The Patterns and Impact of Social Media Exposure of Journal Publications in Gastroenterology: Retrospective Cohort Study.

BACKGROUND: Medical journals increasingly promote published content through social media platforms such as Twitter. However, gastroenterology journals still rank below average in social media engagement. OBJECTIVE: We aimed to determine the engagement patterns of publications in gastroenterology journals on Twitter and evaluate the impact of tweets on citations. METHODS: This was a retrospective cohort study comparing the 3-year citations of all full-length articles published in five major gastroenterology journals from January 1, 2012, to December 31, 2012, tweeted by official journal accounts with those that were not. Multivariate analysis using linear regression was performed to control for journal impact factor, time since publication, article type, frequency of reposting by other users ("retweets"), and media addition to tweets. Secondary analyses were performed to assess the associations between article type or subtopic and the likelihood of social media promotion/engagement. RESULTS: A total of 1666 articles were reviewed, with 477 tweeted by the official journal account. Tweeting an article independently predicted increased citations after controlling for potential confounders (ß coefficient=13.09; P=.007). There was significant association between article type and number of retweets on analysis of variance (ANOVA) (P<.001), with guidelines/technical reviews (mean difference 1.04, 95% CI 0.22-1.87; P<.001) and meta-analyses/systemic reviews (mean difference 1.03, 95% CI 0.35-1.70; P<.001) being retweeted more than basic science articles. The manuscript subtopics most frequently promoted included motility/functional bowel disease (odds ratio [OR] 3.84, 95% CI 1.93-7.64; P<.001) and education (OR 4.69, 95% CI 1.62-13.58; P=.004), while basic science papers were less likely tweeted (OR 0.154, 95% CI 0.07-0.34; P<.001). CONCLUSIONS: Tweeting of gastroenterology journal articles independently predicted higher 3-year citations. Wider adoption of social media to increase reach and measure uptake of published research should be considered.

Associations between the size and location of myocardial infarction and cerebral infarction.

BACKGROUND: Myocardial infarction (MI) is a known cause of cerebral infarction. We assessed whether the size and location of MI is associated with the risk of cerebral infarction. METHODS AND RESULTS: We performed a cross-sectional study of adults who underwent both brain MRI and delayed-enhancement cardiac MRI (DE-CMR) within 365 days of each other at Weill Cornell Medicine between 2014 and 2017 and had evidence of MI on DE-CMR. We used multiple logistic regression to evaluate associations between MI size and any cerebral infarction, apical MI location and any cerebral infarction, and MI size/location and cortical versus subcortical cerebral infarction. Models were adjusted for demographics, and the total number of vascular risk factors. Among 234 patients who underwent both DE-CMR and brain MRI within 365 days, 76 had evidence for MI on DE-CMR. Among these 76 patients, 51 (67.1%) had evidence of cerebral infarction. The size of MI (global MI burden) was not associated with any cerebral infarction (OR per 5% increase in MI size, 1.12; 95% CI, 0.85-1.47), but was associated with cortical cerebral infarction (OR per 5% increase in MI size, 1.30; 95% CI, 1.00.-1.68). Similarly, apical MI location was not associated with any cerebral infarction (OR 2.63, 95% CI, 0.78-8.87), but was associated with cortical cerebral infarction (OR, 3.67; 95% CI, 1.19-11.33). CONCLUSION: Among patients with MI on cardiac MRI, both size and apical location of MI were associated with cortical cerebral infarction. Our results may help stratify cardioembolic risk and inform antithrombotic treatment algorithms among patients with MI.

Left ventricular geometry predicts optimal response to percutaneous mitral repair via MitraClip: Integrated assessment by two- and three-dimensional echocardiography.

OBJECTIVES: To assess impact of left ventricular (LV) chamber remodeling on MitraClip (MClp) response. BACKGROUND: MitraClip is the sole percutaneous therapy approved for mitral regurgitation (MR) but response varies. LV dilation affects mitral coaptation; determinants of MClp response are uncertain. METHODS: LV and mitral geometry were quantified on pre- and post-procedure two-dimensional (2D) transthoracic echocardiography (TTE) and intra-procedural three-dimensional (3D) transesophageal echocardiography (TEE). Optimal MClp response was defined as ≤mild MR at early (1-6 month) follow-up. RESULTS: Sixty-seven degenerative MR patients underwent MClp: Whereas MR decreased ≥1 grade in 94%, 39% of patients had optimal response (≤mild MR). Responders had smaller pre-procedural LV end-diastolic volume (94 ± 24 vs. 109 ± 25 mL/m2 , p = 0.02), paralleling smaller annular diameter (3.1 ± 0.4 vs. 3.5 ± 0.5 cm, p = 0.002), and inter-papillary distance (2.2 ± 0.7 vs. 2.5 ± 0.6 cm, p = 0.04). 3D TEE-derived annular area correlated with 2D TTE (r = 0.59, p < 0.001) and was smaller among optimal responders (12.8 ± 2.1 cm2 vs. 16.8 ± 4.4 cm2 , p = 0.001). Both 2D and 3D mitral annular size yielded good diagnostic performance for optimal MClp response (AUC 0.73-0.84, p < 0.01). In multivariate analysis, sub-optimal MClp response was associated with LV end-diastolic diameter (OR 3.10 per-cm [1.26-7.62], p = 0.01) independent of LA size (1.10 per-cm2 [1.02-1.19], p = 0.01); substitution of mitral annular diameter for LV size yielded an independent association with MClp response (4.06 per-cm2 [1.03-15.96], p = 0.045). CONCLUSIONS: Among degenerative MR patients undergoing MClp, LV and mitral annular dilation augment risk for residual or recurrent MR, supporting the concept that MClp therapeutic response is linked to sub-valvular remodeling.

Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.

BACKGROUND: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is widely employed for flow quantification, but analysis typically requires time consuming manual segmentation which can require human correction. Advances in machine learning have markedly improved automated processing, but have yet to be applied to PC-CMR. This study tested a novel machine learning model for fully automated analysis of PC-CMR aortic flow. METHODS: A machine learning model was designed to track aortic valve borders based on neural network approaches. The model was trained in a derivation cohort encompassing 150 patients who underwent clinical PC-CMR then compared to manual and commercially-available automated segmentation in a prospective validation cohort. Further validation testing was performed in an external cohort acquired from a different site/CMR vendor. RESULTS: Among 190 coronary artery disease patients prospectively undergoing CMR on commercial scanners (84% 1.5T, 16% 3T), machine learning segmentation was uniformly successful, requiring no human intervention: Segmentation time was < 0.01 min/case (1.2 min for entire dataset); manual segmentation required 3.96 ± 0.36 min/case (12.5 h for entire dataset). Correlations between machine learning and manual segmentation-derived flow approached unity (r = 0.99, p < 0.001). Machine learning yielded smaller absolute differences with manual segmentation than did commercial automation (1.85 ± 1.80 vs. 3.33 ± 3.18 mL, p < 0.01): Nearly all (98%) of cases differed by ≤5 mL between machine learning and manual methods. Among patients without advanced mitral regurgitation, machine learning correlated well (r = 0.63, p < 0.001) and yielded small differences with cine-CMR stroke volume (∆ 1.3 ± 17.7 mL, p = 0.36). Among advanced mitral regurgitation patients, machine learning yielded lower stroke volume than did volumetric cine-CMR (∆ 12.6 ± 20.9 mL, p = 0.005), further supporting validity of this method. Among the external validation cohort (n = 80) acquired using a different CMR vendor, the algorithm yielded equivalently small differences (∆ 1.39 ± 1.77 mL, p = 0.4) and high correlations (r = 0.99, p < 0.001) with manual segmentation, including similar results in 20 patients with bicuspid or stenotic aortic valve pathology (∆ 1.71 ± 2.25 mL, p = 0.25). CONCLUSION: Fully automated machine learning PC-CMR segmentation performs robustly for aortic flow quantification - yielding rapid segmentation, small differences with manual segmentation, and identification of differential forward/left ventricular volumetric stroke volume in context of concomitant mitral regurgitation. Findings support use of machine learning for analysis of large scale CMR datasets.

Short-Term Risk of Ischemic Stroke After Detection of Left Ventricular Thrombus on Cardiac Magnetic Resonance Imaging.

BACKGROUND: The short-term risk of ischemic stroke in patients with left ventricular (LV) thrombus identified via delayed-enhancement cardiac magnetic resonance (DE-CMR) imaging is uncertain. METHODS: We performed a retrospective cohort study of patients who underwent DE-CMR for evaluation of LV systolic dysfunction at NewYork-Presbyterian Hospital/Weill Cornell between 2007 and 2016. We identified all hospitalized patients who had DE-CMR evidence of LV thrombus, and as controls, all hospitalized patients who had no DE-CMR evidence of LV thrombus; 2 control patients were randomly selected for each patient with LV thrombus. Our primary outcome was ischemic stroke prior to hospital discharge. Additionally, we compared the risk of stroke among patients with: (1) no LV thrombus, (2) LV thrombus by DE-CMR but not by echocardiography, and (3) LV thrombus by both DE-CMR and echocardiography. RESULTS: We identified 33 patients with LV thrombus and 66 patients without LV thrombus on DE-CMR. Of the 33 patients with LV thrombus on DE-CMR, 13 had echocardiographic evidence of thrombus. Ischemic stroke occurred in 3 of 33 (9.1%; 95% CI, 1.9%-24.3%) patients with LV thrombus on DE-CMR. Ischemic stroke occurred in 0 of 66 (0%; 95% CI, 0%-5.4%) patients without LV thrombus on DE-CMR, 1 of 20 (5.0%; 95% CI, .1%-24.9%) patients with thrombus on DE-CMR but not echocardiogram, and 2 of 13 (15.4%; 95% CI, 1.9%-45.4%) patients with thrombus on both DE-CMR and echocardiogram (P value for comparison among groups, .02). CONCLUSIONS: We found a 9% short-term risk of ischemic stroke in patients with LV thrombus detected on DE-CMR.

Tissue-based markers of right ventricular dysfunction in ischemic mitral regurgitation assessed via stress cardiac magnetic resonance and three-dimensional echocardiography.

Ischemic mitral regurgitation (iMR) augments risk for right ventricular dysfunction (RVDYS). Right and left ventricular (LV) function are linked via common coronary perfusion, but data is lacking regarding impact of LV ischemia and infarct transmurality-as well as altered preload and afterload-on RV performance. In this prospective multimodality imaging study, stress CMR and 3-dimensional echo (3D-echo) were performed concomitantly in patients with iMR. CMR provided a reference for RVDYS (RVEF < 50%), as well as LV function/remodeling, ischemia and infarction. Echo was used to test multiple RV performance indices, including linear (TAPSE, S'), strain (GLS), and volumetric (3D-echo) approaches. 90 iMR patients were studied; 32% had RVDYS. RVDYS patients had greater iMR, lower LVEF, larger global ischemic burden and inferior infarct size (all p < 0.05). Regarding injury pattern, RVDYS was associated with LV inferior ischemia and infarction (both p < 0.05); 80% of affected patients had substantial viable myocardium (< 50% infarct thickness) in ischemic inferior segments. Regarding RV function, CMR RVEF similarly correlated with 3D-echo and GLS (r = 0.81-0.87): GLS yielded high overall performance for CMR-evidenced RVDYS (AUC: 0.94), nearly equivalent to that of 3D-echo (AUC: 0.95). In multivariable regression, GLS was independently associated with RV volumetric dilation on CMR (OR - 0.90 [CI - 1.19 to - 0.61], p < 0.001) and 3D echo (OR - 0.43 [CI - 0.84 to - 0.02], p = 0.04). Among patients with iMR, RVDYS is associated with potentially reversible processes, including LV inferior ischemic but predominantly viable myocardium and strongly impacted by volumetric loading conditions.

Utility of cardiac magnetic resonance for evaluation of mitral regurgitation prior to mitral valve surgery.

Mitral regurgitation (MR) is a common cause of morbidity worldwide and an accepted indication for interventional therapies which aim to reduce or resolve adverse clinical outcomes associated with MR. Cardiac magnetic resonance (CMR) provides highly accurate means of assessing MR, including a variety of approaches that can measure MR based on quantitative flow. Additionally, CMR is widely accepted as a reference standard for cardiac chamber quantification, enabling reliable detection of subtle changes in cardiac chamber size and function so as to guide decision-making regarding timing of mitral valve directed therapies. Beyond geometric imaging, CMR enables tissue characterization of ischemia and infarction in the left ventricular (LV) myocardium as well as within the mitral valve apparatus, thus enabling identification of structural substrates for MR. This review provides an overview of established and emerging CMR approaches to measure valvular regurgitation, including relative utility of different approaches for patients with primary or secondary MR. Clinical outcomes studies are discussed with focus on data demonstrating advantages of CMR for guiding diagnosis, risk stratification, and management of patients with known or suspected MR. Comparative data is reviewed with focus on diagnostic performance of CMR in comparison to conventional assessment via echocardiography (echo). Emerging literature is reviewed concerning potential new approaches that utilize CMR tissue characterization to guide clinical decision-making in order to improve therapeutic outcomes and clinical prognosis for patients with MR.

Echocardiographic linear fractional shortening for quantification of right ventricular systolic function-A cardiac magnetic resonance validation study.

BACKGROUND: Echocardiography (echo)-based linear fractional shortening (FS) is widely used to assess left ventricular dysfunction (LVdys ), but has not been systematically tested for right ventricular dysfunction (RVdys ). METHODS: The population comprised LVdys patients with and without RVdys (EF<50%) on cardiac MRI (CMR): Echo included standard RV indices (fractional area change [FAC], TAPSE, S', and FS in parasternal long-axis (RV outflow tract [RVOT ]) and apical four-chamber views (width [RVWD ], length [RVLG ]). RESULTS: A total of 168 patients underwent echo and CMR (3±3 days); FAC (46±9 vs 28±11), TAPSE (1.9±0.4 vs 1.5±0.3), and S' (11.4±2.3 vs 10.0±2.6, all P≤.001) were lower among RVdys patients, as were FS indices (RVOT 32±8 vs 17±10 | RVWD 40±11 vs 22±12 | RVLG 16±5 vs 9±4%; all P<.001). FS indices yielded similar magnitude of correlation with CMR RVEF (r=.73-.56) as did FAC (r=.70), which was slightly higher than TAPSE (r=.47) and S' (r=.31; all P<.001). FS indices decreased stepwise vs CMR RVEF tertiles, as did FAC (all P<.001). In multivariate analysis, FS in RVOT (regression coefficient .51 [CI 0.37-0.65]), RVWD (0.30 [0.19-0.41]), and RVLG (0.45 [0.20-0.71]; all P≤.001) was independently associated with CMR RVEF. FS indices yielded good overall diagnostic performance (AUC: RVOT 0.89 [CI 0.82-0.97] | RVWD 0.87 [0.78-0.96] | RVLG 0.80 [0.70-0.90]; all P<.001) for CMR-defined RVdy (RVEF<50%). CONCLUSIONS: RV linear FS provides RV functional indices that parallel CMR RVEF. Parasternal long-axis RVOT width, four-chamber RV width, and length are independently associated with RVEF, supporting use of multiple FS indices for RV functional assessment.

Native T1 value in the remote myocardium is independently associated with left ventricular dysfunction in patients with prior myocardial infarction.

PURPOSE: To compare remote myocardium native T1 in patients with chronic myocardial infarction (MI) and controls without MI and to elucidate the relationship of infarct size and native T1 in the remote myocardium for the prediction of left ventricular (LV) systolic dysfunction after MI. MATERIALS AND METHODS: A total of 41 chronic MI (18 anterior MI) patients and 15 age-matched volunteers with normal LV systolic function and no history of MI underwent cardiac magnetic resonance imaging (MRI) at 1.5T. Native T1 map was performed using a slice interleaved T1 mapping and late gadolinium enhancement (LGE) imaging. Cine MR was acquired to assess LV function and mass. RESULTS: The remote myocardium native T1 time was significantly elevated in patients with prior MI, compared to controls, for both anterior MI and nonanterior MI (anterior MI: 1099 ± 30, nonanterior MI: 1097 ± 39, controls: 1068 ± 25 msec, P < 0.05). Remote myocardium native T1 moderately correlated with LV volume, mass index, and ejection fraction (r = 0.38, 0.50, -0.49, respectively, all P < 0.05). LGE infarct size had a moderate correlation with reduced LV ejection fraction (r = -0.33, P < 0.05), but there was no significant association between native T1 and infarct size. Native T1 time in the remote myocardium was independently associated with reduced LV ejection fraction, after adjusting for age, gender, infarct size, and comorbidity (ß = -0.34, P = 0.03). CONCLUSION: In chronic MI, the severity of LV systolic dysfunction after MI is independently associated with native T1 in the remote myocardium. Diffuse myocardial fibrosis in the remote myocardium may play an important pathophysiological role of post-MI LV dysfunction. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1073-1081.