Characterising Haemodynamic Stress during Haemodialysis Using the Extrema Points Analysis Model

Eldehni, Mohamed Tarek; Odudu, Aghogho; McIntyre, Christopher W.

doi:10.1159/000359958

Cited by 9 publications

(14 citation statements)

References 17 publications

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“…25 We then demonstrated that this hemodynamic behavior is exacerbated by the circulatory stress of HD as the MAP extrema points frequencies continue to rise throughout the dialysis session to peak during the third quarter of the session. 49 Furthermore, in a randomized controlled trial, we found that cooling the dialysate could have a protective effect on brain white matter by altering this hemodynamic behavior. 16 In that trial, higher frequencies of MAP extrema points were associated with measures of acute damage in brain white matter.…”

Section: Discussionmentioning

confidence: 90%

“…We have previously demonstrated that in the resting state, extrema points frequencies of MAP seem to be much higher in HD than a normal control . We then demonstrated that this hemodynamic behavior is exacerbated by the circulatory stress of HD as the MAP extrema points frequencies continue to rise throughout the dialysis session to peak during the third quarter of the session . Furthermore, in a randomized controlled trial, we found that cooling the dialysate could have a protective effect on brain white matter by altering this hemodynamic behavior .…”

Section: Discussionmentioning

confidence: 99%

“…It is therefore plausible that higher frequencies of extrema points induce acute injury in brain white matter, which in terms leads to chronic white matter damage that is observed in this study when compared with brain white matter structure of age matched controls. The main determinant of extrema points frequencies in this group was found to be the degree of autonomic dysfunction represented by baroreflex sensitivity …”

Section: Discussionmentioning

confidence: 99%

“…The main determinant of extrema points frequencies in this group was found to be the degree of autonomic dysfunction represented by baroreflex sensitivity. 49 The observed white matter damage and cognitive impairment are likely to have developed as patients progressed though the stages of chronic kidney disease. Drew et al found that the higher incident of white matter disease in HD patients than normal controls was predicted by age and being on hemodialysis.…”

Section: Discussionmentioning

confidence: 99%

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Brain white matter microstructure in end‐stage kidney disease, cognitive impairment, and circulatory stress

Eldehni

Odudu

McIntyre

2019

Hemodialysis International

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Introduction: Structural and functional brain white matter abnormalities are poorly characterized in patients with end‐stage kidney disease. Methods: We examined the prevalence of the brain white matter microstructure disruption using diffusion tensor magnetic resonance imaging and its association with hemodynamic performance and cognitive defects in 49 incident hemodialysis (HD) patients and compared these to 25 age‐matched normal controls. We analyzed fractional anisotropy (FA) and mean diffusivity (MD) maps of the images, a voxelwise statistical analysis was done using tract‐based spatial statistics. Hemodynamic assessment was done using extrema points analysis model of continuous blood pressure monitoring. Findings: We found significant white matter damage in HD patients compared with normal controls (peak FA 0.471 ± 0.031 vs 0.486 ± 0.022 P = 0.023, peak MD 0.00194 ± 0.000363 10−3 mm2.s−1 vs 0.00167 ± 0.0003 10−3 mm2.s−1 P = 0.002). There was diffuse pattern of white matter damage in HD patients, which was independent of age, gender, and the presence of ischaemic heart disease and diabetes with significantly lower FA values in HD patients than normal controls (0.467 ± 0.037 vs 0.507 ± 0.026, P < 0.05 corrected for family wise error. HD patients had worse cognitive scores that correlated with white matter damage (for peak FA, Montreal cognitive assessment r = 0.478 P = 0.001, Trail A r = −0.486 P = 0.001, Trail B r = −0.464 P = 0.001; for peak MD, Montreal cognitive assessment r = −0.533 P < 0.001, Trail A r = 0.641 P < 0.001, Trail B r = 0.514 P < 0.001). In a multivariable linear regression analysis that included age, smoking, the presence of ischaemic heart disease, and diabetes mellitus, higher frequency of mean arterial blood pressure extrema points during HD was independently associated with white matter damage (β = −0.296, P = 0.036, Adjusted R2 for the whole model = 0.400). Discussion: End‐stage kidney disease patients on HD have more brain white matter damage and cognitive impairment than age‐matched controls that are linked to hemodynamic functional measures.

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Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Brain white matter microstructure in end‐stage kidney disease, cognitive impairment, and circulatory stress

Eldehni

Odudu

McIntyre

2019

Hemodialysis International

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“…We conducted ECG tests on each patient 10 minutes before HD and 15 minutes before the end of HD (at peak stress [ 9 ]). The recordings were taken using a 12-lead machine (MAC 1200, GE) at 10mm/mv and 25mm/s.…”

Section: Methodsmentioning

confidence: 99%

Electrocardiographic Abnormalities and QTc Interval in Patients Undergoing Hemodialysis

Nie¹,

Zou²,

Liang³

et al. 2016

PLoS ONE

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BackgroundSudden cardiac death is one of the primary causes of mortality in chronic hemodialysis (HD) patients. Prolonged QTc interval is associated with increased rate of sudden cardiac death. The aim of this article is to assess the abnormalities found in electrocardiograms (ECGs), and to explore factors that can influence the QTc interval.MethodsA total of 141 conventional HD patients were enrolled in this study. ECG tests were conducted on each patient before a single dialysis session and 15 minutes before the end of dialysis session (at peak stress). Echocardiography tests were conducted before dialysis session began. Blood samples were drawn by phlebotomy immediately before and after the dialysis session.ResultsBefore dialysis, 93.62% of the patients were in sinus rhythm, and approximately 65% of the patients showed a prolonged QTc interval (i.e., a QTc interval above 440 ms in males and above 460ms in females). A comparison of ECG parameters before dialysis and at peak stress showed increases in heart rate (77.45±11.92 vs. 80.38±14.65 bpm, p = 0.001) and QTc interval (460.05±24.53 ms vs. 470.93±24.92 ms, p<0.001). After dividing patients into two groups according to the QTc interval, lower pre-dialysis serum concentrations of potassium (K+), calcium (Ca2+), phosphorus, calcium* phosphorus (Ca*P), and higher concentrations of plasma brain natriuretic peptide (BNP) were found in the group with prolonged QTc intervals. Patients in this group also had a larger left atrial diameter (LAD) and a thicker interventricular septum, and they tended to be older than patients in the other group. Then patients were divided into two groups according to ΔQTc (ΔQTc = QTc peak-stress- QTc pre-HD). When analyzing the patients whose QTc intervals were longer at peak stress than before HD, we found that they had higher concentrations of Ca2+ and P5+ and lower concentrations of K+, ferritin, UA, and BNP. They were also more likely to be female. In addition, more cardiac construction abnormalities were found in this group. In multiple regression analyses, serum Ca2+ concentration before HD and LAD were independent variables of QTc interval prolongation. UA, ferritin, and interventricular septum were independent variables of ΔQTc.ConclusionProlonged QT interval is very common in HD patients and is associated with several risk factors. An appropriate concentration of dialysate electrolytes should be chosen depending on patients’ clinical conditions.

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An Analysis of Frequency of Continuous Blood Pressure Variation and Haemodynamic Responses during Haemodialysis

et al. 2021

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Background: Higher beat-to-beat blood pressure (BP) variation during haemodialysis (HD) has been shown to be associated with elevated cardiac damage markers and white matter ischaemic changes in the brain suggesting relevance to end-organ perfusion. We aimed to characterize individual patterns of BP variation and associated haemodynamic responses to HD. Methods: Fifty participants underwent continuous non-invasive haemodynamic monitoring during HD and BP variation were assessed using extrema point (EP) frequency analysis. Participants were divided into those with a greater proportion of low frequency (LF, n = 21) and high frequency (HF, n = 22) of BP variation. Clinical and haemodynamic data were compared between groups. Results: Median EP frequencies for mean arterial pressure (MAP) of mid-week HD sessions were 0.54 Hz (interquartile range 0.18) and correlated with dialysis vintage (r = 0.32, p = 0.039), NT pro-BNP levels (r = 0.32, p = 0.038), and average real variability (ARV) of systolic BP (r = 0.33, p = 0.029), ARV of diastolic BP (r = 0.46, p = 0.002), and ARV of MAP (r = 0.57, p < 0.001). In the LF group, MAP positively correlated with cardiac power index (CPI) in each hour of dialysis, but not with total peripheral resistance index (TPRI). In contrast, in the HF group, MAP correlated with TPRI in each hour of dialysis but only with CPI in the first hour. Conclusions: EP frequency analysis of continuous BP monitoring during dialysis allows assessment of BP variation and categorization of individuals into low- or high-frequency groups, which were characterized by different haemodynamic responses to dialysis. This may assist in improved individualization of dialysis therapy.

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Characterising Haemodynamic Stress during Haemodialysis Using the Extrema Points Analysis Model

Cited by 9 publications

References 17 publications

Brain white matter microstructure in end‐stage kidney disease, cognitive impairment, and circulatory stress

Brain white matter microstructure in end‐stage kidney disease, cognitive impairment, and circulatory stress

Electrocardiographic Abnormalities and QTc Interval in Patients Undergoing Hemodialysis

An Analysis of Frequency of Continuous Blood Pressure Variation and Haemodynamic Responses during Haemodialysis

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