Differential role of central and peripheral arterial stiffness in determining brachial artery resting retrograde flow in patients with ischemic heart disease vs healthy subjects

Retrograde flow in endothelial cell cultures has been shown to induce a pro-atherogenic phenotype. Despite its potential role as a pathophysiological link between cardiovascular risk factors and atherosclerotic disease, resting retrograde flows between patients with cardiovascular disease and healthy subjects have not been compared. Further, the vascular characteristics governing retrograde flow in human arteries have not been systematically investigated. Association of central and peripheral vascular characteristics with retrograde flow profile was investigated in 32 healthy subjects and 47 patients with ischemic heart disease. Endothelial dysfunction was assessed by brachial ultrasound-based calculation of flow-mediated dilation (FMD) and sub-clinical atherosclerosis was estimated from carotid-intima media thickness (CIMT). Retrograde blood flow velocity (RBFV) and shear rate were comparable between the two groups (RBFV 1.82(0.97–3.32) vs 1.78(1.24–2.65) cm/s p  =  0.79). Augmentation index was a significant determinant of retrograde flow in both patients and healthy subjects. Carotid artery incremental elastic modulus was an independent determinant of retrograde flow patterns in healthy subjects while ejection fraction, cf/cr PWV ratio and forearm vascular conductance emerged as independent determinants in patients. Retrograde flow patterns were also associated with FMD (RBFV r  =  −0.43, p  =  0.004) and CIMT (r  =  0.30, p  =  0.041) in patients. The results of the study suggest a difference in the determinants of retrograde flow in patients and healthy subjects, with central arterial stiffness being a major contributor in healthy subjects while interaction between central, peripheral, and cardio-arterial factors influence retrograde flow in patients with ischemic heart disease.


INTRODUCTION
Arterial flow patterns are known to affect the endothelium. In endothelial cell cultures, higher flow in the anterograde direction has shown to be anti-atherogenic, while increased retrograde flow has a pro-atherogenic effect [1]. An increase in oscillatory flow patterns has also been reported to lead to endothelial dysfunction [1][2][3][4]. Areas with a low and oscillatory flow are believed to be associated with the development of atherosclerotic plaques [5]. Carotid artery wall shear stress correlated with an ultrasound-based estimation of carotid atherosclerosis in hypertensive patients [6]. It is well established that endothelial dysfunction precedes the development of atherosclerotic plaque, which is a leading cause of ischemic heart disease.
Interestingly, while atherosclerotic plaques are not common in the peripheral conduit arteries, endothelial dysfunction in the coronary arteries is accompanied by a concurrent endothelial dysfunction in the peripheral conduit arteries [7]. An increase in brachial artery retrograde flow has been reported with ageing [8]. Further, resting retrograde flow patterns in the brachial artery were associated with endothelial dysfunction, as assessed by flowmediated dilation, in a mixed population of Framingham study offspring and third-generation cohorts [9]. Despite its potential role as a pathophysiological link between cardiovascular risk factors and atherosclerotic disease, there is no data comparing brachial artery retrograde flow in human subjects with and without cardiovascular disease. Additionally, the endothelial mechanoreceptors respond to changes in shear stress, which is a function of blood viscosity and flow. While oscillatory shear stress has been reported to upregulate ET-1 and downregulate e-NOS expression in cultured endothelial cells, which suggests endothelial dysfunction, an in vitro environment cannot completely replicate the effect of the in vivo environment and the chronic alterations in vascular structure and function [1]. To the best of our knowledge, the association between retrograde shear stress and endothelial dysfunction or atherosclerotic changes in human subjects has not been described.
A few studies have reported that an increase in peripheral resistance and regional arterial stiffness is associated with retrograde flow [8,9]. An increase in peripheral vascular tone due to sympathetic activation has been reported to partially mediate the increase in retrograde flow due to ageing [10]. However, the flow direction would be determined by the pressure gradient between the proximal and distal points in the vessel. It is hypothesised that both central and peripheral vascular characteristics would influence the retrograde flow at the brachial artery. To the best of our knowledge, no study has evaluated the relationship between local alterations in the central vasculature, i.e. the proximal point, and peripheral vasculature, i.e. the distal end, on retrograde flow patterns.
The current study aimed to compare resting retrograde flow patterns in the brachial artery in patients with ischemic heart disease with that in healthy subjects and further evaluate the central and peripheral vascular factors associated with resting retrograde flow in human subjects. Furthermore, the association of resting retrograde flow with endothelial dysfunction and subclinical atherosclerosis was also evaluated.

METHODS
Thirty-two healthy subjects (20 male) and 47 stable patients (37 male) clinically diagnosed with IHD were recruited for the study. Patients with at least 2 of the following features (i) clinical symptoms suggestive of ischemic heart disease (ii) hospitalisation with records showing dynamic ECG of ST-elevation, ST-depression or abnormal Q wave (iii) elevation of cardiac biomarkers were recruited for the study. A single experienced cardiologist diagnosed patients at the Department of Cardiology, AIIMS. Patients on medications affecting vascular function were asked to withhold the same for 24 h before vascular assessment. All healthy subjects were non-hypertensive (<140/90 mmHg), non-diabetic (fasting blood sugar <126 mg/dL), non-smokers with no known history of any chronic cardiovascular or renal disease or on any medications affecting vascular function and with a normal resting 12-lead ECG. Subjects with any recent infection were excluded from the study.
Disease severity was assessed by gated myocardial perfusion imaging using exercise Technitium-99 Single Positron Emission Computed Tomography (Tc 99 -SPECT). Ejection fraction was reported in addition to a localisation of the perfusion defects using a 20-segment heart model. Both rest and exercise stress images were acquired. Defect size and severity were considered in each of the 20 segments on the stress and rest images. The stress and rest images were scored from 0 to 4, with 0 being normal, 1-mild, 2-moderate, 3-severe and 4-absent radiotracer uptake. The summed stress score(SSS) was calculated as the sum of the stress scores of all the segments. The % perfusion defect was calculated using the formula: The institute ethics committee approved the study for research on human subjects, and the investigations conformed to the Declaration of Helsinki. Before starting the study, written, informed consent was obtained from all patients and subjects. All investigations were performed between 8:00-10:00 am, and subjects were instructed to report in the morning after overnight fasting. All subjects were also required to refrain from caffeinated beverages and heavy exercise a day before the study. A fasting blood sample was taken to estimate total protein and hematocrit at the end of the vascular investigations.

Brachial artery diameter and blood flow measurement
Pulsed wave doppler ultrasound was used to image the brachial artery using a 10 MHz linear array probe (M7 MindRay Medical International Ltd., Shenzen, China). Duplex mode was used to simultaneously record the brachial artery diameter and blood flow velocity waveform with the insonation angle at 60°.
Longitudinal images of the brachial artery were acquired 2-3cms above the anti-cubital fossa. Simultaneous Lead-2 ECG was acquired for R-wave gating of the diameter. Video loops of at least 8-10 consecutive cardiac cycles were recorded and saved for offline analysis using automated edge detection and flow analysis software (Medical Imaging Applications LLC, Brachial Diameter and Flow Analyzer module) for brachial artery diameter and blood flow velocity analysis, respectively.
Brachial artery diameter was obtained by extracting the end-diastolic diameter from the beat-to-beat diameter waveform. For flow analysis, time-averaged mean anterograde and retrograde blood flow velocity (RBFV AUC ) were calculated separately using the area under the curve of the anterograde and retrograde flow waveform, respectively. Additionally, the maximum value of retrograde blood flow velocity for each cardiac cycle was calculated from the trough of the flow velocity waveform for each cycle and used to determine the maximum RBFV max (Fig. 1a). All values were calculated for 8-10 consecutive cardiac cycles and then averaged to obtain the baseline diameter and flow velocity.
Anterograde and Retrograde shear rates were calculated using the following formula: where ABFV AUC and RBFV AUC were used to calculate the respective anterograde and retrograde shear rates.
Oscillatory shear index (OSI) was calculated from the shear rates using the formula: where ASR is the anterograde shear rate, and RSR is the retrograde shear rate For calculation of retrograde shear stress (RSS), the viscosity of blood was estimated using the following validated formula [11]: where HCT is hematocrit expressed in percentage and TP is total protein in g/L. Maximum and time-averaged mean shear stress was calculated using both the formulae using the following formula:

RSS ¼ 4 Viscosity Retrograde blood flow velocity=Radius
where RSS is retrograde shear stress, and the time-averaged mean retrograde blood flow velocity and maximum were used for the respective calculations of RSS AUC and RSS max .

Central arterial stiffness
Central arterial stiffness was measured for both the local and the regional central arterial segments.
Local arterial stiffness. The common carotid artery was imaged using B-mode ultrasound with a 10 MHz linear array probe (MindRay, M7). Video loops of a straight segment of the carotid artery away from the bifurcation were recorded for at-least 4-5 consecutive cardiac cycles which were analyzed offline to measure the systolic and diastolic carotid artery diameter during a cardiac cycle (Fig. 1b). Offline analysis for automated calculation of carotid artery distensibility, compliance, and Incremental Elastic Modulus (IEM) was performed using a validated software (Carotid Analyser Module, Medical Imaging Applications LLC, Coralville, Iowa, USA). Systolic and diastolic central pressures were entered into the software for calculation of compliance and IEM.
For measurement of central pressures, an applanation tonometer was placed at the best palpable point of the radial artery to obtain at-least 10 reproducible cycles of radial artery waveform. Central pressures were derived from the radial artery pressure waveform using a validated transfer function analysis (Sphygmocor ® , Atcor Medical, Sydney, Australia) [12].
Regional arterial stiffness. For estimation of regional arterial stiffness of the central arterial segment, the Pulse Wave Velocity (PWV) of the carotidfemoral(cf) arterial segment was measured using applanation tonometry (Sphygmocor ® ). The applanation tonometer was used to sequentially record the pressure waveform from the carotid and the femoral artery to obtain at-least 10 consecutive reproducible cycles. Distance to the arteries was measured from the suprasternal notch to the best palpable point for the arteries. The distance to the femoral artery was measured by first measuring the distance from the suprasternal notch to the umbilicus and then from the umbilicus to the best palpable point of the femoral artery.
Simultaneous recording of Lead II ECG was done to provide an R-wave gated reference point to time the arrival of the pressure waveform. PWV was obtained from the software by automated calculation using the time elapsed between the onset of the wave at the proximal (carotid) site and the distal (femoral) site. The test was repeated twice for accuracy and the average of the two values was used as a measure of the cf-PWV.

Peripheral arterial stiffness
For peripheral arterial stiffness, PWV of the carotid-radial (cr) arterial segment was measured using applanation tonometry. The same method was used for central regional arterial stiffness by sequentially recording the pressure waveform from the carotid and the radial artery. Distance to the radial artery was measured by first abducting the arm at an angle of 90°, parallel to the floor and then measuring the distance from the suprasternal notch to the best palpable point of the radial artery. An average of two recordings was used as a measure of the cr-PWV.

Forearm vascular conductance
Forearm vascular conductance (FVC) was calculated from the mean arterial pressure and time-averaged mean blood flow (in cm/min) of the brachial artery. Mean arterial pressure (MAP) was derived from the peripheral systolic and diastolic pressures. Forearm vascular conductance was then calculated using the formula: where r is the radius of the brachial artery. The multiplication factor of 60 was used to covert blood flow velocity in cm/s to cm/min

Composite assessment of central and peripheral arterial stiffness
Augmentation index. Additionally, the Augmentation Index was measured as a composite measure of central arterial stiffness and the effect of peripheral wave reflections at the aorta. The same applanation tonometer was placed at the radial artery and aortic Augmentation Index (AI x ) was obtained using a validated transfer function. The amount of augmentation of the aortic pressure waveform was corrected for heart rate and calculated for a heart rate of 75bpm (AI x @75).
Pulse pressure amplification. Change in the pressure waveform from the central elastic to the peripheral muscular arteries results in pulse pressure amplification. Carotid to brachial pulse pressure amplification provides the elastic gradient from the central to the peripheral artery and was quantified as the ratio between the aortic to the peripheral pulse pressure.

Pulse pressure amplification ¼ Brachial Pulse Pressure Aortic Pulse Pressure
Central-to-peripheral elastic gradient. The elastic gradient from the central to the peripheral arteries was calculated as the ratio of carotid-femoral to carotid-radial pulse wave velocity (cf/cr PWV).
The following investigations were done for assessment of endothelial function and sub-clinical atherosclerosis

Endothelial function assessment
Brachial artery endothelium function was assessed using Flow Mediated Dilation (FMD). A blood pressure cuff was placed below the right elbow and the brachial artery was visualized in color flow mode by using a 10 MHz microarray probe. Baseline records were made in 2-dimensional Bmode for 1 min after which baseline brachial artery blood flow was recorded in Pulsed-wave(PW) doppler in duplex mode for simultaneous assessment of diameter and blood flow with an insonation angle of 60°. After collection of the baseline data, reactive hyperemia protocol of occluding the right brachial artery blood flow by rapid inflation of a blood pressure cuff to 50 mmHg above systolic blood pressure was followed. Occlusion was maintained for 5 min. After the release of occlusion by rapid deflation of the blood pressure cuff, an initial 1 min recording was done in PW mode to record the peak flow followed by brachial artery diameter measurement for 3 min. All images were recorded and stored for off-line analysis.
The post occlusion diameter was analysed from the B-mode as described for baseline diameter using automated edge-detection software. The end-diastolic diameters of the 3-min record were assessed to identify the peak diameter using automated edge-detection software. Diameter Fig. 1 Comparison of central stiffness and retrograde flow profile between the two groups. A Incremental Elastic modulus was significantly higher in patients with ischemic heart disease as compared to healthy subjects (Mann-Whitney test). B Carotid compliance was significantly lower in patients of ischemic heart disease compared to healthy subjects (Mann-Whitney test). C Retrograde blood flow velocity (mean -AUC) was comparable between the two groups (Mann-Whitney test). D Retrograde shear stress (mean-AUC) was comparable between the two groups (Mann-Whitney test) (*** indicates p < 0.0001, ** indicates p < 0.05).
values just before and after the peak diameter were checked to ensure that the values were consistent. 4-5 diameter values around the peak diameter were averaged to obtain the diameter in response to reactive hyperemia.
Flow-mediated dilation (FMD) was calculated using the following formulae: Delta FMD ¼ Peak Diameter after Occlusion À Diameter at Baseline and % FMD ¼ Peak Diameter after Occlusion À Diameter at Baseline Diameter at Baseline 100 During the last 1 min of occlusion, diameter in B-mode was acquired for 50 s and diameter and blood flow velocity in duplex mode PW doppler was acquired for last 10 s. The lowest end-diastolic diameter during the 50 s period was identified. The end-diastolic diameter values just before and after the lowest diameter were assessed to ensure that the values were consistent. 4-5 diameter values around the lowest diameter were then averaged to obtain the diameter during the low flow state for calculation of low flow mediated constriction (LFMC) using the following formulae:

Sub-clinical atherosclerosis
Carotid-Intima-Media Thickness (CIMT) provides an estimate of sub-clinical atherosclerotic burden and was measured using B-mode ultrasound (MindRay, M7). A 10 MHz linear array probe was used to take longitudinal images of a straight segment of the common carotid artery. Short loops of 5-7 consecutive cardiac cycles were saved for offline analysis using the carotid analyzer module (MIA, LLC). After automated analysis of the loop, end-diastolic frames were manually selected and far wall CIMT values were obtained. At-least 3 cycles where both near and far walls were clearly visible were averaged and used as a measure of near and far wall CIMT. A clear-straight section was taken for calculation of the CIMT.

Statistical analysis
The data distribution was tested using the Shapiro-Wilk test. Gaussian data are expressed as mean ± standard deviation and non-Gaussian data is expressed as median (interquartile range). Unpaired t test was used to compare parametric data between patients and healthy subjects and Mann-Whitney for non-parametric data.

RESULTS
Demographic characteristics of the study population are described in Table 1. Resting heart rate and fasting blood sugar levels were significantly higher in the patients as compared to healthy subjects. Healthy subjects had higher weight, total cholesterol, LDL, Triglyceride and HDL levels.
Comparison of resting retrograde flow velocity, shear stress and vascular parameters in patients and healthy subjects Incremental elastic modulus was significantly higher (Fig. 1A), and carotid compliance significantly lower (Fig. 1B) in the patients as compared to the healthy subjects. Aortic diastolic blood pressure was also significantly lower in patients. All resting retrograde flow profile variables were comparable between patients and healthy subjects ( Table 2 and Fig. 1C, D). OSI was also comparable between the two groups. Incremental Elastic modulus, carotid compliance, and aortic DBP remained significantly different between the two groups after Benjamini Hochberg's correction for multiple comparisons. There were no focal intrusions in the measured area of the carotid artery and the thickness for all measures was <1.5 mm, indicating the absence of any plaques in the region assessed.
Determinants of retrograde flow velocity and shear stress in healthy subjects Correlation analysis was performed separately for patients and healthy subjects for both RBFV and RSS to identify the central and peripheral vascular determinants of retrograde flow profile in both populations. The results of correlations between retrograde flow velocity, shear stress and OSI with vascular and hemodynamic parameters are described in Table 3 and Fig. 2A-C. A significant positive correlation was seen between RBFV max and RBFV AUC with Age (r = 0.47, p = 0.006 and r = 0.42, p = 0.017). RBFV max , RBFV AUC ,  Stepwise regression analysis using backward elimination was done to identify the best fit model for retrograde flow profile using the variables showing significant univariate associations. Age, weight, Total Cholesterol, LDL, Systolic Perfusion Pressure, Pulse Pressure Amplification, IEM, AI x @75 and carotid compliance were used in the analysis for RBFV max . AI x @75 and total cholesterol emerged in the best-fit model and were independent predictors of RBFV max , explaining 46.9% of the total variance, of which AI x @75 contributed 39.0%. The variance inflation factors were 1.21 for both AI x @75 and total cholesterol, suggesting no collinearity between these variables. For RBFV AUC , weight, IEM and triglyceride levels emerged in the best-fit model and were independent predictors of RBFV AUC . The model explained 53.9% of the total variance, with 19.1% being contributed by weight, 17.4% by IEM, and 17.3% by triglyceride levels. The variance inflation factors were 1.0 for weight and 1.03 for both IEM and triglyceride. AI x @75 emerged as the only variable in the stepwise regression analysis for both RSS max and RSS AUC, explaining 37.7% and 35.2% of the total variability. Aortic diastolic pressure, FVC and IEM emerged in the best-fit model for OSI, explaining 4.33%, 32.4% and 5.17% of the total 41.9% variance, respectively. The variance inflation factors were 1.18 for aortic DBP, 1.10 for FVC and 1.07 for IEM.

Determinants of retrograde flow velocity and shear stress in patients
The results of correlations between retrograde flow velocity, shear stress and OSI with vascular and hemodynamic parameters in the patient population are described in Table 4 and Fig. 2D-F. A significant positive correlation was seen between RBFV max , RBFV AUC , RSS auc and OSI with Age (r = 0.37, p = 0.012, r = 0.36, p = 0.015, r = 0.32, p = 0.033 and r = 0.41, p = 0.005, respectively). A significant positive correlation was seen between ejection fraction and RBFV max , RBFV AUC , RSS max , RSS AUC , and OSI (r = 0.38, p = 0.008, r = 0.34, p = 0.019, r = 0.47, p = 0.001, r = 0.40, p = 0.006 and r = 0.34, p = 0.020 respectively). A negative correlation was seen between OSI and triglycerides (r = −0.30, p = 0.048). No correlation was seen between any of the retrograde flow profile parameters with the severity of perfusion defect.
In stepwise regression analysis with backward elimination, age, aortic SBP, ejection fraction, cf/cr PWV and Augmentation Index were used in the model for RBFV max . Age, aortic SBP, and ejection fraction emerged in the best fit model, explaining 32.2% of the total variability (contributing 4.91, 13.4 and 13.9%, respectively). Aortic SBP and ejection fraction were independent predictors of RBFV max . The VIF were 1.04 for age. 1.03 for aortic SBP and 1.02 for ejection fraction. For RBFV AUC , age, FVC, ejection fraction and cf/cr Parametric data is expressed as mean ± SD and non-parametric data is expressed as median (interquartile range).  Association of brachial artery flow profile with endothelial function and sub-clinical atherosclerosis In healthy subjects, no correlation was seen between any of the retrograde flow profile parameters with %FMD or CIMT. A significant negative correlation was seen between RBFV max and %LFMC (r = −0.44, p = 0.012) (Fig. 3A). Interestingly, a significant positive correlation was seen between ABFV max and ASS max with %FMD (r = 0.45, p = 0.01 and r = 0.53, p = 0.002, respectively). No correlation was seen between FMD with Age, lipid profile or blood sugar levels. % LFMC showed a significant negative correlation with HDL and triglyceride levels (r = −0.37, p = 0.035 and r = −0.38, p = 0.031 respectively). On multiple regression analysis, the association between RBFV max and %LFMC was independent of HDL and triglycerides. In the patient group, a significant negative correlation was seen between RBFV max , RBFV AUC , RSS max , and RSS AUC with %FMD (r = −0.44, p = 0.004, r = −0.43, p = 0.004, r = −0.33, p = 0.030, r = −0.36, p = 0.018, and r = −0.33, p = 0.039, respectively) (Fig. 3B). Interestingly, a significant negative correlation was also seen between ABFV max , with %FMD (r = −0.30, p = 0.046). A significant positive correlation was seen between RBFV max , RBFV AUC , RSS max , and OSI with CIMT (r = 0.36, p = 0.01, r = 0.30, p = 0.041, r = 0.31, p = 0.036 and r = 0.31, p = 0.034, respectively) (Fig. 3C). No other correlations were seen between FMD or CIMT and Age, other lipid profile variables and fasting blood sugar.

DISCUSSION
The study aimed to address two critical aspects concerning retrograde flow. The first was to compare the retrograde flow profile in patients with ischemic heart disease with healthy subjects. The second was to understand the central and peripheral vascular factors associated with retrograde flow.
To the best of our knowledge, the current study is the first to report a comparison of resting retrograde flow profiles between healthy subjects and patients with cardiovascular diseases.
The results of the current study showed no difference in the retrograde flow variables between patients with ischemic heart disease and healthy subjects. Healthy subjects had significantly higher total cholesterol, LDL and HDL levels than the patients, possibly because of the lipid-lowering effect of statins in the patient population. Over 76% of the patient population was taking statins (Supplementary Table 1). Total cholesterol and triglyceride levels showed significant positive correlations with retrograde flow profile in healthy subjects and were also independent predictors of RBFV. Hypercholesterolemia could reduce Nitric Oxide (NO) bioavailability and be associated with increased vascular tone due to vasoconstrictor dominance. Total cholesterol and LDL levels showed a  significant positive correlation with augmentation index and a negative correlation with PPA. Additionally, while the acute effect of medications was partially avoided by asking the patients to withhold these for 24 h, the study findings may be influenced by the long-term effects of these medications on vascular structure and function, which could individually vary across the participants. An overall improvement in vascular compliance has been reported in patients taking angiotensin-enzyme inhibitors, β-blockers, angiotensin-II receptor blockers and calcium channel blockers [13]. An improvement in vascular compliance could result in reduced retrograde flow in patients. Indeed, both brachial FMD and cfPWV were comparable between the two groups. Future long-term studies are needed to evaluate if some of the beneficial effects of these drugs on endothelial function could possibly be mediated by a reduction in retrograde flow. A positive correlation was seen between ejection fraction and retrograde flow, suggesting that patients with lower ejection fraction had lower retrograde flows. Interestingly, age-related increases in retrograde flow have been proposed to be mediated by increases in sympathetic activity [10]. In a recent study, young, healthy males taking anabolic steroids were reported to have higher resting retrograde blood flow velocity and shear rate than non-users which was associated with higher sympathetic activity in the steroid users [14]. An increase in sympathetic nervous system activity and Norepinephrine (NE) spillover has been reported in heart failure patients with reduced ejection fraction (HFrEF). However, neither the increased sympathetic activity nor NE levels directly correlated with the ejection fraction or systemic vascular resistance [15]. FVC was also an independent determinant of retrograde flow in patients, and no correlation was seen between ejection fraction and FVC. The sympathetic activity was not measured in the current study, but the results suggest that ejection fraction and FVC drive the retrograde flow in opposing directions, which may not be related to sympathetic activity, at least in patients with ischemic heart disease.
The results of the central and peripheral vascular factors associated with retrograde flow further highlight the differences in the determinants of retrograde flow between patients and healthy subjects (Fig. 4). Retrograde flow profiles in healthy subjects and patients showed an association with the augmentation index, a composite marker of central stiffness and peripheral wave reflections. Interestingly, retrograde flow in healthy subjects was closely associated with increased central arterial stiffness (IEM, carotid compliance), with minimal effect of FVC. On the other hand, retrograde flow in patients with ischemic heart disease appears to result from an interplay between central, peripheral, and cardioarterial interactions. Ejection fraction, cf/crPWV, Augmentation index and FVC emerged as critical determinants of retrograde flow profile in patients. An increase in IEM and a decrease in carotid compliance would increase the slope and amplitude of incident pressure wave at the brachial arterial site during systole and lead to a sharper decline in pressure during the diastolic phase due to loss of Windkessel function. A higher augmentation index would further indicate an increase in systolic pressure and a lack of diastolic pressure augmentation. The cumulative effect of these changes would lead to lower proximal pressures for a longer duration of the cardiac cycle. Indeed, lower aortic DBP was an independent predictor of OSI in healthy subjects. One study has previously assessed a measure of central stiffness (cfPWV) in association with brachial artery retrograde flow and reported that regional central A significant positive correlation was seen between retrograde blood flow velocity (mean -AUC) (RBFV AUC ) with augmentation index in healthy subjects (Pearson's correlation) (B). A significant positive correlation was seen between RBFV AUC and incremental elastic modulus in healthy subjects (Spearman Correlation) (C). A significant negative correlation was seen between oscillatory shear index and forearm vascular conductance in healthy subjects (Spearman Correlation) (D). A significant positive correlation was seen between RBFV AUC and Ejection fraction in patients with ischemic heart disease (Spearman Correlation) (E). A significant negative correlation was seen between RBFV AUC and forearm vascular conductance in patients with ischemic heart disease (Spearman Correlation) (F). A significant positive correlation was seen between RBFV AUC and cf/cr pulse wave velocity ratio (Spearman Correlation).
arterial stiffness (cfPWV) was higher in subjects with retrograde flow as opposed to those without retrograde flow in Framingham heart study offspring and third-generation cohorts [9]. In another study, flow reversal at the femoral artery of hypertensive subjects was negatively associated with augmentation index and cfPWV [16]. Credeur et al. reported a negative association (r = −0.27) between vascular conductance and retrograde flow in a mixed ageing population of healthy and diseased individuals [8].
Retrograde flow was also associated with endothelial dysfunction and atherosclerotic changes in patients. Furthermore, higher retrograde flow was related to the reversal of the elastic gradient between central and peripheral arteries (cf/cr PWV), which was also associated with endothelial dysfunction. Reversal of the elastic gradient would result in the greater transmission of pulsatile pressures to the microvasculature. The resultant activation of a myogenic response and increased microvascular resistance would increase reflections from the distal sites and contribute to the development of retrograde flow.
An increase in retrograde flow due to vascular alterations could be a potential factor in the development of endothelial dysfunction in patients with heart failure with preserved ejection fraction. Endothelial dysfunction and carotid-intima media thickness have been previously associated with flow reversal in the study on the Framingham cohort [9]. Similar results were observed in the patient population in the current study. Healthy subjects showed a significant positive correlation between anterograde flow and FMD and a negative correlation between RBFV max and LFMC but not between retrograde flow and FMD. In a previous study, we reported that constriction during occlusion (LFMC) might be a better indicator of sub-clinical endothelial dysfunction, especially in a healthy population [17].
The study results suggest that, unlike healthy subjects, the complex interplay between central and peripheral vascular stiffness, flow profile and its consequent effect on endothelial function in the patient population cannot be explained entirely by analytical techniques alone. A limitation of the current study is that ejection fraction was not measured in healthy subjects. Therefore, a comparison of flows, corrected for the reduction due to ejection fraction, cannot be performed. Further, while the current patient population did not exhibit significant valvulopathies, the effect of valvular pathologies and alterations in cardiac systolic and diastolic function on retrograde flow needs to be further evaluated in future studies. Another limitation is the small sample size for intergroup comparison of flows. The smaller sample size also limits the ability to evaluate the effects of disease severity. However, there is no data comparing retrograde flow between any cardiovascular disease group with healthy subjects, and the current study provides preliminary insights. Additionally, in the given sample size and with an observational study design, the results of multiple regression serve to provide conceptual insight into the possible factors affecting retrograde flow. These need to be further evaluated in studies with larger sample size. Future studies in a broader range of patients with cardiovascular diseases and machine learning approaches can help accurately decipher the determinants of retrograde flow in patients. Another addition to the study can be the evaluation of local brachial artery distensibility using echo tracking to understand its contribution to retrograde flow.
Based on the study results, it can be concluded that retrograde shear stress is associated with endothelial dysfunction and subclinical atherosclerosis in patients with ischemic heart disease. Further, central arterial stiffening, possibly by its impact on the morphology of the incident pressure waveform, and an increase in peripheral wave reflections, may influence the retrograde flow in the brachial artery. To the best of our knowledge, this is the first study to evaluate central and peripheral vascular factors associated with baseline retrograde flow profiles and compare retrograde flow profiles in patients with cardiovascular diseases and healthy subjects.    Parameters in bold dark gray were majorly found to be associated with retrograde flow patterns in healthy subjects. Parameters in bold black were majorly found to be associated with retrograde flow patterns in patients with ischemic heart disease. Parameter in italics was found to be associated with retrograde flow in both healthy subjects and patients with ischemic heart disease. Non-bolded parameters in light gray were not found to be associated with retrograde flow patterns in either group.