Abstract
Introduction: The effect of kidney transplantation on endothelial dysfunction and autonomic dysfunction in uremia remains controversial, and few studies have evaluated this question. Endothelial dysfunction and autonomic dysfunction, both, be assessed noninvasively using laser Doppler flowmetry (LDF). This study evaluated cutaneous microvascular blood flow and reactivity using LDF in patients undergoing kidney transplantation. Methods: This prospective longitudinal cohort study involved 40 patients with chronic kidney disease (CKD) undergoing kidney transplantation, compared with 40 patients without kidney disease. Using LDF, post-occlusive reactive hyperemia (PORH) (resting flow [RF], peak flow, ratio between peak, and RF, hyperemic area, PORH index), and sympathetic constrictor response to inspiratory breath-hold (mean minimum inspiratory values) were evaluated. Results: RF and sympathetic constrictor response to inspiratory breath-hold (mean minimum inspiratory values), were lower in the CKD group at 1 week and at 3 months after transplantation (p < 0.005). Mean minimum inspiratory values increase in the CKD group, 3 months after transplantation. Conclusion: Compared with controls with no CKD, in CKD patients undergoing kidney transplantation, microcirculation by LDF shows improvement after 3 months.
Introduction
Chronic kidney disease (CKD) is defined according to international guidelines as a reduction in renal function as shown by a glomerular filtration rate <60 mL/min/1.73 m2 and/or markers of kidney damage for 3 months or more, regardless of the underlying cause [1, 2]. In the USA, around 661,000 individuals have been diagnosed with kidney failure. Of these, 468,000 individuals are on dialysis, and around 193,000 are living with a functioning kidney transplant [2].
Patients with CKD are at an increased risk of cardiovascular morbidity and are 5–10 times more likely to suffer premature death. This risk of mortality increases exponentially as kidney function declines, and this is attributable to a substantial extent to cardiovascular disease (CVD) [1‒7]. The high prevalence of CVD in patients with CKD is partially due to the high rate of coexisting diseases and possibly due to the inflammation and oxidative stress found in these patients. In addition, studies have been conducted to evaluate the association between CVD, endothelial dysfunction, and autonomic dysfunction in uremia [8‒11].
Endothelial dysfunction is characterized by impairment of endothelium-mediated vasodilation in association with a mild proliferation of smooth muscle cells and fibrinolysis [12]. It is present in patients with CKD during any phase of the disease and is found in association with vascular remodelling and the loss of renal micro-vessels, playing an important role in the physiopathology of kidney failure. Endothelial dysfunction may represent a consequence of the diminished bioavailability of nitric oxide, which exerts numerous anti-atherogenic effects in addition to its other properties, such as the ability to inhibit leukocyte and platelet adhesion, and to promote smooth muscle cell proliferation [12‒15].
In autonomic dysfunction in uremia, on the other hand, there is an increase in plasma catecholamine levels and resistance to their physiological effects, as well as a decrease in responses mediated by beta-adrenergic and muscarinic receptors, which is considered part of the spectrum of functional abnormalities associated with the accumulation of uremic toxins [16]. It is traditionally evaluated using cardiovascular autonomic function tests and heart rate variability [17]. The mechanisms through which autonomic dysfunction in uremia is involved with cardiovascular damage remain to be fully clarified; however, sympathetic stimulation may increase cardiac automaticity, favoring the occurrence of arrhythmias and sudden death [11, 16, 18, 19].
The effect of kidney transplantation on endothelial dysfunction and autonomic dysfunction in uremia remains controversial, and few studies have evaluated this question. Endothelial dysfunction can be assessed noninvasively using laser Doppler flowmetry (LDF). The primary function of LDF is to produce a blood perfusion output signal that is proportional to the red blood cell concentration times the mean velocity of these cells. When combined with reactivity tests, this provides an evaluation of endothelial-dependent regulation of vascular tone. It can also be used to evaluate changes in neurovascular control and the possible risk of future cardiovascular events [17, 20‒26]. Therefore, the objective of the present study was to evaluate microvascular blood flow and reactivity using LDF in patients with CKD and to assess how kidney transplantation affects skin microvascular reactivity.
Methods
This prospective longitudinal cohort study recruited patients with CKD undergoing kidney transplantation and patients attending the internal medicine outpatient clinic at the Instituto de Medicina Integral Prof. Fernando Figueira (IMIP). The study was conducted at this institute between April 2016 and December 2019. IMIPs Internal Review Board approved the study protocol, under the approval letter (CAE -43929815800005201). Written informed consent was obtained from all participants.
All patients with CKD (case group) who fulfilled the eligibility criteria and agreed to participate in the study were included. After CKD patients had been admitted to the study, patients from the comparison group were selected. These compared participants (compared group) were patients without CKD who attended their first appointment at the internal medicine outpatient clinic and had similar coexisting diseases (systemic arterial hypertension, diabetes mellitus, collagenoses, and so on) to the patients with CKD and were of a similar age (5 years).
The inclusion criteria for the case group were being over 18 years of age, having CKD (glomerular filtration rate <60 mL/min/1.73 m2 and/or markers of kidney damage for 3 months or more, regardless of the underlying cause), and having been submitted to kidney transplantation. Microvascular tests were conducted in the week following transplantation, and the resulting values were considered baseline measurements. For the compared group, participants had to have the same secondary diseases and be of a similar age (±5 years) as the cases, without the presence of CKD. The exclusion criteria for the case and compared groups were: cognitive impairment, hearing impairment, visual impairment, and/or any motor impairment that could hamper the evaluation of microcirculation, any neuromuscular disease, using illegal drugs, or being a living organ donor (for the case group alone). The following variables were evaluated: postoperative endpoints (acute rejection and early anemia), laboratory tests (creatinine, estimated creatinine clearance rate, and hemoglobin), and microvascular reactivity.
Acute rejection was determined by performing a biopsy of the transplanted kidney, with rejection determined according to the Banff classification of renal transplant pathology [27]. Early anemia, i.e., anemia occurring soon after transplantation, was defined as hemoglobin levels <11 mg/dL and <10 mg/dL for men and women, respectively, in the first 3/6 months following kidney transplantation [28, 29]. The estimated glomerular filtration rate (eGFR) was based on creatinine new equations developed by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and the European Kidney Function Consortium (EKFC) [30]. In addition to the absolute values, for analysis purposes, the eGFR was adjusted to: equal to or less than 60 mL/min/1.73 m2.
The absence of CKD in the controls was evaluated according to the information provided by the patient and his/her attending physician, and in accordance with creatinine levels. Men with creatinine levels >1.3 mg/dL and women with levels >1.1 mg/dL were considered to have some form of kidney disease and were therefore excluded from the study [29, 31].
Microvascular reactivity was evaluated by a vascular monitoring system with LDF (VMS-LDF) dual-channel (Moor Instruments, UK). The patient was required to have fasted for 2 h prior to the examination and avoided caffeine-based drinks, alcohol consumption, and any physical activity for at least 8 h prior to the test. Measurements were conducted over a 20-min period in a noise-free environment with a controlled temperature between 22°C and 23°C. All participants remained comfortably seated in a reclining chair, with arms supported at heart level, and avoided movements or talking during the test. The skin probes were placed on the inner surface of the right forearm approximately 5 cm below the cubital fossa and avoiding large blood vessels, and the responses to brief arterial occlusion, reactive hyperemia, the forearm probe, and the sympathetic constrictor response to deep inspiratory breath-hold (IBH), the finger probe, were measured [32]. The skin blood flux in arbitrary perfusion units (PUs) was displayed and analyzed using the Moor VMS-PC V3.1 software program. Resting blood flux was recorded for 5 min, followed by three, 6 s-long deep IBHs to elicit the sympathetic constrictor response. The investigator controlled the time, and participants were given the opportunity to practice before the probe was positioned. Arterial occlusion was performed following a further 5-min baseline recording using an automated blood pressure cuff placed around the upper arm and inflated to a pressure of 200 mm Hg for 3 min. Recoding was continued until the blood flux measured at the forearm returned to baseline. The following parameters were evaluated [32].
Resting flow (RF): mean resting blood flow measured over 5 min prior to occlusion, expressed as PU
PORH index: post-occlusive forearm skin reactive hyperemia index
PF: peak blood flow at the forearm following release of arterial occlusion, expressed as PU
PF/RF: ratio between peak flow and RF
HA: hyperemic area under the flow curve that represents the dilator response after occlusion is released
MediaInsp (mean minimum inspiratory values): sympathetic constrictor response to IBH, measured by the mean of the absolute value during IBH, expressed as PU
The investigator collected all the microvascular data during the week following kidney transplantation (baseline, time point 1) and again 3 months later (time point 2). The patients’ forms contained an adhesive sticker defining the date of their return visit, with the appointment then being immediately scheduled. Staff at the clinic called each participant on the week of their scheduled visit to confirm the appointment and answer any questions.
Sample Size
Sample size was calculated using the web-based, open-source software programme, OpenEpi, version 3.01, updated on April 4, 2013. The calculation was based on the results of a pilot study conducted with 30 patients (15 in the case group and 15 in the non-CKD controls). The first parameter for the calculation of sample size was the LDF parameter mean inspiratory value, which was found to be 58.20 ± 43.32 (±SD) for the case group and 87.21 ± 46.49 for the controls. Assuming a 95% confidence level and 80% power of the test, 38 patients would be required in each group to detect a difference between the groups. However, to compensate for the loss of follow-up, estimated at 10%, the final sample size was calculated at 42 participants in each group, making a total of 84 participants in the study.
Data Analysis
Data analysis was performed using the STATA software program. In the case of numerical variables with a normal distribution, the Student’s t test was used for two independent samples, and the non-parametric Mann-Whitney test was used when the distribution was not normal. These same tests were used in their paired versions to evaluate measurements repeated over time. To evaluate the normality of the data, the Shapiro-Wilk test was used for the samples with fewer than 40 observations. For the other samples, normalcy was established using the central limit theorem. In addition to the statistical tests, confidence intervals were calculated, considering a 95% confidence interval in all cases.
Results
Of the 91 patients considered for inclusion in the study, 84 were admitted. Four participants were lost to follow-up, two in each group. Therefore, the final analysis included 80 participants, 40 in each group (Fig. 1). The participants in the comparative group were considered suitable controls for the patients in the case group, with the demographic characteristics being very similar in both groups, differing only in respect to the levels of creatinine and eGFR (Table 1). The principal condition responsible for CKD was undetermined in 67.5% of the patients in the case group, while in 27.5% and 5% of the participants, respectively, hypertensive nephropathy and diabetic nephropathy were identified as being responsible for CKD. In the comparative group, 2 (5%) had diabetic mellitus, 11 (27.5%) had systematic arterial hypertension, and 27 (67.5%) had other diagnoses.
Characteristics/group . | Cases (n = 40) . | Non-CKD controls (n = 40) . | p value . |
---|---|---|---|
Age mean (SD), years | 42.77 (2.0) | 44.72 (1.87) | 0.73a |
Sex, n (%) | |||
Female | 16 (40) | 15 (37.5) | 0.81b |
Male | 24 (60.0) | 25 (62.5) | |
Disease responsible for CKD, n (%) | |||
Diabetic nephropathy | 2 (5) | - | - |
Hypertensive nephropathy | 11 (27.5) | - | - |
Other causes | 27 (67.5) | - | - |
Anti-hypertensive treatment, n (%) | 40 (100.0) | 24 (60.0) | p < 0.05a |
Creatinine, mean (SD), mg/dL | 8.2 (0.6) | 0.84 (0.2) | <0.001a |
eGFR, mean (SD), mL/min/1.73 m2 | 11.0 (13.9) | 102.7 (14.1) | <0.001a |
Dialysis duration mean (SD), years | 4.7 (3.5) | - | - |
Immunosuppression protocol, n (%) | - | ||
Azathioprine, cyclosporine, and prednisone | 20 (50.0) | - | - |
Mycophenolate and tacrolimus and prednisone | 20 (50.0) | - |
Characteristics/group . | Cases (n = 40) . | Non-CKD controls (n = 40) . | p value . |
---|---|---|---|
Age mean (SD), years | 42.77 (2.0) | 44.72 (1.87) | 0.73a |
Sex, n (%) | |||
Female | 16 (40) | 15 (37.5) | 0.81b |
Male | 24 (60.0) | 25 (62.5) | |
Disease responsible for CKD, n (%) | |||
Diabetic nephropathy | 2 (5) | - | - |
Hypertensive nephropathy | 11 (27.5) | - | - |
Other causes | 27 (67.5) | - | - |
Anti-hypertensive treatment, n (%) | 40 (100.0) | 24 (60.0) | p < 0.05a |
Creatinine, mean (SD), mg/dL | 8.2 (0.6) | 0.84 (0.2) | <0.001a |
eGFR, mean (SD), mL/min/1.73 m2 | 11.0 (13.9) | 102.7 (14.1) | <0.001a |
Dialysis duration mean (SD), years | 4.7 (3.5) | - | - |
Immunosuppression protocol, n (%) | - | ||
Azathioprine, cyclosporine, and prednisone | 20 (50.0) | - | - |
Mycophenolate and tacrolimus and prednisone | 20 (50.0) | - |
SD, standard deviation; eGFR, estimated glomerular filtration rate.
aStudent’s t test (two-tailed).
bχ2 square test (two-tailed).
At baseline (week 1), no significant differences were found between the case and compared groups for the majority of microvascular parameters evaluated, with the exception of RF and the mean minimum inspiratory values, which were lower in the case group, respectively, 19.9 ± 13.1 versus 29.1 ± 17.5; p = 0.007: 95% CI: −16.0 to −2, 5, and 51.29 ± 37.4 versus 104.2 ± 58.5; p = 0.000; 95% CI: −74.3 to −31.7. At the 3-month evaluation, in addition to the differences that persisted between the groups in relation to the mean minimum inspiratory values (64.7 ± 44.8 PU for cases vs. 100.6 ± 43.1 PU for comparison), the PF/RF ratio was found to be significantly higher in the case group compared to the control group (6.0 ± 4.1 vs. 4.3 ± 1.7; p = 0.013) (Table 2).
Parameters . | Cases . | Non-CKD controls . | Mean differencea (95% CI) . | p value . |
---|---|---|---|---|
One week: mean±SD | ||||
RF | 19.9±13.1 (N = 39) | 29.1±17.5 (N = 40) | −9.2 (−16.0 to −2.5) | 0.007 |
PF | 117.0±107.3 (N = 40) | 133.5±79.7 (N = 40) | −16.5 (−57.4 to 24.4) | 0.429 |
PF/RF ratio | 6.0±5.4 (N = 40) | 5.4±3.4 (N = 40) | 0.6 (−1.3 to 2.6) | 0.539 |
HA | 1,966.5 1±772.0 (N = 36) | 1,743.0±1,196.9 (N = 38) | 223.5 (−452.8 to 900.0) | 0.517 |
PORH index | 2.3±1.2 (N = 40) | 2.4±0.7 (N = 40) | −0.08 (−0.50 to 0.33) | 0.737 |
Mean minimum inspiratory values | 51.3±37.4 (N = 40) | 104.3±58.5 (N = 40) | −53.0 (−74.3 to −31.7) | <0.001 |
Three months: mean±SD | ||||
RF | 19.2±11.1 (N = 39) | 33.5±16.7 (N = 40) | −14.2 (−20.4 to 7.9) | <0.001 |
PF | 117.0±92.5 (N = 40) | 129.6±50.1 (N = 40) | −12.6 (−44.8 to 19.6) | 0.442 |
PF/RF ratio | 6.0±4.1 (N = 40) | 4.3±1.7 (N = 40) | 1.7 (0.4 to 3.1) | 0.013 |
HA | 1,920.8±1,514.9 (N = 36) | 1,805.4±898.1 (N = 38) | 115.4 (−440.8 to 671.6) | 0.684 |
POHR index | 2.4±1.1 (N = 40) | 2.2±0.6 (N = 40) | 0.2 (−0.13 to 0.70) | 0.7152 |
Mean minimum inspiratory values | 64.7±44.8 (N = 39) | 100.6±43.1 (N = 40) | −35.9 (−54.9 to −16.8) | <0.001 |
Parameters . | Cases . | Non-CKD controls . | Mean differencea (95% CI) . | p value . |
---|---|---|---|---|
One week: mean±SD | ||||
RF | 19.9±13.1 (N = 39) | 29.1±17.5 (N = 40) | −9.2 (−16.0 to −2.5) | 0.007 |
PF | 117.0±107.3 (N = 40) | 133.5±79.7 (N = 40) | −16.5 (−57.4 to 24.4) | 0.429 |
PF/RF ratio | 6.0±5.4 (N = 40) | 5.4±3.4 (N = 40) | 0.6 (−1.3 to 2.6) | 0.539 |
HA | 1,966.5 1±772.0 (N = 36) | 1,743.0±1,196.9 (N = 38) | 223.5 (−452.8 to 900.0) | 0.517 |
PORH index | 2.3±1.2 (N = 40) | 2.4±0.7 (N = 40) | −0.08 (−0.50 to 0.33) | 0.737 |
Mean minimum inspiratory values | 51.3±37.4 (N = 40) | 104.3±58.5 (N = 40) | −53.0 (−74.3 to −31.7) | <0.001 |
Three months: mean±SD | ||||
RF | 19.2±11.1 (N = 39) | 33.5±16.7 (N = 40) | −14.2 (−20.4 to 7.9) | <0.001 |
PF | 117.0±92.5 (N = 40) | 129.6±50.1 (N = 40) | −12.6 (−44.8 to 19.6) | 0.442 |
PF/RF ratio | 6.0±4.1 (N = 40) | 4.3±1.7 (N = 40) | 1.7 (0.4 to 3.1) | 0.013 |
HA | 1,920.8±1,514.9 (N = 36) | 1,805.4±898.1 (N = 38) | 115.4 (−440.8 to 671.6) | 0.684 |
POHR index | 2.4±1.1 (N = 40) | 2.2±0.6 (N = 40) | 0.2 (−0.13 to 0.70) | 0.7152 |
Mean minimum inspiratory values | 64.7±44.8 (N = 39) | 100.6±43.1 (N = 40) | −35.9 (−54.9 to −16.8) | <0.001 |
aMean difference, mean cases – mean non-CKD controls.
The comparison of the two time points within each group revealed that the laboratory parameters (creatinine, eGFR, and hemoglobin) were significantly lower 3 months after kidney transplantation. The CKD group showed an increase in MediaInsp, 3 months after transplantation. The other LDF parameters did not change in CKD group. The non-CKD controls showed no modifications of LDF parameters in the intragroup comparison (1 week and 3 months) (Table 3).
Parameters . | Cases (n = 40) . | Non-CKD controls . | ||||||
---|---|---|---|---|---|---|---|---|
week one . | three months . | difference mean (CI 95%) . | p value . | week one . | three months . | difference mean (CI 95%) . | p value . | |
mean±SD . | mean±SD . | mean±SD . | mean±SD . | |||||
RF | 19.9±13.1 | 19.2±11.1 | 0.7 (−1.9 to 3.3) | 0.619 | 29.1±17.5 | 31.5±16.7 | −2.4 (−4.0 to −1.8) | 0.101 |
PF | 117.0±107.3 | 117.0±92.5 | 0.0 (−19.2 to 19.2) | >0.99 | 133.5±79.7 | 129.6±50.1 | 3.9 (−15.3 to 23.1) | 0.692 |
PF/RF ratio | 6.0±4.1 | 6.0±5.4 | 0.0 (−1.1 to 1.1) | 0.916 | 5.4±3.4 | 4.3±1.7 | 1.1 (−0.07 to 2.1) | 0.067 |
HA | 1,966.5±1,772.0 | 1,920.8±1,514.9 | 45.7 (−364.3 to 455.6) | 0.827 | 1,743.0±1,196.9 | 1,805.4±898.1 | −62.4 (−461.4 to 336.6) | 0.759 |
PORH index | 2.3±1.2 | 2.4±1.1 | −0.2 (−0.5 to 0.1) | 0.289 | 2.4±0.7 | 2.2±0.6 | 0.2 (−0.1 to 0.5) | 0.207 |
Mean minimum inspiratory values | 51.3±37.4 | 65.3±44.9 | −13.4 (−25.0 to −1.8) | 0.023 | 104.3±58.5 | 100.6±43.1 | 3.7 (−7.8 to 15.2) | 0.526 |
GFR | 11.0±13.9 | 47.5±24.7 | −36.5 (−44.2 to −29.0) | <0.001 | - | - | - | - |
Creatinine (mg/dL) | 8.2±3.8 | 2.6±2.9 | 5.6 (4.0 to 7.0) | <0.001 | - | - | - | - |
Hemoglobin (mg/dL) | 9.7±2.8 | 11.1±2.3 | −1.5 (−2.6 to −0.4) | 0.016 | - | - | - | - |
Parameters . | Cases (n = 40) . | Non-CKD controls . | ||||||
---|---|---|---|---|---|---|---|---|
week one . | three months . | difference mean (CI 95%) . | p value . | week one . | three months . | difference mean (CI 95%) . | p value . | |
mean±SD . | mean±SD . | mean±SD . | mean±SD . | |||||
RF | 19.9±13.1 | 19.2±11.1 | 0.7 (−1.9 to 3.3) | 0.619 | 29.1±17.5 | 31.5±16.7 | −2.4 (−4.0 to −1.8) | 0.101 |
PF | 117.0±107.3 | 117.0±92.5 | 0.0 (−19.2 to 19.2) | >0.99 | 133.5±79.7 | 129.6±50.1 | 3.9 (−15.3 to 23.1) | 0.692 |
PF/RF ratio | 6.0±4.1 | 6.0±5.4 | 0.0 (−1.1 to 1.1) | 0.916 | 5.4±3.4 | 4.3±1.7 | 1.1 (−0.07 to 2.1) | 0.067 |
HA | 1,966.5±1,772.0 | 1,920.8±1,514.9 | 45.7 (−364.3 to 455.6) | 0.827 | 1,743.0±1,196.9 | 1,805.4±898.1 | −62.4 (−461.4 to 336.6) | 0.759 |
PORH index | 2.3±1.2 | 2.4±1.1 | −0.2 (−0.5 to 0.1) | 0.289 | 2.4±0.7 | 2.2±0.6 | 0.2 (−0.1 to 0.5) | 0.207 |
Mean minimum inspiratory values | 51.3±37.4 | 65.3±44.9 | −13.4 (−25.0 to −1.8) | 0.023 | 104.3±58.5 | 100.6±43.1 | 3.7 (−7.8 to 15.2) | 0.526 |
GFR | 11.0±13.9 | 47.5±24.7 | −36.5 (−44.2 to −29.0) | <0.001 | - | - | - | - |
Creatinine (mg/dL) | 8.2±3.8 | 2.6±2.9 | 5.6 (4.0 to 7.0) | <0.001 | - | - | - | - |
Hemoglobin (mg/dL) | 9.7±2.8 | 11.1±2.3 | −1.5 (−2.6 to −0.4) | 0.016 | - | - | - | - |
Week one, during the week of transplantation; three months, 3 months after first evaluation; SD, standard deviation; RF, resting flow; PL, peak flow; PF/RF, ratio between peak flow and resting flow; HA, hyperemic area; PORH index, post-occlusive reactive hyperemia index; GFR, glomerular filtration rate.
Finally, microvascular reactivity was evaluated following kidney transplantation at time point 2 in the case group according to the occurrence of postoperative endpoints (early anemia and acute rejection), as well as the eGFR. No statistically significant difference was found in the LDF microcirculatory parameters evaluated at 3 months after transplantation (Table 4). A graphic abstract with the main findings of the study and the correlating tests from which they were obtained is shown in Figure 2.
Parameters . | Early anemia present (mean±SD) (N = 32) . | Early anemia absent (mean±SD) (N = 8) . | Difference means (95% CI) . | p value . |
---|---|---|---|---|
RF | 28.9±56.1 | 19.2±10.2 | 9.7 (−5.1 to 35.2) | 0.218 |
PF | 122.0±98.7 | 97.0±62.3 | 25.0 (−33.0 to 73.0) | 0.438 |
PF/RF ratio | 6.1±4.2 | 5.8±4.0 | 0.3 (−3.1 to 2.9) | 0.884 |
HA | 1,922±1,434 | 1,542±1,713 | 379 (−1,055 to 1,350) | 0.708 |
POHR index | 2.4±0.92 | 2.5±1.81 | −0.1 (−1.5 to 0.9) | 0.869 |
Mean minimum inspiratory values | 57.9±35.3 | 93.7±66.5 | −35.8 (−81.0 to 7.6) | 0.155 |
Parameters . | Early anemia present (mean±SD) (N = 32) . | Early anemia absent (mean±SD) (N = 8) . | Difference means (95% CI) . | p value . |
---|---|---|---|---|
RF | 28.9±56.1 | 19.2±10.2 | 9.7 (−5.1 to 35.2) | 0.218 |
PF | 122.0±98.7 | 97.0±62.3 | 25.0 (−33.0 to 73.0) | 0.438 |
PF/RF ratio | 6.1±4.2 | 5.8±4.0 | 0.3 (−3.1 to 2.9) | 0.884 |
HA | 1,922±1,434 | 1,542±1,713 | 379 (−1,055 to 1,350) | 0.708 |
POHR index | 2.4±0.92 | 2.5±1.81 | −0.1 (−1.5 to 0.9) | 0.869 |
Mean minimum inspiratory values | 57.9±35.3 | 93.7±66.5 | −35.8 (−81.0 to 7.6) | 0.155 |
. | Acute rejection present (mean±SD) (N = 20) . | Acute rejection absent (mean±SD) (N = 20) . | . | . |
---|---|---|---|---|
RF | 38.7±69.8 | 25.2±1.28 | 13.5 (4.3 to 64.2) | 0.086 |
PF | 133.4±100.3 | 100.7±83.2 | 32.7 (−24.0 to 87.3) | 0.263 |
PF/RF ratio | 5.3±2.8 | 6.8±5.0 | −1.5 (−4.2 to 0.8) | 0.206 |
HA | 2,088±1,654 | 1,604±1,275 | 484 (−385.2 to 1,411.8) | 0.291 |
POHR index | 2.3±0.9 | 2.6±1.3 | −0.3 (−1.1 to 0.3) | 0.265 |
Mean minimum inspiratory values | 66.5±36.0 | 63.9±53.7 | 2.6 (−27.9 to 28.4) | 0.891 |
. | Acute rejection present (mean±SD) (N = 20) . | Acute rejection absent (mean±SD) (N = 20) . | . | . |
---|---|---|---|---|
RF | 38.7±69.8 | 25.2±1.28 | 13.5 (4.3 to 64.2) | 0.086 |
PF | 133.4±100.3 | 100.7±83.2 | 32.7 (−24.0 to 87.3) | 0.263 |
PF/RF ratio | 5.3±2.8 | 6.8±5.0 | −1.5 (−4.2 to 0.8) | 0.206 |
HA | 2,088±1,654 | 1,604±1,275 | 484 (−385.2 to 1,411.8) | 0.291 |
POHR index | 2.3±0.9 | 2.6±1.3 | −0.3 (−1.1 to 0.3) | 0.265 |
Mean minimum inspiratory values | 66.5±36.0 | 63.9±53.7 | 2.6 (−27.9 to 28.4) | 0.891 |
. | GFR ≤60 (mean±SD) (N = 27) . | GFR >60 (mean±SD) (N = 13) . | . | . |
---|---|---|---|---|
RF | 28.9±60.7 | 23.1±15.8 | 5.8 (−10.9 to 40.0) | 0.530 |
PF | 102.5±81.6 | 147.1±109.2 | −44.6 (−111.9 to 15.6) | 0.167 |
PF/RF ratio | 5.4±2.9 | 7.4±5.8 | −2.0 (−6.1 to 0.5) | 0.150 |
HA | 1,522±1,448 | 2,519±1,875 | −997 (−2,043 to 80) | 0.065 |
POHR index | 2.4±1.2 | 2.5±1.1 | −0.1 (−0.9 to 0.6) | 0.706 |
Mean minimum inspiratory values | 66.6±45.7 | 62.6±44.8 | 4.0 (−24.3 to 33.5) | 0.813 |
. | GFR ≤60 (mean±SD) (N = 27) . | GFR >60 (mean±SD) (N = 13) . | . | . |
---|---|---|---|---|
RF | 28.9±60.7 | 23.1±15.8 | 5.8 (−10.9 to 40.0) | 0.530 |
PF | 102.5±81.6 | 147.1±109.2 | −44.6 (−111.9 to 15.6) | 0.167 |
PF/RF ratio | 5.4±2.9 | 7.4±5.8 | −2.0 (−6.1 to 0.5) | 0.150 |
HA | 1,522±1,448 | 2,519±1,875 | −997 (−2,043 to 80) | 0.065 |
POHR index | 2.4±1.2 | 2.5±1.1 | −0.1 (−0.9 to 0.6) | 0.706 |
Mean minimum inspiratory values | 66.6±45.7 | 62.6±44.8 | 4.0 (−24.3 to 33.5) | 0.813 |
Discussion
The evaluation of microvascular reactivity revealed a significantly enhanced rest flow and sympathetic vasoconstrictor response (lower mean minimum IBH values measured at the fingertip) in the CKD cases group compared to the non-CKD controls at both time points evaluated. However, there was no difference between CKD case and non-CKD groups regarding the PORH index. Only a few articles have assessed PORH index in order to study endothelial function in patients with CKD, and the results are controversial [33, 34]. In the intragroup analysis, the comparison of the two time points within each group showed a significant increase in the sympathetic vasoconstrictor response in microvascular reactivity in the CKD case group. In the non-CKD controls, there were no alterations to the LDF measurements. The laboratory parameters (creatinine, eGFR, and hemoglobin) were significantly lower 3 months after kidney transplantation.
The IBH stimulus with LDF evokes a skin vasomotor response that has been well validated. An IBH can elicit a rapid and transient sympathetically mediated vasoconstriction that can be detected in the cutaneous micovasculature of the fingertip pulp [35, 36]. Our finding showing an increase in the sympathetic vasoconstrictor response to IBH after kidney transplant may indicate better autonomic function. Autonomic dysfunction has been identified as an important contributor to the increased CVD in patients with CKD [37].
All the stages of CKD are associated with increased risks of major adverse cardiovascular events (MACE) and premature death. The pathophysiology of cardiovascular disease in patients with CKD remains to be completely clarified. Risk factors such as hypertension, diabetes, and hyperlipidemia are important; however, they do not fully explain the high prevalence of CVD in this population [4]. In recent decades, there has been growing interest in evaluating other mechanisms that could explain the wide spectrum of cardiovascular changes found in patients with CKD, including oxidative stress, endothelial dysfunction, anemia, inflammation, vascular calcification, and dysfunction of the autonomic nervous system [15]. Of these factors, autonomic dysfunction in uremia, anemia, and endothelial dysfunction, all present at every stage of CKD, merit particular mention; however, further clarification is required regarding their actual participation in the pathophysiology of CVD in the CKD patient [15, 32].
The present results showed the mean minimum IBH values measured at the fingertip (MediaInsp) to be lower in the patients with CKD compared to the controls, with this difference persisting even 3 months after transplantation, even though there has been a significant increase of the MediaInsp in the CKD group after the transplant. The measurement of mean inspiratory values during LDF registers the perfusion per unit of tissue volume over a unit of time. It represents sympathetically mediated vasoconstriction in response to breath holding. Results are expressed as PUs, which are strongly correlated with circulation, vary in time and space, and express fluctuations in tissue circulation caused by sympathetic vasomotor effects [26, 33].
Patients with CKD commonly present changes in the sympathovagal balance, i.e., autonomic dysfunction, characterized by increased sympathetic activity associated with a reduction in the parasympathetic tone [33, 38]. This condition triggers an increase in plasma and tissue catecholamine levels while simultaneously increasing resistance to its peripheral effect, i.e., there is a diminished response mediated by beta-adrenergic and muscarinic receptors [11, 38]. Therefore, autonomic dysfunction in uremia could presumably present as a reduction in mean minimum inspiratory values at LDF, more specifically, as a reduction in the vasoconstrictive response, since under these conditions there is a reduction in the sympathetic adrenergic component, whose activation results in the constriction of muscles containing the main component of the vascular reflex regulation, the neurotransmitter noradrenaline [38].
The possibility of using LDF to evaluate neurovascular innervation in humans has yet to be fully evaluated. A study conducted in 2004 examined the possibility of evaluating the sympathetic system from the perivascular innervation of the skin in the limbs using LDF. This method proved highly effective for characterizing the neuroregulation of the microvasculature. Therefore, the reduction in mean minimum inspiratory values would be related to a reduction in the arginine vasopressin test and may therefore be altered in patients with autonomic dysfunction in uremia [27]. Although the results of the present study do not permit associations to be established between alterations in mean minimum inspiratory values during evaluation of microcirculation by LDF and autonomic dysfunction in uremia, they do permit this hypothesis to be raised, serving to encourage future studies to be developed to evaluate the actual role of this exam in the diagnosis of this condition.
Kidney transplantation failed to improve mean minimum inspiratory values. Therefore, it does not appear to have increased the capacity of the vasoconstrictive response to stimulus, which could raise two hypotheses: transplantation is possibly incapable of reversing autonomic dysfunction in uremia, or 3 months of transplantation are insufficient to reverse the changes produced by CKD. The progression of this alteration following transplantation has yet to be established, probably due to the scarcity of well-conducted studies but also to the limited sensitivity of the specific tests used to diagnose autonomic dysfunction in uremia [39, 40].
Findings on the effect of kidney transplantation on autonomic dysfunction in uremia remain conflicting. Kidney transplantation has evolved dramatically, making it the best form of treatment for patients with CKD. In addition, it has been clearly established that patients who receive a kidney transplant have a 68% lower risk of death compared to those on dialysis awaiting transplantation [39, 40]. This would tend to support the hypothesis that the factors involved in cardiovascular risk, including autonomic dysfunction in uremia, are effectively controlled following organ transplantation. However, if little is known about the reversibility of uremic alterations following kidney transplantation, there is virtually no evidence at all on the time required following transplantation for complications to revert. In the present study, these parameters were evaluated only 3 months following transplantation, a period of time that may be insufficient to reveal a reversal of changes that have often been present for long periods of time.
In relation to the other parameters encompassed in the evaluation of microcirculation, the present findings differ from results reported in the literature. Most of the parameters measured at LDF (RF, PF, PF/RF ratio, HA, and PORH index) remained unchanged, contradicting some reports that endothelial dysfunction is present in end-stage CKD and constituting a relevant risk factor for cardiovascular events in these patients [41, 42]. The factor responsible for endothelial dysfunction in patients with end-stage renal disease may be asymmetric dimethylarginine, a potent inhibitor of endogenous nitric oxide synthase, raising the hypothesis of a close association between high asymmetric dimethylarginine levels and impaired endothelium-dependent vasodilation in these patients [8, 12, 41]. In the present study, no evidence was found of endothelial alterations in patients with CKD compared to the controls; however, the PF/RF ratio was slightly higher at time point 2 (3 months following transplantation). This alteration in itself may be unassociated with kidney transplantation or may be a result of the sample size, which was not calculated specifically for all the parameters of microcirculation evaluated by LDF.
We believe that these findings can serve as a basis for the design of future studies capable of evaluating the true potential of the use of LDF for the evaluation of microcirculation in the diagnosis and monitoring of patients with autonomic dysfunction in uremia. Furthermore, these results should encourage further, well-designed studies to be conducted to specifically evaluate whether mean inspiratory values are associated with autonomic dysfunction in uremia and to construct stratified values predictive of a risk of autonomic dysfunction in uremia or even of cardiovascular complications.
This study did not show any statistically significant differences in PORH parameters between the study group and the comparative group. This finding could be influenced by the insufficiently large group of patients participating in the study or the insufficient time of follow-up - only 3 months. PORH assessment with the LDF technique has been pointed out as a sensitive indicator of endothelial damage. However, it should be noted that the PORH mechanism has not been sufficiently explained, and the results of the LDF PORH study may be influenced by shear stress, NO release, and endothelium-dependent hyperpolarization [42‒44].
The strong points of the present study include the pioneering of a longitudinal cohort study design with CKD patients submitted to kidney transplantation and followed by microcirculation evaluation through LDF. In our literature review, we did not find similar studies. Furthermore, a paired comparison group was used, a valid alternative when randomization is impossible. Besides, some of the authors have experience with LCD studies [45].
One of the limitations of the study was the impossibility of evaluating the actual correlation between the evaluation of the autonomic component of microcirculation (measured by mean inspiratory values) and autonomic dysfunction in uremia since there is no validated test for the diagnosis of this condition; therefore, the accuracy of the mean inspiratory value for the diagnosis of autonomic dysfunction in uremia could not be assessed. Nevertheless, that was not the objective of the present study, and we believe that these findings will serve to encourage further studies in the area. Another limitation was that the compared patients have not undergone a major surgical procedure, a kidney transplant, and we do not know to what extent this intervention may influence the experiment at time point 1. Except for CKD, the compared patients had the same age, gender, and chronic diseases (systemic arterial hypertension, diabetes mellitus, and collagenoses) as the case group. Furthermore, we did not use the wavelet transform technique, a time-frequency method with logarithmic frequency resolution, used to analyze oscillations in human peripheral blood flow measured by LDF. We can also consider the short period of patient follow-up, just 3 months, and the small number of patients studied (80). However, there was a previous sample size calculation, and the COVID-19 pandemic made further patient follow-up unfeasible. In conclusion, LDF evaluation of microcirculation revealed significant abnormalities in patients with CKD who underwent kidney transplantation compared to those without CKD. Compared with controls with no CKD, in CKD patients undergoing kidney transplantation, microcirculation by LDF shows improvement after 3 months.
Statement of Ethics
This study protocol was reviewed and approved by Instituto de Medicina Integral Prof. Fernando Figueira (IMIP)’s Internal Review Board, Approval No. CAE -43929815800005201. Written informed consent was obtained from all participants.
Conflict of Interest Statement
The authors have no conflicts of interest to declare.
Funding Sources
No funding was received for this study.
Author Contributions
P.S.G.N.B. is the principal investigator of the study and takes full responsibility for the integrity and accuracy of the data. Study concept and design: P.S.G.N.B., J.G.B.A., and F.A.O. Data collection: P.S.G.N.B. and I.A.P. Data analysis and interpretation: P.S.G.N.B. and F.A.O. Drafting of the manuscript: P.S.G.N.B., I.A.P., J.G.B.A., F.A.O., and C.G.F. All authors read and approved the final manuscript.
Data Availability Statement
The data that support the findings of this study are not publicly available because their containing information that could compromise the privacy of research participants, but are available from the corresponding author (JGBA, e-mail: joaoguilherme@imip.org.br) upon reasonable request.