Because the frequency of cardiac event rates is low among chest pain patients following either performance of coronary CT angiography (CCTA) or stress testing, there is a need to better assess how these tests influence the central management decisions that follow from cardiac testing. The present study was performed to assess the relative impact of CCTA vs stress testing on medical therapies and downstream resource utilization among patients admitted for the work-up of chest pain. METHODS: The admitted patients were randomized in a 1:1 ratio to either cardiac imaging stress test or CCTA. Primary outcomes were time to discharge, change in medication usage, and frequency of downstream testing, cardiac interventions, and cardiovascular re-hospitalizations. We randomized 411 patients, 205 to stress testing, and 206 to CCTA. RESULTS: There were no differences in time to discharge or initiation of new cardiac medications at discharge. At 1 year follow-up, there was no difference in the number of patients who underwent cardiovascular downstream tests in the CCTA vs stress test patients (21% vs 15%, P = .1) or cardiovascular hospitalizations (14% vs 16%, P = .5). However, there was a higher frequency of invasive angiography in the CCTA group (11% vs 2%, P = .001) and percutaneous coronary interventions (6% vs 0%, P < .001). CONCLUSIONS: Randomization of hospitalized patients admitted for chest pain work-up to either CCTA or to stress testing resulted in similar discharge times, change in medical therapies at discharge, frequency of downstream noninvasive testing, and repeat hospitalizations. However, a higher frequency of invasive coronary angiography and revascularization procedures were performed in the CCTA arm. (ClinicalTrials.gov number, NCT01604655.).

The presence of diastolic and systolic dysfunction in patients with impaired relaxation filling pattern.

BACKGROUND: Impaired relaxation filling pattern in the presence of preserved left ventricular ejection fraction is a common finding which is ascribed to early diastolic dysfunction. We thought to determine the distribution of various markers of systolic and diastolic dysfunction in these patients. METHODS: A total of 106 patients were included in this retrospective observational study. Diastolic dysfunction was defined using the American Society of Echocardiography recommendations ("50% rule"). The systolic dysfunction was evaluated by global longitudinal strain and circumferential strain. For further analysis, the patients were divided into the lower strain (lower tertile) and higher strain (upper tertiles) groups based on longitudinal strain. RESULTS: There were marked differences between the groups in essential echocardiographic parameters. Patients in the lower strain group were more likely to have definite diastolic dysfunction (23% vs 7%, P<.01) and less likely to have normal diastolic function (54% vs 80%, P<.01). They also showed lower circumferential strain (-21.2% vs -25.7%, P<.01). In multivariate analysis, left atrial enlargement (odds ratio (OR) 4.6, 95% confidence interval (CI) 1.2-17.1), left ventricular mass index (OR 1.03, 95% CI 1.0-1.1), left ventricular end-diastolic volume (OR 1.1, 95% CI 1.0-1.1), and E-wave deceleration time (OR 0.99, 95% CI 0.98-1.0) were independently associated with lower global longitudinal strain. CONCLUSIONS: Patients with impaired relaxation filling pattern in the presence of preserved left ventricular ejection fraction have a wide spectrum of left ventricular systolic and diastolic performance abnormalities. Isolated assessment of diastolic dysfunction may not fully characterize this group of patients.

Combining stress-only myocardial perfusion imaging with coronary calcium scanning as a new paradigm for initial patient work-up: an exploratory analysis.

BACKGROUND: We conducted an exploratory analysis to test whether the addition of a CAC scan can increase the applicability of stress-only SPECT-MPI. METHODS: We studied 162 patients referred for rest/stress SPECT-MPI who underwent a CAC scan. Each scan was interpreted by two readers in stepwise fashion: stress-only images; addition of clinical data; and addition of CAC data. At each step, the reader was asked if rest SPECT-MPI was necessary. RESULTS: Stress-only images were interpreted as normal in 62, probably normal in 42, equivocal in 15, probably abnormal in 5, and definitely abnormal in 38 patients. Rest SPECT-MPI imaging was considered necessary, in 0% of normal studies, but in 88% of probably normal studies, and 100% of those with equivocal/abnormal studies. Addition of the clinical data did not materially change this decision. Additional consideration of the CAC scan results did not influence the deemed lack of need for a rest SPECT-MPI with normal SPECT-MPI or the necessity of rest SPECT-MPI with abnormal SPECT-MPI. However, the CAC scan reduced the deemed need for a rest SPECT-MPI in 72% with a probably normal, 47% with an equivocal, and 40% of those with a probably abnormal SPECT-MPI. CONCLUSIONS: Our exploratory analysis indicates that addition of a CAC scan to stress SPECT-MPI tends to diminish experienced readers' deemed need to perform rest SPECT-MPI studies among patients with probably normal or borderline stress-only SPECT-MPI studies. Thus, further study appears warranted to assess the utility of using CAC scanning as a means for increasing the percent of SPECT-MPI studies that can be performed as stress-only studies.