Peripheral tissue perfusion and associated factors in individuals with type 2 diabetes mellitus: cross-sectional study

doi:10.21203/rs.3.rs-2198110/v1

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Peripheral tissue perfusion and associated factors in individuals with type 2 diabetes mellitus: cross-sectional study

https://doi.org/10.21203/rs.3.rs-2198110/v1

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Background: Early recognition of peripheral tissue perfusion deficits can minimize secondary complications of peripheral arterial disease in individuals with diabetes.

Aims: To compare peripheral tissue perfusion of the lower limb between individuals with type 2 diabetes (T2DM) without apparent vascular disease and apparently healthy individuals and to evaluate factors associated with peripheral tissue perfusion.

Methods: 62 individuals participated in this study: 31 with T2DM and 31 apparently healthy individuals. In both groups, anthropometric measurements and physical activity levels were evaluated. Peripheral tissue perfusion was analyzed using near-infrared spectroscopy during the arterial occlusion maneuver and the Incremental Shuttle Walking Test.

Results: The tissue oxygen saturation (StO₂) level during progressive effort was lower in the T2DM group (T2DM, 58.74 [56.27–61.74]; healthy, 62.15 [59.09–66.49]; p = 0.005). There were significant correlations between the StO₂ level during progressive effort and physical activity level (p < 0.0001; r = -0.681), total body fat percentage (p = 0.001; r = 0.590), segmental body fat percentage (p < 0.0001; r = 0.616), total skeletal muscle mass (SMM; p < 0.0001; r = -0.628), and segmental SMM (p = 0.001; r = -0.592).

Conclusions: There is a change in tissue perfusion of the lower limb in individuals with T2DM and simple measures can help understand tissue microcirculation in this group, allowing clinical conduct to anticipate vascular complications.

Lower member

Microcirculation

Near-infrared spectroscopy

Type 2 diabetes mellitus.

The International Diabetes Federation estimates that in 2045, there will be a 46% increase in people worldwide with diabetes compared to 2021 [1]. Peripheral arterial disease (PAD) is one of the main factors responsible for the morbidity and mortality of individuals with diabetes [2]. The main cause of PAD is atherosclerosis, which, despite being a widespread process, is more common in individuals with diabetes [3, 4]. PAD is present in 50% of individuals with diabetes, who manifest PAD 5–10 times greater than that of non-diabetics [5].

It is important to highlight that more than 50% of PAD cases are asymptomatic, consequently undiagnosed, and untreated and that although most of them do not develop a serious disease, it may indicate impaired general vascular health and predict future lethal events [6]. In addition, PAD in individuals with diabetes has faster progression and worse outcomes [7].

Thus, despite the clinical importance of detecting early changes related to PAD in individuals with diabetes, the diagnostic methods widely use peripheral blood pressure measurement, which may not be reliable in individuals with diabetes due to the calcification of blood vessels [8]. In this sense, the evaluation of tissue oxygen saturation (StO₂) in symptomatic and asymptomatic diabetic patients stands out since early recognition of perfusion deficits can reduce or prevent PAD complications in individuals with diabetes, such as ulcers and diabetic foot [3]. Therefore, the growing interest in methods assessing tissue perfusion in conditions of rest and exertion in individuals with diabetes is justified [4, 9]. Of these methods, near-infrared spectroscopy (NIRS), which allows continuous and non-invasive monitoring, stands out [8].

However, in the clinical context, NIRS has not yet been used regularly for the diagnostic investigation of early metabolic and vascular changes in individuals with diabetes, especially type 2 diabetes [8], probably because of the necessary financial investment and the increased demand for time in attendance. Therefore, understanding whether there is an association between simple routine measures and peripheral tissue perfusion could assist in clinical practice and add information about tissue microcirculation in these individuals. However, before considering the associations, it is necessary to understand whether there is a difference in the tissue perfusion pattern between healthy individuals and individuals with type 2 diabetes (T2DM) without apparent vascular disease since the studies that exist from this perspective have not evaluated type 2 diabetes,10 either they did not assess the musculature most affected by PAD [10, 11] or they did not assess the situation at rest [12, 13].

Therefore, the objectives of this study were (1) to compare parameters of peripheral tissue perfusion of the lower limb at rest and during and after progressive effort between individuals with T2DM without apparent vascular disease and apparently healthy individuals and (2) to evaluate the factors associated with peripheral tissue perfusion of the lower limb in individuals with T2DM during progressive effort. The hypothesis of this study was that even without PAD, individuals with diabetes have less capillary volume expansion caused by impaired vasodilation due to endothelial dysfunction.

This cross-sectional observational study was approved by the Ethics and Research Committee of the Federal University of Minas Gerais (approval number: 2.395.601; CAAE, 78445417.1.0000.5149), as determined in resolution 466/12 of the National Health Council, which is in accordance with the Declaration of Helsinki. All participants gave their informed consent for inclusion before they participated in the study.

Sample

A total of 62 individuals voluntarily participated in this study, 31 with T2DM and 31 apparently healthy individuals, matched by sex, age (± 3 years), and body mass index (BMI) (± 3 kg/m²).

For the T2DM group, individuals of both sexes were included, with a medical diagnosis of type 2 diabetes, above 18 years of age, without musculoskeletal changes or comorbidities that prevented physical effort, and with medical clearance to participate in the study. Two individuals were excluded from the sample: one with a resting ankle-brachial index (ABI) value below 0.90 and one with a resting ABI > 1.40. For the healthy group, individuals of both sexes were included: apparently healthy; between 30 and 79 years of age; non-smokers; and without a diagnosis of diabetes, systemic arterial hypertension, kidney disease, symptoms of angina and intermittent claudication, or any musculoskeletal changes that prevent physical exertion. Two individuals who were unable to understand or perform any of the proposed tests were excluded from the sample.

For the sample calculation, a previous correlation study was considered as a reference [9], from which an average correlation coefficient (r) of 0.50 was obtained. For the calculation, an alpha of 5% (Z_α = 1.960) and a power of 80% (Z_β = 0.842) were considered, and applying the equation [14] N=[(Z_α+Z_β)/C]²+3, where C = 0,5*In[(1 + r)/(1-r)], a sample size of 29 individuals per group was obtained.

Measures and instruments

Figure 1 shows the flowchart of the assessment steps for both groups. After 10 min of rest in the supine position, participants in the T2DM group were subjected to an ABI evaluation according to the guidelines in the literature [15, 16]. The lowest ABI value was used for the analysis of the results.

As part of the anthropometric assessment, the waist, hip, and abdominal circumferences were measured with a tape measure (Cescorf®, Brazil) according to the International Society for the Advancement of Kinanthropometry (ISAK) [17], and routine biochemical tests (fasting blood glucose, glycated haemoglobin [HbA1c], total cholesterol and cholesterol fraction, and triglyceride levels) were performed within a maximum interval of 3 months from the date of the evaluation.

In the anthropometric evaluation of both groups, height was measured using a Balmak 111 scale stadiometer (Balmak Balanças®, Brazil), and body mass and composition were assessed using the InBody R20 bioimpedance scale (InBody®, Korea). Physical activity level was assessed by the activity-adjusted score (AAE) from the Human Activity Profile (HAP). The HAP is an instrument composed of 94 items, arranged numerically in increasing order of energy expenditure. For each of them, there are three possible answers: “I still do”, “I stopped doing it” or “I never did”. From each answer, the AAE is calculated by subtracting from the number corresponding to the activity with the highest oxygen demand that the individual “still does” the number of items that the individual “failed to do”, before the last one that he "still does" [18].

For the evaluation of tissue perfusion, a NIRS device with a portable continuous wave system (PortaMon System, Artinis®, the Netherlands) was used, which utilizes the emission of light in two wavelengths (760 and 850 nm) to measure the concentrations of oxyhaemoglobin and deoxyhaemoglobin and calculate StO₂. Before starting the evaluation with NIRS, the skinfold of the medial region of the sural triceps was measured to assess the local adipose layer. For this measurement, a Cescorf® scientific adipometer was used, and the measurement procedure proposed by the ISAK was adopted [17]. Then, the NIRS sensors were positioned on the medial gastrocnemius muscle of the dominant leg, self-reported by the participant, and fixed with plastic wrap and an elastic band.

Procedures with NIRS

For the assessment of StO₂ values at rest, the individuals remained at rest for 10 min in the supine position, and then they were submitted to an arterial occlusion maneuver, which consisted of a cuff positioned on the distal third of the participant’s thigh, which was inflated to values greater than 250 mmHg and maintained for a period of 5–6 min [19]. During and after this procedure, the following values were recorded: StO₂ value immediately before (StO_{2 − basal}), lowest achieved StO₂ value (StO_{2 − minor}), deoxygenation rate (Tx-desox; ratio of the difference between StO_{2 − basal} and StO_{2 − minor} and the time spent in seconds to reach StO_{2 − minor}), and reoxygenation rate (Tx-reox; ratio of the difference between StO_{2 − basal} and StO_{2 − minor} and the time spent to reach StO_{2 − basal}).

After the NIRS assessment at rest, 10 min later, the participants were continuously monitored and were asked to perform the Incremental Shuttle Walking Test (ISWT) [20], a 12-stage progressive walking speed test, performed over a 10-meter course, and with a change of direction based on the guidance of different sound signals. For this test, the heart rate (HR) was continuously monitored using a heart rate monitor (Polar® model FT1, Finland) and recorded at the beginning, at the end of each stage, at the end of the test, and the end of the first minute of recovery. Blood pressure (BP) was recorded before the test, at the end of the test, and after recovery using a sphygmomanometer and stethoscope (PA Med®, Brazil). The test was interrupted due to failure to follow the course (not reaching the cone) for two consecutive times [21] or when the HR reached a value greater than 85% of the maximum,20 calculated using the following formula: 208 − (0.73 × age in years) [22]. During and after ISWT, peripheral tissue perfusion variables were recorded from the NIRS: StO_{2 − basal}, StO_{2 − minor}, Tx-desox, Tx-reox, and resistance time (T-resist) – time elapsed in seconds after the individual reached the lowest StO_{2 − minor} until the end of the test. All NIRS data were collected, stored, viewed, and analyzed using the OxySoft software® application.

T2DM: type 2 diabetes; ABI: ankle-brachial index; AOM: arterial occlusion manoeuvre; HAP: Human Activity Profile; ISWT: Incremental Shuttle Walking Test; NIRS: near-infrared spectroscopy

Statistical analysis

Data normality was analyzed using the Shapiro-Wilk test. The sample’s descriptive data are presented as mean and standard deviation. The results of peripheral tissue perfusion are expressed in the median and interquartile range (25–75). For the comparison between groups of parametric variables, the t-test was performed for independent samples, and for the non-parametric variables, the Mann-Whitney U test was performed. For association analysis, Spearman’s correlation coefficients were calculated. An alpha value of 5% was considered significant. The Statistical Package for Social Sciences (SPSS 21.0, Chicago, IL, USA) was used for the data analysis.

Sample characteristics

Thirty-one subjects were evaluated in each group. Each sample group comprised 17 women (55%) and 14 men (45%). Table 1 shows the general characteristics of the sample. Table 2 shows the specific data for the group with type 2 diabetes.

ISWT data

During ISWT, the median of the HR variation (∆) (type 2 diabetes, 42 [33–65 bpm]; healthy, 54 [41–71 bpm]; p = 0.049) and ∆SBP (type 2 diabetes, 20 [10–40 mmHg]; healthy, 35 [20–50 mmHg]; p = 0.048) were significantly different between groups, while the ∆DBP (type 2 diabetes, 0 [-10–0 mmHg]; healthy, 0 [-10–0 mmHg]; p = 0.562) was similar between the two groups.

NIRS data

Table 3 shows the comparison of peripheral tissue perfusion values between the T2DM and healthy groups, indicating that StO_{2 − minor} during ISWT was lower in the T2DM group (p = 0.005).

Since StO2_− minor during ISWT was the only statistically different peripheral perfusion variable between groups with T2DM and healthy, its association with simple routine measures for individuals with T2DM was verified. Figure 2 shows the scatter plots with significant correlations between the StO_{2 − minor} during ISWT and some simple routine measures. Other simple routine measures tested were as follows: diagnosis time (p = 0.661; r = 0.084), smoking (p = 0.080; r = -0.324), BMI (p = 0.535; r = 0.118), waist-to-hip ratio (p = 0.215; r = -0.233), abdominal circumference (p = 0.789; r = 0.051), fasting blood glucose (p = 0.517; r = 0.128), HbA1c (p = 0.880; r = -0.029), total cholesterol (p = 0.061; r = 0.352), high-density lipoprotein (p = 0.623; r = 0.097), and low-density lipoprotein (p = 0.351; r = 0.183).

Table 1

Demographic and clinical characteristics and physical activity level in type 2 diabetes and healthy groups
Variables	T2DM (n = 31)	Healthy (n = 31)	p
Age (years)	60.74 ± 10.18	60.23 ± 10.33	0.844
BMI (kg/m²)	30.50 ± 5.30	29.55 ± 4.75	0.458
TS (mm)	15.01 ± 9.36	19.07 ± 12.45	0.152
BFP total (%)	36.58 ± 9.67	35.97 ± 8.70	0.794
BFP segmental (%)	33.61 ± 9.43	33.46 ± 8.89	0.939
Total SMM (kg)	27.77 ± 6.93	26.95 ± 6.31	0.631
Segmental SMM (kg)	7.22 ± 1.84	7.11 ± 1.71	0.803
HAP	76.16 ± 7.63	82.16 ± 9.11	0.007*
ISWT (m)	435.16 ± 132.39	472.58 ± 136.19	0.277
Data are presented as mean ± standard deviation. * p ≤ 0.05. T2DM: type 2 diabetes; BFP: body fat percentage; BMI: body mass index; HAP: adjusted score of the Human Activity Profile; ISWT: distance covered in the test; SMM: skeletal muscle mass; TS: tricipital skinfold

Table 2

Clinical characteristics of the type 2 diabetes group (N = 31)
Variables	T2DM
Diagnostic time (years)	8.46 ± 5.72
ABI	1.11 ± 0.10
WHR	0.94 ± 0.83
Abdominal circumference (cm)	99.53 ± 20.08
Glucose fasting (mg/dL)	148.45 ± 61.65
Total cholesterol (mg/dL)	198.03 ± 32.00
HDL (mg/dL)	56.24 ± 14.37
LDL (mg/dL)	107.82 ± 36.79
Triglycerides (mg/dL)	146.07 ± 60.02
HbA1c (mmol/mol) HbA1c (%)	55 ± 10.16 7.14 ± 1.32
Smoker (%)	2 (6.50)
Drugs
Beta-blocker (%)	8 (25.80)
Antihypertensive (%)	19 (61.30)
Hypoglycaemic (%)	31 (100.00)
Insulin (%)	3 (9.70)
Data are presented as mean ± standard deviation and as absolute and relative frequencies. T2DM: type 2 diabetes; ABI: ankle-brachial index; WHR: waist-to-hip ratio; HDL: high-density lipoprotein; LDL: low-density lipoprotein; HbA1c: glycated haemoglobin

Table 3

Comparison between groups of peripheral tissue perfusion values
	Variables	T2DM (n = 31)	Healthy (n = 31)	P
AOM	StO_{2 − basal} (%)	65.01 (63.51–67.49)	64.77 (62.25–68.64)	0.540
	StO_{2 − minor} (%)	55.71 (50.27–59.58)	54.81 (45.60–59.81)	0.668
	Tx-desox (%/s)	0.03 (0.02–0.05)	0.34 (0.25–0.61)	0.218
	Tx-reox (%/s)	0.36 (0.23–0.41)	0.42 (0.17–0.55)	0.606
ISWT	StO_{2 − basal} (%)	66.62 (63.36–69.16)	68.72 (63.67–71.08)	0.113
	StO_{2 − minor} (%)	58.74 (56.27–61.74)	62.15 (59.09–66.49)	0.005*
	Tx-desox (%/s)	0.02 (0.01–0.03)	0.02 (0.01–0.03)	0.179
	Tx-reox (%/s)	0.08 (0.05–0.20)	0.11 (0.05–0.26)	0.762
	T-resist (s)	76.51 (51.06–96.20)	78.07 (46.24–125.83)	0.080
Data are presented as median and interquartile range. * p ≤ 0.05. T2DM: type 2 diabetes; AOM: arterial occlusion manoeuvre; ISWT: Incremental Shuttle Walking Test; StO_{2 − basal}: value immediately before; StO_{2 − minor}: lowest value reached; Tx-desox: ratio of the variation between StO_{2 − basal} and StO_{2 − minor} on the time in seconds to reach StO_{2 − minor}; T-resist: time elapsed in seconds after the individual reached the StO_{2 − minor} until the end of the test

BFP: body fat percentage; HAP: adjusted score of the Human Activity Profile; ISWT: mental shuttle walking test; SMME: skeletal muscle mass; StO_{2 − mInor}: lowest value reached

The main findings of this study were the significantly lower value of StO_{2 − minor} during physical effort in the T2DM group compared to that in the healthy group and the significant association of moderate magnitude between this variable and the adjusted HAP score, total BFP, segmental BFP, total SMM, and segmental SMM.

In a recent study using NIRS, Manfredini et al. [23] assessed individuals with PAD with and without diabetes and identified a report of late lameness in the presence of diabetes, with a significantly lower degree of oxygenation in the medial gastrocnemius muscle compared to individuals with PAD alone. Considering these results and that muscle hypoxia can impair the performance of functional tasks and balance [23], the present study stands out in identifying that individuals with diabetes, asymptomatic and without apparent PAD, present worse peripheral tissue perfusion of the lower limbs. This indicates that it is possible to intervene early upon the appearance of functional limitations and mitigate their complications.

In a previous study, Mohler et al. [12] assessed blood volume during exercise using NIRS and reported for the first time that the expansion of blood flow in individuals with T2DM without PAD during exercise was smaller than that in individuals with PAD alone. This indicates that a unique aspect of individuals with diabetes is the impairment of blood volume during exercise [12]. This behavior is similar to the results observed in the present study, i.e. the lower value of StO_{2 − minor} during progressive effort in the T2DM group. This finding reinforces the hypothesis that, even without PAD, individuals with diabetes have less capillary volume expansion caused by impaired vasodilation due to endothelial dysfunction [24]. Therefore, there is a deficiency in the oxygen supply to the active muscles. In addition, the group of healthy people showed a greater variation in SBP compared to physical exertion, which reflects their better cardiac function [25].

Other studies have evaluated the behavior of peripheral tissue perfusion during exercise in individuals with T2DM using NIRS [11, 26]. However, these studies [11, 26] corroborate that muscle oxygenation is impaired in T2DM individuals concerning to healthy ones. According to Barker et al. [27], tissue perfusion values differ between different anatomical points. Therefore, the current study is important in understanding the tissue perfusion of the muscle most affected by peripheral atherosclerotic phenomena, the sural triceps [28], and mainly because it is assessed in a more functional activity such as walking.

Manfredini et al. [29], in their study, evaluated the metabolism of the medial gastrocnemius in individuals with PAD concerning to healthy individuals. This study [29] observed a compensatory response to a significant increase in HR in the group with PAD, even with 21% of this group using beta-blockers, thus maintaining the same volume of local blood in relation to healthy ones. This increase in microvascular blood flow is expected due to the compensatory mechanism in response to impaired blood flow in the larger arterial vessels; however, individuals with diabetes are not able to adjust their cardiac output [30]. This can be seen in the present study since the HR variation during effort was significantly lower in the group with T2DM than that in the healthy group. However, another possible explanation for this behavior is the use of beta-blockers, a class of drugs that reduce HR [31], by 25.80% of the group with diabetes.

Another significant difference found in the present study was the lower physical activity level in the group with T2DM compared to the healthy group. This difference is expected because there is a decrease in physical activity among individuals with diabetes due to greater difficulty in exercising [32]. This may be because these individuals have fewer type I muscle fibers (mitochondrial dysfunction), or because they have a decreased microvascular response in the lower limbs during exercise [30]. Thus, peripheral impairments, not only central limitations, are important contributors to low physical fitness in individuals with diabetes [9]. However, despite the statistical difference in the physical activity level, both groups had the same classification, being considered active (adjusted HAP score > 74) [18], which indicates that even in physically active individuals, peripheral tissue perfusion in individuals with diabetes type 2 is worse.

Thus, the same classification of the physical activity level can justify the similar functional capacity between the groups, which was directly measured by the distance covered in the ISWT. Another possible reason for this result is that the group with T2DM selected for the study did not present vascular alterations in the ABI. Otherwise, the common microvascular stiffness in individuals with symptomatic diabetes limits the delivery of oxygen to skeletal muscles, inducing early fatigue during exercise [9].

Considering that StO₂ is the most important direct parameter in clinical practice [33], but assessment is not always possible, in the present study, we highlight the inverse correlation between the value of the lowest StO₂ during progressive effort in the T2DM group and the adjusted HAP score. This correlation probably occurs because a higher physical activity level in individuals with diabetes may indicate adaptations resulting from exercise, such as neovascularization and increased mitochondrial capacity [34], and also because the level of training interferes with the degree of deoxygenation of the skeletal muscles [35].

Another measure of easy clinical application that showed a direct correlation with the StO_{2 − minor} during the ISWT was the BFP, total and segmental, with a correlation of greater magnitude in the segmental measurement. This correlation probably occurs because the thickness of the adipose tissue, especially that underlying the positioning of the NIRS, overestimates the values of StO₂ [36], which in this case can be extrapolated to the value of BFP, and, more significantly, the segmental BFP that corresponds only to the evaluated lower limb. In this sense, studies have shown that body fat is directly associated with a lower supply of muscle oxygen [37, 38], since the adipose tissue has a lower metabolic rate and less blood flow; consequently, the changes in the NIRS signal are less [35]. Furthermore, according to a recent study [39], insulin resistance, a common consequence of this accumulation of fat and cause of type 2 diabetes, is associated with a decrease in the microvascular response during brachial artery occlusion, which indicates changes in microvascular function even before the development of hyperglycemia. Therefore, a limitation of the present study was the lack of insulin resistance assessment as part of the biochemical tests of the T2DM group, which could be a potential factor associated with peripheral tissue perfusion of the lower limbs in these individuals during progressive effort.

Finally, an inverse correlation was observed between SMM, total and segmental, and StO_{2 − minor} during ISWT, which may be due to the higher metabolic demand of SMM. This behavior can be more specifically explained considering the segmental SMM, since this correlation represents hyperaemia in the active muscle during exercise, which means that the greater the SMM, the greater the blood flow at the site [40], thus favouring tissue perfusion and resulting in a lower StO₂ value during the ISWT.

The behavior observed indicates some early change regarding the health condition, be it in the mitochondrial function or in the microvascular response of the lower limbs, which still does not have clinical repercussions, but deserves attention and a more thorough assessment. Additionally, to assist in clinical practice, simple routine measures such as the physical activity level and body composition can help understand the tissue microcirculation in individuals with T2DM without apparent vascular changes, thus allowing clinical conduct to anticipate vascular complications.

Conflict of interest

The Authors declare that they have no conficts of interests in this work.

Ethical Standard Statement

The study protocol was in accordance with the Declaration of Helsinki as revised in 2000 and was approved by the Institutional Review Board.

Informed consent

All participants gave their informed consent for inclusion before they participated in the study.

Acknowledgments

The authors would like to thank the Universidade Federal de Viçosa - Campus Florestal, especially the Physical Education Course for physical space and materials available for this study.

Funding source

This work was supported by Fundação de Amparo à Pesquisa do Estado de Minas Gerais - FAPEMIG [grants: Programa Pesquisador Mineiro PPM-00369-18 and CDS - APQ-02820-12]; Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq [grant 307597/2011-3] and PROEX/CAPES [grant 23038.002321/ 2020-79].

CRediT authorship contribution statement

VCF: conceptualization, methodology, formal analysis, investigation, interpretation of results, and writing of the original draft.

GAP: interpretation of results and writing of the original draft.

JSAF and TEOC: investigation.

DAGP: conceptualization, methodology, formal analysis, investigation, interpretation of results, writing of the original draft, and project administration.

All authors: read and approved the final version of the manuscript.

Conflict of Interest: None.

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Peripheral tissue perfusion and associated factors in individuals with type 2 diabetes mellitus: cross-sectional study

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Introduction

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Measures and instruments

Procedures with NIRS

Statistical analysis

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ISWT data

NIRS data

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