Development of a Risk Score to Predict New Pacemaker Implantation After Transcatheter Aortic Valve Replacement

ObjectivesThe aim of this study was to define risk factors and develop a predictive risk score for new pacemaker implantation (PMI) after transcatheter aortic valve replacement (TAVR).BackgroundTAVR has become an accepted treatment alternative for patients with severe aortic stenosis at elevated surgical risk. New PMI is a common occurrence after TAVR and is associated with poorer outcomes.MethodsAll patients without prior valve procedures undergoing elective TAVR with the Edwards SAPIEN 3 at a single institution (n = 1,266) were evaluated. Multivariate analysis was performed to evaluate for predictors of PMI in this population in a derivation cohort of patients with complete data (n = 778), and this model was used to develop the Emory risk score (ERS), which was tested in a validation cohort (n = 367).ResultsFifty-seven patients (7.3%) in the derivation cohort required PMI. In a regression model, history of syncope (odds ratio [OR]: 2.5; p = 0.026), baseline right bundle branch block (OR: 4.3; p < 0.001), QRS duration ≥138 ms (OR: 2.5; p = 0.017), and valve oversizing >15.6% (OR: 1.9; p = 0.041) remained independent predictors of PMI and were included in the ERS. The ERS was strongly associated with PMI (per point increase OR: 2.2; p < 0.001) with an area under the receiver-operating characteristic curve of 0.778 (p < 0.001), which was similar to its performance in the derivation cohort.ConclusionsA history of syncope, right bundle branch block, longer QRS duration, and higher degree of oversizing are predictive of the need for PMI after TAVR. Additionally, the ERS for PMI was developed and validated, representing a simple bedside tool to aid in risk stratification for patients for undergoing TAVR.     

Characteristics and association with survival of respiratory-related hospitalization in Japanese idiopathic pulmonary fibrosis patients

BackgroundThe characteristics and significance of respiratory-related hospitalization in patients with idiopathic pulmonary fibrosis (IPF) in Asian countries remain unknown. The purpose of this study was to define the characteristics of respiratory-related hospitalization and to inspect the relationship between respiratory-related hospitalization and subsequent survival in patients with IPF in Japanese general practice.MethodsPatients with IPF who underwent clinical evaluation between February 2008 and August 2017 were screened. Only those who had undergone evaluation within 1 year after the diagnosis of IPF were included in the study. The post-diagnosis pulmonary function tests were considered the registration point. We then performed a 6-month landmark analysis including only patients who were alive 6 months after the registration. The characteristics of respiratory-related hospitalizations during the 6 months after registration and the association between respiratory-related hospitalization and survival were investigated.ResultsA total of 106 patients with IPF were included in the study. The mean forced vital capacity (FVC) at registration was 80.2 ± 25.1% predicted. Seventeen patients (16.0%) had respiratory-related hospitalization during the 6 months after registration. Pneumonia was the most frequent reason for hospitalization (47.0%), followed by acute exacerbation of IPF (29.4%). In multivariate analysis, % predicted FVC (hazard ratio: 0.98, 95% confidence interval: 0.96–0.99, p = 0.004), 6-month decrease in % predicted FVC (1.05, 1.02–1.08, 0.005), and respiratory-related hospitalization (2.45, 1.24–4.85, 0.009) were significantly associated with survival.ConclusionsPneumonia is the most frequent cause of respiratory-related hospitalization in Japanese IPF patients. Furthermore, respiratory-related hospitalization is significantly associated with subsequent poor survival.     

Predictive factors for the long-term use of pirfenidone in patients with fibrosing interstitial lung disease

BackgroundPirfenidone is an anti-fibrotic agent approved for idiopathic pulmonary fibrosis (IPF), and long-term treatment data and the effect of continuation after disease progression have been reported. The efficacy and safety of pirfenidone in fibrosing interstitial lung disease (ILD) patients without IPF have been recently reported in clinical trials; therefore, the benefits of long-term treatment are also expected. This study aims to analyze the long-term treatment data of pirfenidone and clarify the predictive factors for long-term use of pirfenidone in non-IPF patients.MethodsWe retrospectively reviewed the records of consecutive fibrosing ILD patients who started using pirfenidone between 2008 and 2014.ResultsOf the 266 fibrosing ILD patients, 167 patients had IPF, and 99 had non-IPF. Despite the non-significant differences in body size and pulmonary function between IPF and non-IPF patients, the non-IPF patients had better overall survival than the IPF patients (median 4.06 years vs. 2.09 years, p < 0.0001). In addition, the non-IPF patients had a significantly longer time to treatment discontinuation than the IPF patients (median 2.20 years vs. 1.20 years, p = 0.002). Multivariate logistic regression analysis for ≥2 years of use of pirfenidone showed that the percent predicted forced vital capacity (%FVC) and age were predictive factors common to both IPF and non-IPF patients.ConclusionsOur results indicate that non-IPF patients can continue using pirfenidone for longer durations than IPF patients. Initiation of pirfenidone for fibrosing ILD patients with higher %FVC and younger age would lead to long-term use of pirfenidone.     

Predictors of acute exacerbation in biopsy-proven idiopathic pulmonary fibrosis

BackgroundAcute exacerbation (AE) is a major cause of death in patients with idiopathic pulmonary fibrosis (IPF). Current evidence on AE-IPF has been largely based on clinical, rather than pathological, analyses.MethodsWe investigated AE incidence and its predictors using clinical, radiological, and pathological data of patients diagnosed with IPF by multi-disciplinary discussion.This study, a secondary analysis of previous research, included 155 patients with IPF who underwent surgical lung biopsy (SLB). Cumulative AE incidence was evaluated by the Kaplan–Meier method. Predictors of AE-IPF were analyzed with a Fine-Gray sub-distribution hazard model. Sub-analysis was performed using propensity score-matching analysis.ResultsIn this cohort, the median age of the patients was 66 years and the median percent-predicted forced vital capacity was 82.8%. The cumulative AE incidence rates at 30 days and one year post SLB were 1.9% and 7.6%, respectively. On multivariable analysis, a lower percent-predicted diffusing capacity of the lung for carbon monoxide (%DL_CO) (hazard ratio 0.98 per 1% increase, P = 0.02) and fibroblastic foci (FF)-present (vs. absent; hazard ratio 3.01, P = 0.04) were independently associated with a higher incidence of AE. The propensity score-matching analysis with adjustment for age, gender, and %DL_CO revealed that the cumulative AE incidence rate was significantly higher in the FF-present subgroup than in the FF-absent subgroup (1-year incidence rate, 10.5% vs. 0%, respectively; P = 0.04 by Gray's test).ConclusionsFF and %DL_CO were independent predictors of AE in patients with biopsy-proven IPF. FF may be associated with the pathogenesis of AE-IPF.     

Human epididymis protein 4 is a new biomarker to predict the prognosis of progressive fibrosing interstitial lung disease

BackgroundThe clinical course and prognosis of progressive fibrosing interstitial lung diseases (PF-ILDs) vary between individuals. Notably, predictive serum biomarkers for disease management are needed. Serum human epididymis protein 4 (HE4) is reportedly elevated in patients with idiopathic pulmonary ?brosis (IPF); however, its clinical utility remains unknown. We evaluated the potential of serum HE4 as a biomarker for patients with PF-ILD.MethodsSerum HE4 was measured in a retrospective study consisting of 34 patients with PF-ILD and 40 healthy volunteers. The relationship between serum HE4 levels and clinical parameters or prognosis was investigated. To validate the significance of results obtained, a prospective observational study was performed in 37 patients presenting PF-ILD and 40 control patients without PF-ILD.ResultsSerum HE4 levels were higher in patients with PF-ILD than in healthy volunteers (P < 0.01). Moreover, serum HE4 levels correlated with the extent of honeycombing on chest high-resolution computed tomography (r = 0.41, P = 0.015). In multivariate analysis using the Cox proportional hazard model, higher HE4 levels (>238 pmol/L) were associated with an elevated mortality risk; hazard ratio (HR) 7.27, 95% CI 1.56–34.0, P = 0.01 in the derivation cohort; HR 44.3, 95% CI 4.19–468, P < 0.01 in validation cohort.ConclusionsSerum HE4 levels may serve as a new diagnostic and prognostic biomarker for patients with PF-ILD.     

Left Atrial Strain Impairment Precedes Geometric Remodeling as a Marker of Post-Myocardial Infarction Diastolic Dysfunction

ObjectivesThe aims of this study were to test the magnitude of agreement between echocardiography (echo)- and cardiac magnetic resonance (CMR)–derived left atrial (LA) strain and to study their relative diagnostic performance in discriminating diastolic dysfunction (DD) and predicting atrial fibrillation (AF).BackgroundsPeak atrial longitudinal strain (PALS) is a novel performance index. Utility of echo-quantified LA strain has yet to be prospectively tested in relation to current DD guidelines or compared to CMR.MethodsThe study population comprised 257 post-myocardial infarction (MI) patients undergoing echo and CMR, including prospective derivation (n = 157) and clinical validation (n = 100) cohorts. DD was graded on echo using established consensus guidelines blinded to strain results.ResultsPALS on both echo and CMR was nearly 2-fold lower among patients with versus no DD (p < 0.001) and was significantly different in those with mild versus no DD (p < 0.01). In contrast, LA geometric parameters including echo- and CMR-derived volumes were significantly different between advanced versus no DD groups (p < 0.001) but not between groups with mild versus no DD (all p > 0.05). Echo and CMR PALS yielded small differences irrespective of orientation and similar diagnostic performance for DD in the derivation (area under the curve [AUC]: 0.70 to 0.78) and validation (AUC: 0.75 to 0.78) cohorts. Impaired PALS on both modalities was independently associated with MI size (p < 0.001). During 4.4 ± 3.8 years of follow-up in the derivation cohort, 8% developed AF. Both 2-chamber echo- and CMR-derived PALS stratified arrhythmic risk (p = 0.004 and p = 0.02, respectively), including a 4-fold difference among patients in the lowest versus remainder of quartiles of echo-derived PALS (24% vs. 6%). Similarly, echo and CMR PALS were lower (both p < 0.05) among patients with subsequent heart failure hospitalizations.ConclusionsEcho-derived PALS parallels results of CMR, yields incremental diagnostic utility versus LA geometry for stratifying presence and severity of DD, and improves prediction of AF and congestive heart failure after MI.     

Deep-Learning Models for the Echocardiographic Assessment of Diastolic Dysfunction

ObjectivesThe authors explored a deep neural network (DeepNN) model that integrates multidimensional echocardiographic data to identify distinct patient subgroups with heart failure with preserved ejection fraction (HFpEF).BackgroundThe clinical algorithms for phenotyping the severity of diastolic dysfunction in HFpEF remain imprecise.MethodsThe authors developed a DeepNN model to predict high- and low-risk phenogroups in a derivation cohort (n = 1,242). Model performance was first validated in 2 external cohorts to identify elevated left ventricular filling pressure (n = 84) and assess its prognostic value (n = 219) in patients with varying degrees of systolic and diastolic dysfunction. In 3 National Heart, Lung, and Blood Institute–funded HFpEF trials, the clinical significance of the model was further validated by assessing the relationships of the phenogroups with adverse clinical outcomes (TOPCAT [Aldosterone Antagonist Therapy for Adults With Heart Failure and Preserved Systolic Function] trial, n = 518), cardiac biomarkers, and exercise parameters (NEAT-HFpEF [Nitrate’s Effect on Activity Tolerance in Heart Failure With Preserved Ejection Fraction] and RELAX-HF [Evaluating the Effectiveness of Sildenafil at Improving Health Outcomes and Exercise Ability in People With Diastolic Heart Failure] pooled cohort, n = 346).ResultsThe DeepNN model showed higher area under the receiver-operating characteristic curve than 2016 American Society of Echocardiography guideline grades for predicting elevated left ventricular filling pressure (0.88 vs. 0.67; p = 0.01). The high-risk (vs. low-risk) phenogroup showed higher rates of heart failure hospitalization and/or death, even after adjusting for global left ventricular and atrial longitudinal strain (hazard ratio [HR]: 3.96; 95% confidence interval [CI]: 1.24 to 12.67; p = 0.021). Similarly, in the TOPCAT cohort, the high-risk (vs. low-risk) phenogroup showed higher rates of heart failure hospitalization or cardiac death (HR: 1.92; 95% CI: 1.16 to 3.22; p = 0.01) and higher event-free survival with spironolactone therapy (HR: 0.65; 95% CI: 0.46 to 0.90; p = 0.01). In the pooled RELAX-HF/NEAT-HFpEF cohort, the high-risk (vs. low-risk) phenogroup had a higher burden of chronic myocardial injury (p < 0.001), neurohormonal activation (p < 0.001), and lower exercise capacity (p = 0.001).ConclusionsThis publicly available DeepNN classifier can characterize the severity of diastolic dysfunction and identify a specific subgroup of patients with HFpEF who have elevated left ventricular filling pressures, biomarkers of myocardial injury and stress, and adverse events and those who are more likely to respond to spironolactone.     

Serial 6-month change in forced vital capacity predicts subsequent decline and mortality in Japanese patients with newly diagnosed idiopathic pulmonary fibrosis

BackgroundThe clinical course of idiopathic pulmonary fibrosis (IPF) is characterized by a progressive decline in lung function; however, predicting changes in lung function is difficult. We sought to determine whether the prior 6-month trend in forced vital capacity (FVC) could predict mortality and the subsequent 6-month trend in FVC.MethodsWe retrospectively analyzed consecutive patients with newly diagnosed IPF who underwent serial pulmonary function tests. The immediate two years after the initial evaluation were divided into four terms of six months each and stratified on the basis of presence or absence of a ≥10% relative decline in FVC at six months (declined and stable groups, respectively).ResultsWe included 107 patients with %predicted FVC of 80.8% and %predicted diffusing capacity of the lung for carbon monoxide of 58.9%. In multivariate analysis, a decline in %predicted FVC in the initial six months was found to be an independent prognostic factor (hazard ratio 4.45, 95% confidence interval 2.62–7.56, p < 0.01). Among the 46 terms in which the FVC declined during the initial 1.5-year study period, a decline in FVC was exhibited in 23 (50.0%) of the subsequent terms. Among 231 terms in which FVC remained stable, a decline was observed in 32 (13.9%) of the subsequent terms (relative risk 3.61, p < 0.01). The frequency of FVC decline in each term was 16–27%. FVC was stable or declined in all four terms in 50.5% and 15.9% of cases, respectively.ConclusionsSix-month decline in FVC predicts subsequent FVC change and mortality in IPF patients in the era of antifibrotic agents.     

Automated Algorithm Using Pre-Intervention Fractional Flow Reserve Pullback Curve to Predict Post-Intervention Physiological Results

ObjectivesThis study sought to develop an automated algorithm using pre-percutaneous coronary intervention (PCI) fractional flow reserve (FFR) pullback recordings to predict post-PCI physiological results in the pre-PCI phase.BackgroundBoth FFR and percent FFR increase measured after PCI showed incremental prognostic implications. However, there is no current method to predict post-PCI physiological results using physiological assessment in the pre-PCI phase.MethodsAn automated algorithm that analyzes instantaneous FFR gradient per unit time (dFFR(t)/dt) was developed from the derivation cohort (n = 30). Using dFFR(t)/dt, the pattern of atherosclerotic disease in each patient was classified into 3 groups (major, mixed, and minor FFR gradient groups) in both the internal validation cohort with constant pullback method (n = 234) and the external validation cohort with nonstandardized pullback methods (n = 252). All patients in the validation cohorts underwent PCI on the basis of pre-PCI FFR ≤0.80. Suboptimal post-PCI physiological results were defined as both post-PCI FFR <0.84 and percent FFR increase ≤15%. From the derivation cohort, cutoffs of dFFR(t)/dt for major and minor FFR gradient were 0.035/s and 0.015/s, respectively.ResultsIn validation cohorts, dFFR(t)/dt showed significant correlations with percent FFR increase (R = 0.801; p < 0.001) and post-PCI FFR (R = 0.099; p = 0.029). In both the internal and external validation cohorts, the major FFR gradient group showed significantly higher post-PCI FFR and percent FFR increase compared with those in the mixed or minor FFR gradient groups (all p values <0.001). The proportions of suboptimal post-PCI physiological results were significantly different among 3 groups (10.4% vs. 25.8% vs. 45.7% for the major, mixed, and minor FFR gradient groups, respectively; p < 0.001) in validation cohorts. Absence of major FFR gradient lesion (odds ratio: 2.435, 95% [CI]: 1.252 to 4.734; p = 0.009) and presence of minor FFR gradient lesion (odds ratio: 2.756, 95% confidence interval: 1.629 to 4.664; p < 0.001) were independent predictors for suboptimal post-PCI physiological results.ConclusionsThe automated algorithm analyzing pre-PCI pullback curve was able to predict post-PCI physiological results. The incidence of suboptimal post-PCI physiological results was significantly different according to algorithm-based classifications in the pre-PCI physiological assessment. (Automated Algorithm Detecting Physiologic Major Stenosis and Its Relationship with Post-PCI Clinical Outcomes [Algorithm-PCI]; NCT04304677)     

A New Index for Pre-Operative Cardiovascular Evaluation

BackgroundCurrently used indices for pre-operative cardiovascular evaluation are either powerful, but complex, or simple, but with weak discriminatory power.ObjectivesThis study sought to prospectively derive and validate a simple powerful index that can stratify the cardiovascular risk of patients undergoing noncardiac surgery.MethodsThe derivation cohort consisted of 3,284 prospectively enrolled adult patients undergoing noncardiac surgery at the American University of Beirut Medical Center. The validation cohort consisted of 1,167,414 patients registered in the American College of Surgeons National Surgical Quality Improvement Program database. The primary outcome measure was death, myocardial infarction, or stroke at 30 days after surgery.ResultsThe primary outcome occurred in 38 patients (1.2%) in the derivation cohort. Multivariate logistic regression analysis in the derivation cohort identified 6 data elements to be included in the prediction model: age ≥75 years, history of heart disease, symptoms of angina or dyspnea, hemoglobin <12 mg/dl, vascular surgery, and emergency surgery. Each patient was assigned a Cardiovascular Risk Index (CVRI) of 0, 1, 2, 3, and >3 based on the number of data elements present. The incidence of the primary outcome increased steadily across the CVRI groups in both the derivation (0%, 0.5%, 2.0%, 5.6%, and 15.7%, respectively; p < 0.0001) and validation (0.3%, 1.6%, 5.6%, 11.0%, and 17.5%, respectively; p < 0.0001) cohorts. The discriminatory power of the new CVRI was further confirmed by constructing a receiver-operating characteristic curve that had an area under the curve of 0.90 in the derivation cohort and 0.82 in the validation dataset.ConclusionsThis study reports a new index for pre-operative cardiovascular evaluation which has a strong discriminatory power that can effectively stratify patients into low- (CVRI 0 to 1), intermediate- (CVRI 2 to 3), and high-risk (CVRI >3) groups. This has important implications for the efficient triage and management of patients scheduled for noncardiac surgery.     

Extent of pulmonary fibrosis on high-resolution computed tomography is a prognostic factor in patients with pleuroparenchymal fibroelastosis

BackgroundSeveral prognostic factors for pleuroparenchymal fibroelastosis (PPFE) have recently been reported. However, detailed high-resolution computed tomography (HRCT) findings have not yet been evaluated as prognostic factors. This study retrospectively investigated whether HRCT findings are prognostic factors in patients with PPFE compared to those with idiopathic pulmonary fibrosis (IPF).MethodsPatients with PPFE and IPF diagnosed at our hospital between January 2008 and December 2016 were enrolled. Clinical and HRCT characteristics were obtained. In addition to our patients, we also analyzed data of PPFE patients whose cause of death had been identified in previous studies.ResultsWe enrolled 15 patients with PPFE and 75 patients with IPF. Consolidation and maximum pleural thickening were significantly higher in patients with PPFE than in those with IPF (both P < .001). Fibrosis score, honeycomb area, and traction bronchiectasis were not significantly different between these patient groups but were significant prognostic factors in patients with PPFE in univariate analysis (P = .021, P = .017, and P = .014, respectively). The proportions of deaths by acute exacerbation or lung cancer were significantly lower in patients with PPFE than in those with IPF (P < .001 and P = .001, respectively), whereas death by respiratory failure was significantly more frequent in PPFE patients (P < .001).ConclusionsHRCT findings, such as fibrosis score, honeycomb area, and traction bronchiectasis, were independent prognostic factors in patients with PPFE. Respiratory failure, but not acute exacerbation and lung cancer, was the main cause of death in patients with PPFE.     

Limited efficacy of nintedanib for idiopathic pleuroparenchymal fibroelastosis

BackgroundThe antifibrotic agent nintedanib has been reported to effectively prevent the decline in forced vital capacity (FVC) in a broad range of interstitial lung diseases. However, the efficacy of nintedanib against idiopathic pleuroparenchymal fibroelastosis (iPPFE) remains unclear.MethodsWe retrospectively examined patients with idiopathic PPFE or idiopathic pulmonary fibrosis (IPF) who received nintedanib for more than 6 months. We evaluated annual changes in %FVC, radiological PPFE lesions, and body weight before and during nintedanib treatment. To investigate radiological PPFE lesions, we examined the fibrosis score, which was defined as the mean percentage of the high attenuation area in the whole lung parenchyma using three axial computed tomography images.ResultsOverall, 15 patients with iPPFE and 27 patients with IPF were included in the present study. In patients with IPF, the annual rate of decline in %FVC was significantly lower during nintedanib treatment than that before treatment (?2.01%/year [?7.64 to 3.21] versus ?7.64%/year [?10.8 to ?4.44], p = 0.031). Meanwhile, in patients with iPPFE, the annual rate of decline in %FVC during nintedanib treatment was higher than that before treatment (?18.0%/year [?21.6 to ?12.7] versus ?9.40%/year [?12.3 to ?8.23], p = 0.109). In addition, nintedanib treatment failed to inhibit the annual rate of increase in fibrosis score in patients with iPPFE (6.53/year [1.18–15.3] during treatment versus 2.70/year [0.27–12.2] before treatment, p = 0.175).ConclusionsNintedanib efficacy may be limited in patients with iPPFE.     

CMR DENSE and the Seattle Heart Failure Model Inform Survival and Arrhythmia Risk After CRT

ObjectivesThis study sought to determine if combining the Seattle Heart Failure Model (SHFM-D) and cardiac magnetic resonance (CMR) provides complementary prognostic data for patients with cardiac resynchronization therapy (CRT) defibrillators.BackgroundThe SHFM-D is among the most widely used risk stratification models for overall survival in patients with heart failure and implantable cardioverter-defibrillators (ICDs), and CMR provides highly detailed information regarding cardiac structure and function.MethodsCMR Displacement Encoding with Stimulated Echoes (DENSE) strain imaging was used to generate the circumferential uniformity ratio estimate with singular value decomposition (CURE-SVD) circumferential strain dyssynchrony parameter, and the SHFM-D was determined from clinical parameters. Multivariable Cox proportional hazards regression was used to determine adjusted hazard ratios and time-dependent areas under the curve for the primary endpoint of death, heart transplantation, left ventricular assist device, or appropriate ICD therapies.ResultsThe cohort consisted of 100 patients (65.5 [interquartile range 57.7 to 72.7] years; 29% female), of whom 47% had the primary clinical endpoint and 18% had appropriate ICD therapies during a median follow-up of 5.3 years. CURE-SVD and the SHFM-D were independently associated with the primary endpoint (SHFM-D: hazard ratio: 1.47/SD; 95% confidence interval: 1.06 to 2.03; p = 0.02) (CURE-SVD: hazard ratio: 1.54/SD; 95% confidence interval: 1.12 to 2.11; p = 0.009). Furthermore, a favorable prognostic group (Group A, with CURE-SVD <0.60 and SHFM-D <0.70) comprising approximately one-third of the patients had a very low rate of appropriate ICD therapies (1.5% per year) and a greater (90%) 4-year survival compared with Group B (CURE-SVD ≥0.60 or SHFM-D ≥0.70) patients (p = 0.02). CURE-SVD with DENSE had a stronger correlation with CRT response (r = −0.57; p < 0.0001) than CURE-SVD with feature tracking (r = −0.28; p = 0.004).ConclusionsA combined approach to risk stratification using CMR DENSE strain imaging and a widely used clinical risk model, the SHFM-D, proved to be effective in this cohort of patients referred for CRT defibrillators. The combined use of CMR and clinical risk models represents a promising and novel paradigm to inform prognosis and device selection in the future.     

A Novel Assessment Using Projected Transmitral Gradient Improves Diagnostic Yield of Doppler Hemodynamics in Rheumatic and Calcific Mitral Stenosis

ObjectivesThe aims of this study were to: 1) develop a formula for projected transmitral gradient (TMG), expected gradient under normal heart rate (HR), and stroke volume (SV); and 2) assess the prognostic value of projected TMG.BackgroundIn mitral stenosis (MS), TMG is highly dependent on hemodynamics, often leading to discordance between TMG and mitral valve area.MethodsAll patients with suspected MS based on echocardiography from 2001 to 2017 were analyzed. Data were randomly split (2:1); projected TMG was modeled in the derivation cohort, then tested in the validation cohort. The composite endpoint was death or mitral valve intervention.ResultsOf 4,973 patients with suspected MS, severe and moderate MS, defined as mitral valve area ≤1.5 and >1.5 to 2.0 cm², were present in 437 (9%) and 936 (19%), respectively. In the derivation cohort (n = 3,315; age 73 ± 12 years; 34% male), corresponding gradients were TMG ≥6 and 4 to <6 mm Hg, respectively, under normal hemodynamics. Based on the impact of hemodynamics on TMG, the formula was projected TMG = TMG ? 0.07 (HR ? 70) ? 0.03 (SV ? 97) in men and projected TMG = TMG ? 0.08 (HR ? 72) ? 0.04 (SV ? 84) in women. In the validation cohort (n = 1,658), projected TMG had better agreement with MS severity than TMG (kappa 0.61 vs. 0.28). Among 281 patients with TMG ≥6 mm Hg, projected TMG ≥6 mm Hg, present in 171 patients (61%), was associated with higher probability of the endpoint versus projected TMG <6 mm Hg (adjusted hazard ratio: 1.8; 95% confidence interval: 1.2 to 2.6; p < 0.01).ConclusionsThe novel concept of projected TMG, constructed using the observed impact of HR and SV on TMG, significantly improved the concordance of gradient and valve area in MS and provided better risk stratification than TMG.     

A Boosted Ensemble Algorithm for Determination of Plaque Stability in High-Risk Patients on Coronary CTA

ObjectivesThis study sought to identify culprit lesion (CL) precursors among acute coronary syndrome (ACS) patients based on qualitative and quantitative computed tomography–based plaque characteristics.BackgroundCoronary computed tomography angiography (CTA) has been validated for patient-level prediction of ACS. However, the applicability of coronary CTA to CL assessment is not known.MethodsUtilizing the ICONIC (Incident COroNary Syndromes Identified by Computed Tomography) study, a nested case-control study of 468 patients with baseline coronary CTA, the study included ACS patients with invasive coronary angiography–adjudicated CLs that could be aligned to CL precursors on baseline coronary CTA. Separate blinded core laboratories adjudicated CLs and performed atherosclerotic plaque evaluation. Thereafter, the study used a boosted ensemble algorithm (XGBoost) to develop a predictive model of CLs. Data were randomly split into a training set (80%) and a test set (20%). The area under the receiver-operating characteristic curve of this model was compared with that of diameter stenosis (model 1), high-risk plaque features (model 2), and lesion-level features of CL precursors from the ICONIC study (model 3). Thereafter, the machine learning (ML) model was applied to 234 non-ACS patients with 864 lesions to determine model performance for CL exclusion.ResultsCL precursors were identified by both coronary angiography and baseline coronary CTA in 124 of 234 (53.0%) patients, with a total of 582 lesions (containing 124 CLs) included in the analysis. The ML model demonstrated significantly higher area under the receiver-operating characteristic curve for discriminating CL precursors (0.774; 95% confidence interval [CI]: 0.758 to 0.790) compared with model 1 (0.599; 95% CI: 0.599 to 0.599; p < 0.01), model 2 (0.532; 95% CI: 0.501 to 0.563; p < 0.01), and model 3 (0.672; 95% CI: 0.662 to 0.682; p < 0.01). When applied to the non-ACS cohort, the ML model had a specificity of 89.3% for excluding CLs.ConclusionsIn a high-risk cohort, a boosted ensemble algorithm can be used to predict CL from non-CL precursors on coronary CTA.     

Interpatient Similarities in Cardiac Function: A Platform for Personalized Cardiovascular Medicine

ObjectivesThe authors applied unsupervised machine-learning techniques for integrating echocardiographic features of left ventricular (LV) structure and function into a patient similarity network that predicted major adverse cardiac event(s) (MACE) in an individual patient.BackgroundPatient similarity analysis is an evolving paradigm for precision medicine in which patients are clustered or classified based on their similarities in several clinical features.MethodsA retrospective cohort of 866 patients was used to develop a network architecture using 9 echocardiographic features of LV structure and function. The data for 468 patients from 2 prospective cohort registries were then added to test the model’s generalizability.ResultsThe map of cross-sectional data in the retrospective cohort resulted in a looped patient network that persisted even after the addition of data from the prospective cohort registries. After subdividing the loop into 4 regions, patients in each region showed unique differences in LV function, with Kaplan-Meier curves demonstrating significant differences in MACE-related rehospitalization and death (both p < 0.001). Addition of network information to clinical risk predictors resulted in significant improvements in net reclassification, integrated discrimination, and median risk scores for predicting MACE (p < 0.05 for all). Furthermore, the network predicted the cardiac disease cycle in each of the 96 patients who had second echocardiographic evaluations. An improvement or remaining in low-risk regions was associated with lower MACE-related rehospitalization rates than worsening or remaining in high-risk regions (3% vs. 37%; p < 0.001).ConclusionsPatient similarity analysis integrates multiple features of cardiac function to develop a phenotypic network in which patients can be mapped to specific locations associated with specific disease stage and clinical outcomes. The use of patient similarity analysis may have relevance for automated staging of cardiac disease severity, personalized prediction of prognosis, and monitoring progression or response to therapies.     

A Network-Based “Phenomics” Approach for Discovering Patient Subtypes From High-Throughput Cardiac Imaging Data

ObjectivesThe authors present a method that focuses on cohort matching algorithms for performing patient-to-patient comparisons along multiple echocardiographic parameters for predicting meaningful patient subgroups.BackgroundRecent efforts in collecting multiomics data open numerous opportunities for comprehensive integration of highly heterogenous data to classify a patient's cardiovascular state, eventually leading to tailored therapies.MethodsA total of 42 echocardiography features, including 2-dimensional and Doppler measurements, left ventricular (LV) and atrial speckle-tracking, and vector flow mapping data, were obtained in 297 patients. A similarity network was developed to delineate distinct patient phenotypes, and then neural network models were trained for discriminating the phenotypic presentations.ResultsThe patient similarity model identified 4 clusters (I to IV), with patients in each cluster showed distinctive clinical presentations based on American College of Cardiology/American Heart Association heart failure stage and the occurrence of short-term major adverse cardiac and cerebrovascular events. Compared with other clusters, cluster IV had a higher prevalence of stage C or D heart failure (78%; p < 0.001), New York Heart Association functional classes III or IV (61%; p < 0.001), and a higher incidence of major adverse cardiac and cerebrovascular events (p < 0.001). The neural network model showed robust prediction of patient clusters, with area under the receiver-operating characteristic curve ranging from 0.82 to 0.99 for the independent hold-out validation set.ConclusionsAutomated computational methods for phenotyping can be an effective strategy to fuse multidimensional parameters of LV structure and function. It can identify distinct cardiac phenogroups in terms of clinical characteristics, cardiac structure and function, hemodynamics, and outcomes.     

ORMDL3/GSDMB genotype as a risk factor for early-onset adult asthma is linked to total serum IgE levels but not to allergic sensitization

BackgroundAn orosomucoid-like 3 (ORMDL3)/gasdermin B (GSDMB) gene locus on chromosome 17q is consistently associated with childhood-onset asthma, which is highly atopic. As some evidence suggests the relationship between asthma and allergic sensitization reflects asthma patient susceptibility to augmented IgE responses driven by common environmental allergens rather than an increased asthma risk after allergen exposure, we aimed to determine any relationships between this locus region and childhood-onset adult asthma with regard to serum total IgE levels or allergic sensitization.MethodsWe conducted a case–control association study using three independent Japanese populations (3869 total adults) and analyzed the ORs for association of rs7216389, an expression quantitative trait locus for ORMDL3/GSDMB, with adult asthma according to onset age. Additionally, associations between the rs7216389 genotype and total serum IgE levels or allergic sensitization was examined.ResultsRs7216389 was associated with both childhood-onset adult asthma (OR for asthmatic patients afflicted at the age of 10 years or younger = 1.61, p = 0.00021) and asthmatic patients with higher levels of total serum IgE (OR for asthmatic patients with IgE ≥1000IU/mL = 1.55, p = 0.0033). In both healthy controls and in the combined healthy and asthmatic individuals, rs7216389 was correlated with increased total serum IgE levels (p < 0.0005), but not allergic sensitization (p > 0.1).ConclusionsORMDL3/GSDMB is an important susceptibility gene for childhood-onset adult asthma in Japanese populations and this association is linked to elevated total serum IgE levels but not to allergic sensitization.     

Myocardial Flow Reserve and Coronary Calcification in Prognosis of Patients With Suspected Coronary Artery Disease

ObjectivesThe aim of this analysis is to examine the incremental prognostic value of coronary artery calcium (CAC) score and myocardial flow reserve (MFR) in patients with suspected coronary artery disease (CAD) undergoing positron emission tomography (PET) myocardial perfusion imaging (MPI).BackgroundAdvances in cardiac PET and computed tomography imaging enabled the simultaneous acquisition of anatomic and physiological data for patients suspected of CAD.MethodsConsecutive patients who underwent PET MPI and CAC score calculation at King Abdulaziz Cardiac Center, Riyadh, Saudi Arabia, between May 2011 and May 2018 were included in the study. MPI and CAC images were obtained in the same setting. The primary endpoint of the study was a composite of cardiac death and nonfatal myocardial infarction. Cox proportional hazard regression was used to assess the incremental prognostic value of CAC and MFR by sequentially adding the variables to a model that included clinical and PET variables.ResultsA total of 4,008 patients (mean age 59.7 ± 11.6 years, 55% women) were included in the analysis. Risk factors were prevalent (77.6% hypertension, 58.1% diabetes). In total, 35.9% of the cohort had CAC of 0, 16.5% had CAC ≥400, and 43.9% had MFR <2. Over a median follow up of 1.9 years, 130 (3.2%) patients had cardiac death/nonfatal myocardial infarction. CAC and MFR score added incremental prognostic value over clinical and perfusion variables (base model: c-index 0.8137; Akaike information criterion [AIC]: 1,865.877; p = 0.0011; CAC model: c-index = 0.8330; AIC: 1,850.810; p = 0.045 vs. base model; MFR model: c-index = 0.8279; AIC: 1,859.235; p = 0.024). Combining CAC and MFR did not enhance risk prediction (c-index = 0.8435; AIC: 1,846.334; p = 0.074 vs. MFR model; p = 0.21 vs. CAC model.)ConclusionsIn this large cohort of patients referred for PET MPI, both CAC and MFR independently added incremental prognostic value over clinical and MPI variables. Although combining both may have synergetic prognostic effect, this relation was not shown in multivariable model of this analysis.     

Right Atrial/Pulmonary Arterial Wedge Pressure Ratio in Primary and Mixed Constrictive Pericarditis

BackgroundCardiac filling pressures may be elevated due to abnormalities in the myocardium, heightened pericardial restraint, or both. The authors hypothesized that the relative contributions due to myocardium and pericardium could be estimated by the ratio between right atrial pressure and pulmonary arterial wedge pressure (RAP/PAWP), which would enable better discrimination of the extent of myocardial disease in patients with constrictive pericarditis (CP).ObjectivesThis study investigated the relationships between RAP/PAWP and the pericardial thickness as well as echocardiographic parameters of myocardial function and assessed the prognostic implications of RAP/PAWP for long-term mortality in primary and mixed CP patients who underwent pericardiectomy.MethodsA total of 113 surgically confirmed CP patients who underwent echocardiography and cardiac catheterization within 7 days of each other between 2005 and 2013 were included in the study. The patients were classified into a high RAP/PAWP group (≥0.77; n = 56) or a low RAP/PAWP group (<0.77; n = 57) according to the median RAP/PAWP value. The primary outcome was prognostic implication of RAP/PAWP on long-term mortality and assessment of the relationship between RAP/PAWP and Doppler echocardiographic parameters in primary and mixed CP. In addition, the relationship between RAP/PAWP and the pericardial thickness was assessed.ResultsRAP/PAWP was directly correlated with pericardial thickness (regression coefficient [β] = 8.34; p < 0.001). RAP/PAWP had a significant direct correlation with early diastolic velocity of medial mitral annulus (eʹ) (β = 10.69; p < 0.001) and inverse relationship with early transmitral diastolic velocity (E) (β = −105.15; p < 0.001), resulting in an inverse relationship with the ratio of E/eʹ (β = −23.53; p < 0.001). Patients with high RAP/PAWP ratio had a better survival rate compared with those with low RAP/PAWP ratio (p = 0.01). Its prognostic value was significant in primary CP (p = 0.03) but not in mixed CP with concomitant myocardial disease (p = 0.89).ConclusionsThe RAP/PAWP ratio can reflect the degree of pericardial restraint versus restrictive myocardium and was associated with the long-term survival after pericardiectomy.