Use Of Continuous Glucose Monitoring in The Assessment And Management Of Patients With Diabetes And Chronic Kidney Disease

GLYCEMIC PROFILES OF PATIENTS ON DIALYSIS 

CGM systems provide comprehensive 24-hour profiles for the assessment of relationships between glycemic variation, timing of dialysis regimens, and insulin administration. In addition to the aforementioned CGM metrics, most CGM systems now provide standardized ambulatory glucose profiles (AGPs) which provide a graphical representation of 24-hour sensor glucose trends. Table 3 summarizes evaluation studies of CGM in patients on HD or PD.

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GLYCEMIC PROFILES DURING HEMODIALYSIS (HD)

In patients on HD, the composition of the dialysate and dialysis membrane both contribute to glycemic variability during HD and in the post-HD period. Differences in glucose profiles have also been reported between HD and non-HD days. The phenomenon of "glycemic disarray" in HD has been described, referring to the fall in glucose during HD followed by rebound hyperglycemia in the post-HD period (Figure 2). HD-induced hypoglycemia is frequently observed. In early studies, Takahashi et al. demonstrated a reduction in plasma glucose concentration from the pre-dialyser site to the post-dialyser site in patients under a dialysate of 5.55 mmol/L glucose. This reduction in serum glucose within the dialyzer might be induced by dialysate-stress-triggered diffusion of plasma glucose into the erythrocyte, as well as loss into the dialysate (72). In general, patients might lose around 15-30 g of glucose during an HD session. In patients with ESKD, defective counter-regulatory effects, reduced renal gluconeogenesis and hypoglycemia unawareness might result in frequent asymptomatic hypoglycaemic events. In 17 patients with T2D on HD, the mean sensor glucose was lower during the on-dialysis than the off-dialysis days (60). In 12 patients on dialysis, Gai et al. reported that the median CGM glucose level was below the concentration of dialysate of 5.55 mmol/L during most of the HD sessions (87% of the time) (51). In 9 patients with T2D, Jung et al. reported a significant reduction in mean sensor glucose during HD session, regardless of the glucose concentration of dialysate solution (5.55 – 11.1 mmol/L) with most of the hypoglycaemic events occurring on the day of HD (61). In 46 patients with ESKD with or without diabetes, Jin et al. reported a significant reduction in mean sensor glucose during HD session irrespective of the status of diabetes although patients with diabetes had greater glucose loss during HD session (62).

In a recent study involving 98 Japanese patients with T2D on HD who had 2-day CGM, sensor glucose showed a sustained decline irrespective of dialysate glucose concentration with 50% of patients with diabetes reaching a glucose nadir lower than the dialysate concentration. In the whole group, 21% experienced HD-related hypoglycemia <3.9 mmol/L either during the HD session or post-HD and before the next meal. There were no differences in terms of clinical characteristics (e.g. body mass index, duration of diabetes, insulin treatment) and traditional glycemic markers (e.g. HbA1c and GA), between patients with HD-related or post-HD hypoglycemia and patients without hypoglycemia. Despite an average HbA1c: 6.4% ± 1.2% for these T2D patients, asymptomatic HD-related hypoglycemia was frequent and the HD-related hypoglycaemia was only captured by CGM (65).

Rebound hyperglycemia during the post-HD period may be related to choices of dialysate and dialysis membrane, which can influence plasma insulin concentrations during dialysis (73, 74). Insulin is readily removed from plasma by diffusion owing to its small molecular size and low protein-binding capacity. However, during HD, most of the insulin is removed via adsorption with the dialysis membrane through electrostatic and hydrophobic interactions resulting in hyperglycemia in the post-HD period. The clearance of insulin by absorption depends on the type of dialysis membrane, with the greatest absorption in polysulfone membrane and the lowest absorption in polyester-polymer alloy (19). The counter-regulatory hormonal responses to HD-induced hypoglycemia could increase insulin resistance and trigger post-HD hyperglycemia. Kazempour-Ardebili et al. demonstrated that nocturnal sensor glucose was significantly higher on the HD day than HD-free day (60). This was also confirmed by other studies where the time of HD session was reported in the 24-hour CGM profile (51, 61, 63). Jin et al. confirmed post-HD hyperglycemia especially in patients with diabetes compared with their non-diabetic counterparts (62). Padmanabhan et al. evaluated the effects of different dialysate and dialysis membranes on glycemic control. In a study of 38 patients with and without diabetes, HD-induced hypoglycemia and post-HD hyperglycemia occurred with the use of glucose-free dialysate but the fluctuation could be attenuated by using glucose-containing dialysate (64). Both HD-induced hypoglycemia and post-HD hyperglycemia may contribute to heightened glycemic variability, increased oxidative stress and inflammation with worsening of clinical outcomes. By using CGM, these silent events may be detected early to inform treatment.

GLUCOSE PROFILES DURING PERITONEAL DIALYSIS (PD) 

One of the determining factors of glycemic profile in patients with PD is the rate of peritoneal absorption of glucose, which is in turn affected by glucose concentration of dialysate, dwell time, and status of membrane transport (75). Ultrafiltration by peritoneal membrane is created by either crystalloid osmosis using a higher glucose concentration in the dialysate, or by colloid osmosis using large colloid agents like icodextrin (76). Icodextrin solution contains a mixture of glucose polymers which are slowly absorbed via lymphatics. Together with its osmotic effect, icodextrin leads to sustained ultrafiltration and is widely used as an alternative osmotic agent to dextrose especially in dialysate with long dwelling time (77). Early observational studies using CGM showed that patients with PD spent a large proportion of time in hyperglycemia (66). In a study of 20 patients with well-controlled T1D and T2D and mean HbA1c of 5.9% who were dialyzed on glucose-containing dialysates, patients spent on average 33% time above 10 mmol/l and 1% time below 3.9 mmol/l (70). Lee et al. evaluated the impact of glucose influx from dialysate in 25 patients with diabetes on maintenance PD. In patients using glucose-based dialysate, the sensor glucose levels increased by 7-8 mg/dL within 1 hour of exchange using glucose-containing dialysate. The glycemic excursion was similar with 1.25% and 2.25% glucose solutions with larger increments observed with 3.86% glucose solutions (67). Figure 3 shows an example of CGM profile in a patient on continuous ambulatory peritoneal dialysis (CAPD).

Icodextrin is associated with stable or even decreases in CGM sensor glucose during PD dwells (67). Marshall et al. demonstrated the effect of switching dialysate on CGM profiles in 8 patients with PD. Switching from three 1.36% glucose exchanges and one 3.86% glucose exchange to two bags of 1.36% glucose exchange, one bag of amino acid exchange and one bag of icodextrin was associated with lower sensor glucose and glycemic variability (68). In a retrospective study of 60 patients with 95% of them receiving icodextrin dialysate, the CGM-detected time in hypoglycemia was 5% which was often asymptomatic (69).

The diffusing capacity of the peritoneal membrane is another crucial factor in determining glycemia. The exchange rate of serum-dialysate glucose is dependent on the osmotic pressure, as well as the transport status of the peritoneal membrane. The osmotic gradient between dialysate and peritoneum is rapidly lost in patients with high transporter status due to the rapid absorption of glucose from dialysate (78). As a result, these patients might have a high risk of PD-related hyperglycemia. Skubala et al. demonstrated the effect of peritoneal transport status using CGM in 30 patients with and without diabetes. In their study, patients on 1.36% and 2.27% glucose dialysates had similar HbA1c, mean 24-hour CGM-glucose, mean post-PD glucose, and mean post-PD increment in glucose. However, mean post-PD glucose and mean post-PD increment in glucose was significantly different in patients with high peritoneal transport (HPT) and high average peritoneal transport (HAPT), even in nondiabetic individuals (71).

Another modifiable factor of CGM-glucose is the timing, route and dose of insulin administration in patients on PD. Subcutaneous basal-bolus insulin regimens are effective regimens in patients with T1D or T2D on PD but require frequent self-monitoring (50). Intraperitoneal (IP) delivery of insulin can counteract the glucose absorption from the dialysate. However, there are no standardized recommendations on the initiation or titration of IP insulin for different dialysates (79). Dose adjustments are often based on infrequent fasting and post-meal capillary blood glucose with CGM having the potential to guide adjustment of insulin therapy in patients on PD.

In summary, patients with diabetes on HD or PD display distinct glycemic profiles and patterns that can be comprehensively assessed by CGM. Apart from patient factors (e.g. beta-cell function, PD transporter status), there are a number of modifiable treatment factors, such as choices of dialysate, dialysis regimen and doses/timing of insulin, where data from CGM can help optimize treatment.

FIGURE 3 | An illustrative 24-hour ambulatory glucose profile in a patient with type 2 diabetes on continuous ambulatory peritoneal dialysis (CAPD). He is on three 1.5% dextrose exchanges daily and a basal-bolus insulin regimen. Laboratory measures of glycemic control were HbA1c 7.5% and Fructosamine 224 µmol/L. Based on CGM metrics, the glucose management indicator (GMI) was 6.9%, and the coefficient variation (CV) was 36.9%. The blue arrow on the bottom indicates the times of insulin injection and meal intake. The vertical blue arrow on top indicates PD exchange timing, and the horizontal blue arrow on top indicates PD exchange period. Green lines indicate the target CGM glucose range (3.9 mmol/L to 10 mmol/L).

USE OF PERSONAL CGM PATIENTS IN ADVANCED CKD OR MAINTENANCE DIALYSIS

Personal use of real-time (rt) or flash CGM devices may reduce hypoglycemia and improve glycemic control in patients with diabetes without CKD. The benefits of CGM use in patients with T1D on improving glycemic control are now well-established. In the Randomized Controlled Trial Examining the Benefit of CGM Use for Adults with T1D on Insulin Injections (DIAMOND) trial (80), there was a significant HbA1c difference of -0.6% in favor of rt-CGM versus standard SMBG after 24 weeks of intervention in T1D patients on multiple daily injections (MDI). In another randomized study involving 161 patients with T1D treated with MDI, a similar significant difference of -0.43% in HbA1c in favor of rt-CGM versus standard SMBG was reported after 26-weeks of intervention and during 17 weeks of post-intervention washout period (80, 81). In an open-labeled randomized trial in adults with well-controlled T1D on MDI (REPLACE-BG trial), use of flash CGM without confirmatory SMBG was safe and reduced hypoglycemia (82) with improved treatment satisfaction (83).

Several pilot and small-scale studies supported the potential beneficial effects of professional CGM in patients on HD or PD, whilst data on continuous personal use was limited. Most studies explored the use of blinded CGM for treatment titration. In a pilot study, Kepenekian al. used blinded CGM in 28 T2D patients on HD with suboptimal glycemic control for 54 hours at baseline and during a 3-month follow-up period. After 3 months of intervention, the CGM-adapted insulin regimen was associated with a greater reduction in HbA1c without increasing symptomatic hypoglycemia (84). The DIALYDIAB pilot study involved 15 patients with T1D or T2D and compared the effect of blinded-CGM SMBG using a two-period design. Use of blinded CGM triggered more frequent treatment adjustments compared with SMBG alone. This resulted in better glucose profile with significantly lower HbA1c and time above range without increasing hypoglycaemic episodes (85). There are also few studies in patients with PD where CGM was used to assess the effects of structured education (50) or compare different glucose-lowering drug regimens (86). These studies demonstrated the potential of CGM in promoting patient self-management and informing providers in treatment adjustment to improve glycemic control.

CGM systems have the potential to be combined with automated insulin delivery in closed-loop systems, also referred to as an 'artificial pancreas". A recent randomized trial evaluated a fully automated closed-loop system against standard insulin therapy in 26 patients with T2D on HD using a cross-over design (87). In this study, TIR was significantly higher (57.1% versus 42.5%) and the time above and below range was lower (TAR: 42.6% versus 56.6%, TBR: 0.12% versus 0.17%) in the closed-loop phase. The mean sensor glucose was also significantly lower in the closed-loop versus control phase (10.1 mmol/L versus 11.6 mmol/L). Of note, the time spent in extreme hyperglycemia (defined as >20 mmol/L) was significantly lower during the closed-loop phase than the control phase (1.8% versus 6.7%). However, the system was given only for short-term use operated by healthcare professionals in a clinic setting rather than home use.

The ease of operation of personal CGM systems in patients with ESKD with multiple comorbidities need to be considered. Many patients with ESKD may have visual impairment due to retinopathy or cataracts, skin problems and cognitive issues that limit their ability to operate these devices. However, personal CGM with real-time alerts might benefit patients with ESKD on complex insulin regimens or vulnerability to hypoglycemia. Future research is required to investigate the utility and cost-effectiveness of personal CGM in patients with advanced CKD and dialysis.

There are some limitations in the use of CGM for patients under dialysis. Apart from potential sensor interference from endogenous and exogenous substances (46), the accuracy of CGM is lower in the hypoglycemic range and under rapid changes in blood glucose values (88–90). False hypoglycaemic alerts may occur more frequently under these conditions, which may lead to unnecessary treatment. A confirmatory SMBG value is advisable for treatment decisions at these extreme glucose values. Additionally, repeated false positive alerts could lead to alarm fatigue and increase patient anxiety.

CONCLUSIONS 

Optimal glycemic control will delay the progression of CKD and improve clinical outcomes. HbA1c and alternative glycemic markers have limitations, particularly in patients with advanced CKD. With the advent of CGM, it is now possible to monitor the glycemic status with better precision in patients with CKD. Professional CGM can inform health care professionals on glucose profiles not provided by HbA1c in patients with CKD to optimize treatment regimens. Real-time or flash CGM provides instant or timely feedback to users on the impact of meals and treatment on glucose excursion. The inclusion of real-time alerts in CGM, displayed in smart devices, can provide early warnings against hyperglycemia and hypoglycemia. This information may improve the safety of the prescription of GLDs and insulin in these high-risk patients. Finally, the integration of this CGM system with fully automated closed-loop insulin delivery systems offers the potential of more precise control.

The use of CGM in patients with ESKD has revealed distinct glycemic patterns during maintenance dialysis. Glycemic patterns in patients under HD are impacted by the glucose concentrations in dialysate and choices of dialysis membranes. Glucose-free dialysate is generally preferred due to lower cost and chance of bacterial infection. However, glucose-containing dialysate may reduce HD-related hypoglycemia and post-HD hyperglycemia, especially in patients with diabetes. Healthcare professionals should consider providing glucose-containing dialysate, replenishing post-HD glucose loss by snacks, or adjusting insulin regimen to avoid HD-related glycemic excursion. Similar to HD, glycemic patterns in PD patients are impacted by dialysate glucose concentration and peritoneal membrane transport state. Health care professionals should consider glucose influx from glucose-rich dialysate and adjust insulin treatment to maintain a stable blood glucose. Although a switch to glucose-free dialysates may theoretically reduce glucose influx, randomized trials suggested this might be associated with adverse outcomes (91). Pending further evidence, a careful adjustment of insulin and dialysate regimens in patients under PD may strike the balance between optimizing glycemic control and ultrafiltration. Future studies using CGM should be conducted to investigate whether the use of personal CGM with glycemic alerts will reduce hypoglycemia and complications and improve long-term outcomes in patients with advanced CKD and dialysis.

AUTHOR CONTRIBUTIONS

JL and EC conceived the idea of the paper. JL researched and wrote the manuscript, JL, JN, EC, and JC critically revised the manuscript. All authors contributed to and approved the final manuscript.

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