Myocardial steatosis and biventricular strain and strain rate imaging in patients with type 2 diabetes mellitus

Magnetic resonance spectroscopy can quantify myocardial triglyceride content in type 2 diabetic patients. Its relation to alterations in left (LV) and right (RV) ventricular myocardial functions is unknown. A total of 42 men with type 2 diabetes mellitus were recruited. Exclusion criteria included hemoglobin A(1c) >8.5, known cardiovascular disease, diabetes-related complications, or blood pressure >150/85 mm Hg. Myocardial ischemia was excluded by a negative dobutamine stress test. LV and RV volumes and ejection fraction were quantified by magnetic resonance imaging. LV global longitudinal and RV free wall longitudinal strain, systolic strain rate, and diastolic strain rate were quantified by echocardiographic speckle tracking analyses. Myocardial triglyceride content was quantified by magnetic resonance spectroscopy and dichotomized on the basis of the median value of 0.76. The median age was 59 years (25th and 75th percentiles, 54 and 62 years). Median diabetes diagnosis duration was 4 years, and median glycohemoglobin level was 6.2 (25th and 75th percentiles, 5.9 and 6.8). There were no differences in LV and RV end-diastolic and end-systolic volume indexes and ejection fraction between patients with high (≥0.76) and those with low ( <0.76) myocardial triglyceride content. However, patients with high myocardial triglyceride content had greater impairment of LV and RV myocardial strain and strain rate. The myocardial triglyceride content was an independent correlate of LV and RV longitudinal strain, systolic strain rate, and diastolic strain rate. High myocardial triglyceride content is associated with more pronounced impairment of LV and RV functions in men with uncomplicated type 2 diabetes mellitu

Effect of biventricular pacing on diastolic dyssynchrony

ObjectivesThis study sought to examine the changes in diastolic dyssynchrony with cardiac resynchronization therapy (CRT).BackgroundLittle is known about the effect of CRT on diastolic dyssynchrony.MethodsConsecutive heart failure patients (n = 266, age 65.7 ± 10.0 years) underwent color-coded tissue Doppler imaging at baseline, 48 h, and 6 months after CRT. Systolic and diastolic dyssynchrony were defined as maximal time delay in peak systolic and early diastolic velocities, respectively, in 4 basal LV segments. CRT responders were defined as those with ≥15% decrease in LV end-systolic volume at 6 months.ResultsBaseline LVEF was 25.2 ± 8.1%; 63.5% patients were CRT responders. Baseline incidence of systolic and diastolic dyssynchrony, and a combination of both was 46.2%, 51.9%, and 28.6%, respectively. Compared to nonresponders, responders had longer baseline systolic (79.2 ± 43.4 ms vs. 45.4 ± 30.4 ms; p < 0.001) and diastolic (78.5 ± 52.0 ms vs. 50.1 ± 38.2 ms; p < 0.001) delays. In follow-up, systolic delays (45.4 ± 31.6 ms at 48 h; 38.9 ± 26.2 ms at 6 months; p < 0.001) and diastolic delays (49.4 ± 36.3 ms at 48 h; 37.7 ± 26.0 ms at 6 months; p < 0.001) improved only in responders.ConclusionsAt baseline: 1) diastolic dyssynchrony was more common than systolic dyssynchrony in HF patients; 2) nonresponders had less baseline diastolic dyssynchrony compared to responders. After CRT: 1) diastolic dyssynchrony improved only in responders. Further insight into the pathophysiology of diastolic dyssynchrony and its changes with CRT may provide incremental information on patient-specific treatments

Alterations in multidirectional myocardial functions in patients with aortic stenosis and preserved ejection fraction: A two-dimensional speckle tracking analysis

AimsTo identify changes in multidirectional strain and strain rate (SR) in patients with aortic stenosis (AS).Methods and resultsA total of 420 patients (age 66.1 ± 14.5 years, 60.7 men) with aortic sclerosis, mild, moderate, and severe AS with preserved left ventricular (LV) ejection fraction [(EF)

Risk of COVID-19 after natural infection or vaccinationResearch in context

Summary: Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health

Risk of COVID-19 after natural infection or vaccinationResearch in context

Background: While vaccines have established utility against COVID-19, phase 3 efficacy studies have generally not comprehensively evaluated protection provided by previous infection or hybrid immunity (previous infection plus vaccination). Individual patient data from US government-supported harmonized vaccine trials provide an unprecedented sample population to address this issue. We characterized the protective efficacy of previous SARS-CoV-2 infection and hybrid immunity against COVID-19 early in the pandemic over three-to six-month follow-up and compared with vaccine-associated protection. Methods: In this post-hoc cross-protocol analysis of the Moderna, AstraZeneca, Janssen, and Novavax COVID-19 vaccine clinical trials, we allocated participants into four groups based on previous-infection status at enrolment and treatment: no previous infection/placebo; previous infection/placebo; no previous infection/vaccine; and previous infection/vaccine. The main outcome was RT-PCR-confirmed COVID-19 >7–15 days (per original protocols) after final study injection. We calculated crude and adjusted efficacy measures. Findings: Previous infection/placebo participants had a 92% decreased risk of future COVID-19 compared to no previous infection/placebo participants (overall hazard ratio [HR] ratio: 0.08; 95% CI: 0.05–0.13). Among single-dose Janssen participants, hybrid immunity conferred greater protection than vaccine alone (HR: 0.03; 95% CI: 0.01–0.10). Too few infections were observed to draw statistical inferences comparing hybrid immunity to vaccine alone for other trials. Vaccination, previous infection, and hybrid immunity all provided near-complete protection against severe disease. Interpretation: Previous infection, any hybrid immunity, and two-dose vaccination all provided substantial protection against symptomatic and severe COVID-19 through the early Delta period. Thus, as a surrogate for natural infection, vaccination remains the safest approach to protection. Funding: National Institutes of Health