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. 2023 Jun 7;30(5-6):e12819. doi: 10.1111/micc.12819

The sublingual microcirculation and frailty index in chronic kidney disease patients

Ryan A P Homes 1,✉, Fiona Giddens 2, Ross S Francis 3,4, Ruth E Hubbard 2, Emily H Gordon 2, Mark J Midwinter 1
PMCID: PMC10909441  PMID: 37285445

Abstract

Objective

To examine the relationship between sublingual microcirculatory measures and frailty index in those attending a kidney transplant assessment clinic.

Methods

Patients recruited had their sublingual microcirculation taken using sidestream dark field videomicroscopy (MicroScan, Micro Vision Medical, Amsterdam, the Netherlands) and their frailty index score using a validated short form via interview.

Results

A total of 44 patients were recruited with two being excluded due to microcirculatory image quality scores exceeding 10. The frailty index score indicated significant correlations with total vessel density (p < .0001, r = −.56), microvascular flow index (p = .004, r = −.43), portion of perfused vessels (p = .0004, r = −.52), heterogeneity index (p = .015, r = .32), and perfused vessel density (p < .0001, r = −.66). No correlation was shown between the frailty index and age (p = .08, r = .27).

Conclusions

There is a relationship between the frailty index and microcirculatory health in those attending a kidney transplant assessment clinic, that is not confounded by age. These findings suggest that the impaired microcirculation may be an underlying cause of frailty.

Keywords: frailty, frailty index, kidney disease, microcirculation, sublingual

Abbreviations

AVA

automated vascular analysis

CKD

chronic kidney disease

FI

frailty index

FI‐SF

frailty index short form

HI

heterogeneity index

KTAC

kidney transplant assessment clinic

MFI

microcirculatory flow index

MIQS

microcirculatory image quality score

PAH

Princess Alexandra Hospital

PPV

portion of perfused vessels

PVD

perfused vessel density

SDF

sidestream dark field

TVD

total vessel density

1. INTRODUCTION

Frailty is a complex multimodal state, characterized by a decline in an individual's physiological reserve, leading to an increased vulnerability to stressors. 2 , 3 , 4 This reduction is secondary to a decrease in homeostatic signaling which disrupts an individual's ability to cope with acute stressors and compensate for cellular stress, leading to an increased risk of adverse outcomes such as death and functional dependence. 5 , 6 , 7 , 8 Patients with chronic kidney disease (CKD) have high rates of frailty. 9 In a predialysis CKD population, 65% of patients presented with moderate frailty, rising to 73% in a dialysis‐dependant CKD cohort. 10 , 11 Kidney transplant candidates experience higher rates of frailty that lead to greater health deterioration and mortality as compared to their nonfrail counterparts. 12 , 13 It is also a predictor of physiological reserve improvement after kidney transplantation. 14

Frailty can be assessed in clinical settings using a variety of validated tools, with the frailty index (FI) being a frequently employed method. 15 , 16 , 17 , 18 , 19 The FI represents the cumulative deficit model of frailty whereby the more problems an individual acquires, the more likely they are to be frail. The FI employs a well‐defined method to derive a score from a list of health deficits across multiple domains, including clinical signs and symptoms, diseases and disabilities. 17 , 20 , 21 The frailty index is a continuous variable (ranging from zero to one) with higher scores indicating higher frailty; however, individuals with an FI score >0.25 are typically categorized as being “frail”. 22 The FI predicts nursing home admission, mortality, and hospitalization in adult populations, including older adults with CKD. 10 The granularity of the FI makes it a useful tool to examine the pathophysiology of frailty. 23

As frailty is a loss of physiological reserve, the condition sees decline across multiple physiological systems (i.e., hormonal, musculoskeletal, etc). 24 The concept of physiological reserve quantifies the maximum additional work capacity a physiological system can produce under exposure to a stressor, in comparison to the basal work output needed to maintain homeostasis. 25 Frail patients use a greater proportion of their physiological capacity in maintaining homeostasis than nonfrail patients leaving them with limited reserve to respond to trivial insults, that can lead to decompensation. 26 , 27 At present, the underlying mechanisms responsible for the decline in physiological reserve, which are likely to be multifactorial, are poorly characterized at the cellular and tissue level.

The maintenance of physiological reserve across body systems depends on adequate functional parenchyma to undergo sufficient homeostatic metabolic exchange at a cellular level. This blood‐tissue interface occurs in the microcirculation, that encompasses a complex network of capillaries with associated arterioles and venules which are <20 μm in diameter. 28 The microcirculation is critical to the maintenance of tissue structure, function, and mass due to its integral role in the diffusion of gasses, nutrients, and metabolic products. Vascular endothelium lining is essential for the regulatory mechanisms that underlie strain/stress blood rheology and meeting the metabolic demands (e.g., O2 and CO2 perfusion) of surrounding tissues. 29 As parenchymal cells receive their metabolic support via the microcirculation, a dysfunction in this system can lead to a limitation in functional reserve. 30

At present, studies regarding microcirculatory dysfunction have been largely restricted to acute critical care settings such as sepsis or traumatic injuries, leading to complications such as multiple organ dysfunction. 31 , 32 In both states, the vascular endothelium is injured, leading to systemic organ impairment as a result of increased vascular permeability and/or dysregulation in vessel perfusion and oxygen delivery to the parenchyma. 33 A recent review of the mechanisms underlying vascular aging, highlighted a need to explore mechanistic changes to the microcirculation in complex states such as frailty. 34 While increasing in likelihood with aging, frailty is present in people who experience chronic organ failure. Individuals with CKD often produce higher rates frailty at younger ages. This study aimed to evaluate the associations between frailty as measured by the FI and microcirculatory parameters, in a cohort of patients with CKD or kidney failure attending the kidney transplant assessment clinic (KTAC).

2. METHODS

This cohort study was approved by the Metro South Health ethical research committee (Identifier: HREC/2021/QMS/69114).

2.1. Study population

Patients were recruited between May 2021 and July 2022 as a subset of a larger study at the Princess Alexandra Hospital (PAH) researching routine FI assessment in kidney transplant candidates. Of the 147 individuals recruited, 44 participants consented to the additional sublingual microcirculatory measures. Patients recruited were at least 18 years, were from an English‐speaking background (unless an interpreter was available), had any type of kidney disease and were dialysis independent or dependent. Exclusion criteria included severe cognitive or functional illness that would affect their participation in the study.

2.2. Sublingual microcirculation measures

Imaging of the sublingual microcirculation was conducted via sidestream dark field (SDF) videomicroscopy (MicroScan, Micro Vision Medical, Amsterdam, the Netherlands). Participants were positioned supine on a physiotherapy plinth, with the backrest elevated to 40 degrees (Figure 1). Five to ten video sequences, each of 5 sec duration, were captured from different sublingual sites in each subject using AVA4.3C [Automated Vascular Analysis (AVA) 4.0, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands] technology by a single investigator (RH). Video sequences were subsequently stored without analysis using pseudonymisation. AVA 3.2 [Automated Vascular Analysis (AVA) 3.0, Academic Medical Centre, University of Amsterdam, Amsterdam, the Netherlands] parameters were calculated using manual analysis techniques due to previously identified discrepancies with the automated 4th generation of AVA. 35 , 36 , 37 Microcirculatory clips were selected and analyzed based on the score outcomes (less than ten) of the Microcirculatory Image Quality Score (MIQS). 37 The MIQS took into consideration seven parameters: the duration, illumination, focus, content, stability, pressure, and vessel diameter (vessels <20 μm were examined exclusively) of each clip. Two participants were not considered due to MIQS scores exceeding 10. All chosen clips were analyzed to evaluate the microcirculation in accordance with the suggested parameters in the consensus literature. 38 These parameters included: total vessel density (TVD), perfused vessel density (PVD), the proportion of perfused vessels (PPV), microvascular flow index (MFI) score; and the heterogeneity index (HI). Small vessel blood flow was classified utilizing an ordinal scale were as follows: 0 = absent/no flow, 1 = intermittent flow/absence of flow 50% of clip duration, 2 = sluggish flow, and 3 = continuous flow, which enabled the generation of the MFI and HI. HI was quantified by calculating the difference between the extreme values of PPV across three recordings and dividing by the PPV mean value. 39 Microcirculatory analysis undertaken by a single trained observer, at minimum of 24 h following patients last dialysis session, blinded to FI scores and clinical information.

FIGURE 1.

FIGURE 1

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Participant with MicroScan sublingual microcirculatory probe. Figure 1A Shows the participant with the sublingual microcirculatory probe positioned on the sublingual mucosa of the tongue as shown in [1B]. Figure 1B adapted from. 1

2.3. Frailty Index

The frailty index short form (FI‐SF) was conducted via an in‐person interview. The FI‐SF evaluates a total of 58 variables that were recognized as “deficits”, and represented multiple health domains that included medical conditions, physiological function, and mental cognition. The FI was obtained by summing the “deficits” and dividing by the number of variables listed in the FI‐SF. This process was conducted in a digital format using the REDCap (Version 12.5.4, Vanderbilt University, Nashville, America) software system.

2.4. Statistical analysis

Statistical analysis was performed via GraphPad Prism 8.0.1 (GraphPad Software, San Diego, California USA) and R commander (Version 2.7‐x, Vienna, Austria, 2022). All microcirculatory parameters were assessed for distribution normality using q‐q plots and Shapiro–Wilk tests. Pearson Correlation coefficients with 95% confidence intervals were utilized for data exhibiting a normal distribution, whereas a nonparametric Spearman correlation test was performed on non‐normally distributed data. Statistical significance was set to p < .05.

3. RESULTS

Table 1 summarizes the demographics of 42 study participants. Seventy‐six percent of patients had stage 5 CKD and either undergoing peritoneal or hemodialysis, with 17% being predialysis. The remainder of patients were stage 4, not undergoing dialysis. Majority of the study population were of European decent (83%), had never smoked (50%), and did not have diabetes (81%). Hemodialysis (50%) was the most frequently used method of dialysis. Table 2 shows the median and interquartile range of the TVD, PVD, PPV, MFI and HI for the cohort. Potential relationships among frailty and the microcirculatory parameters were explored by a univariate Pearson correlation. Table 3 shows a significant negative correlation between the FI and all five microcirculatory measures (TVD: −0.56, MFI: −0.43, PPV: −0.52, HI: 0.32, PVD: −0.66). Notably, no significant correlation (r = .27) was observed between age and FI. The values obtained from Pearson's Coefficient of Determination (r 2) indicated that TVD, MFI, PVD, and age accounted for 31%, 19%, 43%, and 8% of the variance with reference to the frailty index (PPV and HI was performed using nonparametric testing).

TABLE 1.

Demographic frequency distribution of a renal transplant assessment population.

Parameters (N = 42) Median (IQR)
Age (years) 53 (45–64)
Height (meters) 1.70 (162–178)
Weight (kilogram) 79.8 (67–95)
Body mass index (kilogram/meter) 28.3 (24–30)
Frailty index 0.19 (0.15–0.30)
Sex N (%)
Male 22 (52.4%)
Female 20 (47.6%)
Ethnicity
White/European 35 (83.3%)
Asian 3 (7.1%)
Aboriginal or Torres Strait Islander 1 (2.3%)
Other 3 (7.1%)
Smoking status
Never 21 (50%)
Former 18 (42.9%)
Current 1 (2.3%)
No response 2 (4.8%)
Diabetes
Yes 8 (19.0%)
No 34 (81.0%)
Stage of kidney disease
CKD stage 4 3 (7%)
CKD stage 5 predialysis 7 (17%)
CKD stage 5 peritoneal dialysis 11 (26%)
CKD stage 5 hemodialysis 21 (50%)
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TABLE 2.

Microcirculatory measures of the renal transplant assessment population.

Parameters (N = 44) Median (IQR)
Total vessel density (MM/MM2) 17.23 (15–20.4)
Microcirculatory flow index (A.U) 2.4 (2.1–2.8)
Perfused vessel density (MM/MM2) 15.3 (13.1–17.6)
Portion of perfused vessels (%) 84.43 (78.6–92.6)
Heterogeneity index (A.U.) 0.13 (0.1–0.3)
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TABLE 3.

Correlation (Pearson) of microcirculatory parameters and FI.

R‐value (upper CI, lower CI) p‐value R 2
Age 0.27 (−0.03, 0.5) .08 .07
TVD (mm/mm2) ‐0.56 (−0.7, −0.3) .0001 .31
MFI (A.U) ‐0.43 (−0.7, −0.2) .004 .19
PVD (mm/mm2) −0.66 (−0.8, −0.4) <.0001 .43
PPV (%) a −0.52 (−0.7, −0.3) .0004 N/A
HI* 0.37 (0.1, 0.6) .015 N/A
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a

= indicates nonparametric test.

4. DISCUSSION

The findings demonstrate that across all microcirculatory parameters, there are significant negative associations between frailty index scores (Figures 2, 3). This relationship was not altered after adjustment for age (Figure 2F). These results indicate that among KTAC attendees, microcirculatory changes were more closely associated with declining physiological reserve than with increasing chronological age.

FIGURE 2.

FIGURE 2

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Scatter plot of microcirculation parameters versus frailty index in KTAC attendees. XY plot shows perfused vessel density (A), portion of perfused vessels (B), total vessel density (C), microvascular flow index (D), heterogeneity index (E) and age (F) and frailty index on the X and Y axes, respectively. Black dots represent numerical patient's data (n = 42).

FIGURE 3.

FIGURE 3

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Microcirculation of two KTAC attendees. Figure 3A illustrates the microcirculation of a KTAC attendee with a frailty index of 0.10. Figure 3B illustrates the microcirculation of an individual with a frailty index of 0.41. (A) shows a greater density and perfusion of microcirculatory vessels in comparison to (B).

The microcirculation has been studied extensively in acute settings, notably comparing the relationships between microcirculatory dysfunction and postoperative complications. 40 , 41 More recently, microcirculation has become of interest in chronic disease research. For example, in a study investigating the sublingual microcirculation of patients with liver cirrhosis, it was determined that cirrhotic patients had significantly lower microcirculatory health as compared with healthy counterparts. 42 Microcirculatory changes have become of significant interest in patients with acute or chronic kidney disease. Various techniques that align to the methods of this study have been utilized such as doppler flow and CytoCam incident dark field imaging. 42 , 43 , 44 For example, patients undergoing dialysis were demonstrated to have significantly reduced measures of microcirculatory health in both large (<50 μm) and small (>20 μm) vessels compared to healthy controls. 45 However, in a CKD population, no differences were observed in MFI, PPV, or PVD in younger (> 25 year) versus older (> 55 years) adults. 46 It is important to note that these studies investigated the differences among a healthy and kidney failure cohort with no evaluation of underlying frailty.

These insights influenced the design of the current study, which involved a relationship‐based investigation of the microcirculation using the frailty index as a continuous measure. Research investigating the implications of CKD on frailty has been shown using multiple methods, but minimal have used the FI as a continuous measure. 47 , 48 Although the median frailty index of the patients falls within the prefrail cutoff (FI = 0.19), it is important to note that categorical measures of frailty have limited validation across many settings. 49 Therefore, the use of continuous measures is recommended whenever possible. To our knowledge, this cohort study is the first investigation to study the relationships that exist between an individual's frailty index and their sublingual microcirculation.

The strongest relationship was observed between the FI and PVD, accounting for 43% of the variance (Figure 2A). This would seem logical as the maintenance of functional parenchyma would require a critical density and perfusion to support metabolic activity. The PVD findings in this study cohort may be due to dialysis induced deterioration of the endothelial glycocalyx, which is an essential subcellular structure that is located on the luminal surface of the vascular endothelium. 48 Nitric oxide production is also critical in maintaining microvascular perfusion and is linked to the endothelial glycocalyx and its role as a mechanoreceptor. Impaired PVD has been shown in other clinical settings (cardiopulmonary bypass and traumatic hemorrhage) to be related to loss of the glycocalyx. 50 , 51 Investigation of glycocalyx shedding may provide insights into the etiology of microcirculatory impairment and the development of frailty. 52 , 53 , 54 , 55

The current investigation has notable limitations that require consideration. It was not possible to investigate the effects of demographic factors such as sex, smoking status, dialysis time/type, and diabetes on the relationships highlighted in these works. Dialysis has also been shown to affect the microcirculation in terms of flow and proportion of vessels perfused. 45 , 56 However diabetic patients with cirrhosis have indicated no differences in the PVD, MFI, and PPV when compared to healthy controls. 46 Adjusting for these demographics, would help determine if they are contributing to the significant relationships between the FI and microcirculation.

The investigation exclusively analyzed the sublingual microcirculation, meaning there is an assumption that this would be representative of the systemic circulation more widely. Examination specifically of the microcirculation in the beds of the organ systems, including the kidney for comparison would be informative, but practically challenging. Further investigation would need to examine whether the relationship with the frailty index is confounded by organ etiology or being specific to the population studied in this cohort. One of the current study's strengths is that a relationship‐based investigation of the microcirculation using the frailty index as a continuous measure has been established.

In summary, this cohort study highlighted a significant negative relationship between frailty status (as determined by the frailty index) and sublingual microcirculatory health among KTAC candidates. The observed results were independent of an individual's chronological age. These findings will lay the foundations for future works that investigate the microcirculation as a potential underlying cause of frailty.

5. PERSPECTIVES

Renal transplantation can improve or reverse frailty; however, the underlying causes of this improvement remain largely unknown. 14 The observations of this study provide a potentially useful human model to investigate the biomedical mechanisms that underpin these improvements. These findings will be instrumental in shaping future studies such as a longitudinal investigation of effects of renal transplant on frail individuals.

CONFLICT OF INTEREST STATEMENT

The authors RH, MM, RF, and EG have no conflict of interest to disclose.

ACKNOWLEDGEMENTS

The authors would like to extend their thanks to Metro South Health for providing funding, as well as express gratitude to all those at the Princess Alexandra Hospital who contributed to the project. Open access publishing facilitated by The University of Queensland, as part of the Wiley ‐ The University of Queensland agreement via the Council of Australian University Librarians.

Homes RAP, Giddens F, Francis RS, Hubbard RE, Gordon EH, Midwinter MJ. The sublingual microcirculation and frailty index in chronic kidney disease patients. Microcirculation. 2023;30:e12819. doi: 10.1111/micc.12819

DATA AVAILABILITY STATEMENT

The data associated with the manuscript will be made available upon request.

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Data Availability Statement

The data associated with the manuscript will be made available upon request.

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