Association between myocardial work indices and cardiovascular events according to hypertension in the general population.

AIMS: Pressure-strain loop (PSL) analysis is a novel echocardiographic tool capable of assessing myocardial work non-invasively. In this study, we aim to evaluate the prognostic value of myocardial work indices in the general population. METHODS AND RESULTS: This was a prospective community-based cohort study (n = 4466). PSL analyses were performed to acquire global work index (GWI), global constructive work (GCW), global wasted work, and global work efficiency (GWE). The endpoint was a composite of heart failure or cardiovascular death (HF/CVD). Survival analysis was applied. A total of 3932 participants were included in this analysis (median age: 58 years, 43% men). Of these, 124 (3%) experienced the outcome during a median follow-up period of 3.5 years [interquartile range (IQR): 2.6-4.4 years]. Hypertension significantly modified the association between all work indices and outcome (P for interaction < 0.05), such that work indices posed a higher risk of outcome in non-hypertensive than in hypertensive participants. After adjusting for Atherosclerosis Risk in Communities (ARIC)-HF risk variables, all work indices predicted outcome in non-hypertensive participants, but only GWI, GCW, and GWE predicted outcome in hypertensive participants [GWI: hazard ratio (HR) = 1.12 (1.07-1.16), per 100 mmHg% decrease; GCW: HR = 1.12 (1.08-1.17), per 100 mmHg% decrease; GWE: HR = 1.08 (1.04-1.12), per 1% decrease]. Only GWE significantly increased C-statistics when added to ARIC-HF risk variables in hypertensive participants (C-stat 0.865 vs. 0.877, P for increment = 0.003). CONCLUSION: Hypertension modifies the association between myocardial work indices and HF/CVD in the general population. All work indices are associated with outcome in normotensive participants. GWI, GCW, and GWE are independently associated with outcome in hypertension, but only GWE improves risk prediction.

Normal Values for Myocardial Work Indices Derived From Pressure-Strain Loop Analyses: From the CCHS.

BACKGROUND: Pressure-strain loop analyses is a noninvasive technique capable of evaluating myocardial work. Reference values are needed to benchmark these myocardial work indices for clinical practice. METHODS: Healthy participants from a general population study were used to establish reference values for global work index (GWI), global constructive work (GCW), global wasted work (GWW), and global work efficiency (GWE) measured by pressure-strain loop analyses. The relation to age and sex was examined. We furthermore examined the proportion of abnormal work indices according to low, intermediate, and high cardiovascular risk by the Framingham risk score. RESULTS: The healthy sample consisted of 1827 participants (median age, 45 years; 39% men). Lower reference values were GWI, 1576 mm Hg%; GCW, 1708 mm Hg%; and GWE, 93.0% and upper reference value for GWW was 159 mm Hg%. Women exhibited significantly higher GWI, GCW, and GWW and lower GWE. Sex significantly modified the association between all indices and age (P for interaction: 0.001 for GWI, 0.009 for GCW, 0.003 for GWW, and 0.009 for GWE). For men, only GCW increased with age, whereas the other indices did not change with age. For women, GCW increased linearly with increasing age, whereas GWI, GWW, and GWE changed in a curvilinear fashion with age such that GWI increased in younger participants, GWW increased in elderly, and GWE declined concordantly. Abnormalities in myocardial work indices became more frequent with increasing Framingham risk score category (abnormal GWI: 2% versus 4% versus 5%, P=0.001; abnormal GCW: 2% versus 3% versus 4%, P=0.006; abnormal GWW: 3% versus 6% versus 11%, P<0.001; abnormal GWE: 3% versus 4% versus 11%, P<0.001). CONCLUSIONS: Myocardial work indices differ between sexes and change with age in a sex-dependent manner. Accordingly, we established age- and sex-specific reference values from a general population sample. Abnormal work indices become more frequent with higher clinical risk. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT02993172.

Myocardial Work in Patients Hospitalized With COVID-19: Relation to Biomarkers, COVID-19 Severity, and All-Cause Mortality.

Background COVID-19 infection has been hypothesized to affect left ventricular function; however, the underlying mechanisms and the association to clinical outcome are not understood. The global work index (GWI) is a novel echocardiographic measure of systolic function that may offer insights on cardiac dysfunction in COVID-19. We hypothesized that GWI was associated with disease severity and all-cause death in patients with COVID-19. Methods and Results In a multicenter study of patients admitted with COVID-19 (n=305), 249 underwent pressure-strain loop analyses to quantify GWI at a median time of 4 days after admission. We examined the association of GWI to cardiac biomarkers (troponin and NT-proBNP [N-terminal pro-B-type natriuretic peptide]), disease severity (oxygen requirement and CRP [C-reactive protein]), and all-cause death. Patients with elevated troponin (n=71) exhibited significantly reduced GWI (1508 versus 1707 mm Hg%; P=0.018). A curvilinear association to NT-proBNP was observed, with increasing NT-proBNP once GWI decreased below 1446 mm Hg%. Moreover, GWI was significantly associated with a higher oxygen requirement (relative increase of 6% per 100-mm Hg% decrease). No association was observed with CRP. Of the 249 patients, 37 died during follow-up (median, 58 days). In multivariable Cox regression, GWI was associated with all-cause death (hazard ratio, 1.08 [95% CI, 1.01-1.15], per 100-mm Hg% decrease), but did not increase C-statistics when added to clinical parameters. Conclusions In patients admitted with COVID-19, our findings indicate that NT-proBNP and troponin may be associated with lower GWI, whereas CRP is not. GWI was independently associated with all-cause death, but did not provide prognostic information beyond readily available clinical parameters. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT04377035.

Automatic detection of valve events by epicardial accelerometer allows estimation of the left ventricular pressure trace and pressure-displacement loop area.

Measurements of the left ventricular (LV) pressure trace are rarely performed despite high clinical interest. We estimated the LV pressure trace for an individual heart by scaling the isovolumic, ejection and filling phases of a normalized, averaged LV pressure trace to the time-points of opening and closing of the aortic and mitral valves detected in the individual heart. We developed a signal processing algorithm that automatically detected the time-points of these valve events from the motion signal of a miniaturized accelerometer attached to the heart surface. Furthermore, the pressure trace was used in combination with measured displacement from the accelerometer to calculate the pressure-displacement loop area. The method was tested on data from 34 animals during different interventions. The accuracy of the accelerometer-detected valve events was very good with a median difference of 2 ms compared to valve events defined from hemodynamic reference recordings acquired simultaneously with the accelerometer. The average correlation coefficient between the estimated and measured LV pressure traces was r = 0.98. Finally, the LV pressure-displacement loop areas calculated using the estimated and measured pressure traces showed very good correlation (r = 0.98). Hence, the pressure-displacement loop area can be assessed solely from accelerometer recordings with very good accuracy.

Dynamic gravity compensation does not increase detection of myocardial ischemia in combined accelerometer and gyro sensor measurements.

Previous studies have shown that miniaturised accelerometers can be used to monitor cardiac function and automatically detect ischemic events. However, accelerometers cannot differentiate between acceleration due to motion and acceleration due to gravity. Gravity filtering is essential for accurate integration of acceleration to yield velocity and displacement. Heart motion is cyclic and mean acceleration over time is zero. Thus, static gravity filtering is performed by subtracting mean acceleration. However, the heart rotates during the cycle, the gravity component is therefore not constant, resulting in overestimation of motion by static filtering. Accurate motion can be calculated using dynamic gravity filtering by a combined gyro and accelerometer. In an animal model, we investigated whether increased accuracy using dynamic filtering, compared to using static filtering, would enhance the ability to detect ischemia. Additionally, we investigated how well the gyro alone could detect ischemia based on the heart's rotation. Dynamic filtering tended towards lower sensitivity and specificity, using receiver operating characteristics analysis, for ischemia-detection compared to static filtering (area under the curve (AUC): 0.83 vs 0.93, p = 0.125). The time-varying gravity component indirectly reflects the heart's rotation. Hence, static filtering has the advantage of indirectly including rotation, which alone demonstrated excellent sensitivity to ischemia (AUC = 0.98).