Glycemic Control and Mortality in Diabetic Patients Undergoing Hemodialysis: Much More to Learn

Factors associated with patient activation among patients with diabetes on hemodialysis: a multicenter cross-sectional study from a developing country

BACKGROUND

Diabetes mellitus (DM) is a major public health concern with considerable morbidity and mortality. DM affects patients' quality of life and can lead to multiple complications, including chronic kidney disease (CKD) and the need for dialysis. Higher patient activation can improve health outcomes in hemodialysis patients with DM. This study aimed to explore the factors associated with higher patient activation and health-related quality of life (HRQoL) among hemodialysis patients with DM.

METHODS

This was a cross-sectional, questionnaire-based study conducted on hemodialysis patients with DM in Palestine. The quota sampling method was utilized to draw samples from six dialysis centers. The questionnaire consists of three sections. The first section includes demographic, socioeconomic and clinical questions. The second section utilizes the patient activation measure-13 (PAM-13) to measure patient activation, while the third section assesses HRQoL using the EQ-5D-5 L tool and the visual analog scale (VAS). Mann‒Whitney and Kruskal‒Wallis tests were employed to examine the relationships between variables at the bivariate level, and multiple regression analysis was employed at the multivariate level.

RESULTS

Of the 200 patients who were approached, 158 were included. The median PAM, EQ-5D index, and VAS score were low at 51.0, 0.58, and 60.0, respectively. A higher PAM score was independently associated with a higher household income level and taking medications independently. A higher EQ-5D index was associated with taking more than eight medications, taking medications independently, living with fewer than three comorbid conditions, and having a higher PAM. A higher VAS score was associated with being married, and receiving less than 3.5 hours of hemodialysis.

CONCLUSIONS

A higher patient activation level was associated with a higher income level and independence in taking medications. Interventions designed to improve patient activation, such as medication management programs, should address these factors among the target population. Longitudinal studies are needed to assess the time effect and direction of causation between health status and patient activation.

Prospective Study of Change in Skin Autofluorescence Over Time and Mortality in People Receiving Hemodialysis

Introduction

Elevated skin autofluorescence (SAF), a measure of tissue accumulation of advanced glycation end products (AGEs), is a strong predictor of all-cause and cardiovascular mortality in the hemodialysis population. However, prospective studies investigating the association between changes in SAF over time and mortality are scarce. We therefore aimed to investigate the prognostic value of SAF trend for predicting mortality in a hemodialysis population.

Methods

We enrolled 120 patients on hemodialysis in a 5-year observational, prospective study. SAF was measured at baseline, 3, 6, 9, 12, and 24 months. Rate of change in SAF (i.e., SAF trend) was calculated using linear regression. Time to event was the number of days from baseline to death, kidney transplantation, or March 31, 2022.

Results

Mean age, mean baseline SAF, and median SAF trend were 65 ± 14 years, 3.4 ± 0.9 arbitrary units (AU), and an increase of 0.1 (-0.1 to 0.4) AU/yr, respectively. Median observation time was 42 months, during which 59 participants (49%) died. Univariable analysis identified age, history of smoking, lower serum albumin, higher baseline SAF, and increase in SAF as significant predictors of higher mortality. In multivariable analysis, higher baseline SAF (hazard ratio: 1.45; 95% confidence interval: 1.08-1.94; P = 0.01) and increasing SAF trend (2.37 [1.43-3.93]; P < 0.001) were independent predictors of increased mortality.

Conclusion

An increasing SAF trend and higher baseline SAF were independent predictors of all-cause mortality in this hemodialysis population, suggesting that monitoring of SAF may have clinical utility. Strategies to improve outcomes by reducing or preventing the increase in SAF should now be investigated in prospective studies.

Distinct biomarker roles for HbA1c and glycated albumin in patients with type 2 diabetes on hemodialysis

AIMS

HbA_1c and glycated albumin (GA) are used to monitor glycemia, but their accuracy to represent glycemic profiles in hemodialysis remains controversial.

METHODS

Continuous glucose monitoring in 97 patients with type 2 diabetes (41 on hemodialysis [HD] and 56 without nephropathy) was analyzed to evaluate whether HbA_1c and/or GA serve as appropriate glycemic profile markers.

RESULTS

The average glucose significantly correlated with HbA_1c in both HD group and group without nephropathy (r=0.59, P<0.0001; r=0.40, P<0.005). The slopes of linear regression lines were statistically indistinguishable (F=0.30, P=0.744), while the y-intercepts were significantly different (F=57.86, P<0.0001). GA showed strong correlation with the glycemic standard deviation (r=0.68, P<0.0001), and with the average glucose (r=0.42, P<0.001). Least square analysis revealed that only HbA_1c, but not GA, was significantly associated with the average glucose (F=10.20, P<0.0005; F=0.38, P=0.5427), while only GA was significantly associated with the glycemic variability in HD group.

CONCLUSIONS

In HD participants, HbA_1c correlates with the average glucose more than GA, but underestimates it, and a correction formula of HbA1c can be developed as an appreciable marker. GA value itself reflects the average glucose, but less accurately than HbA_1c, while it could serve as an indicator for hyperglycemia/hypoglycemia excursion.

[Significance of hemoglobin A1C in the management of diabetes in dialysis patients]

According to latest guidelines hemoglobin A1C plays a central role in the diagnosis of diabetes mellitus. It is well-known from epidemiologic studies that a high rate of diabetic patients enters into dialysis programs and these patients have an unfavourable mortality outcome. Based on surveys conducted in recent years in this patient group, hemoglobin A1C has an important role in assessing carbohydrate metabolism. However, there are several factors independent of blood glucose may affect hemoglobin A1C values both in hemodialysis and peritoneal dialysis patients. Hemodialysis disturbs hemoglobin A1c assessment because of an accelerated turnover of lost red blood cells. During peritoneal dialysis a considerable amount of glucose may be absorbed from the peritoneal solutions that may influence hemoglobin A1C level. Several alternative markers such as glycated albumin and fructosamine have been evaluated but they failed to have prognostic advantage. It has been concluded that among dialysis patients the hemoglobin A1C range between 6.5 and 8% is associated with the lowest mortality risk.