Glycemic variability and all-cause mortality in patients with diabetes receiving hemodialysis: A prospective cohort study

In-hospital glycemic variability and all-cause mortality among patients hospitalized for acute heart failure

BACKGROUND

High glycemic variability (GV) is a poor prognostic marker in cardiovascular diseases. We aimed to investigate the association of GV with all-cause mortality in patients with acute heart failure (HF).

METHODS

The Korean Acute Heart Failure registry enrolled patients hospitalized for acute HF from 2011 to 2014. Blood glucose levels were measured at the time of admission, during hospitalization, and at discharge. We included those who had 3 or more blood glucose measurements in this study. Patients were divided into two groups based on the coefficient of variation (CoV) as an indicator of GV. Among survivors of the index hospitalization, we investigated all-cause mortality at 1 year after discharge.

RESULTS

The study analyzed 2,617 patients (median age, 72 years; median left-ventricular ejection fraction, 36%; 53% male). During the median follow-up period of 11 months, 583 patients died. Kaplan-Meier curve analysis revealed that high GV (CoV > 21%) was associated with lower cumulative survival (log-rank P < 0.001). Multivariate Cox proportional analysis showed that high GV was associated with an increased risk of 1-year (HR 1.56, 95% CI 1.26-1.92) mortality. High GV significantly increased the risk of 1-year mortality in non-diabetic patients (HR 1.93, 95% CI 1.47-2.54) but not in diabetic patients (HR 1.19, 95% CI 0.86-1.65, P for interaction = 0.021).

CONCLUSIONS

High in-hospital GV before discharge was associated with all-cause mortality within 1 year, especially in non-diabetic patients with acute HF.

Prevalence of glycemic variability and factors associated with the glycemic arrays among end-stage kidney disease patients on chronic hemodialysis

Glycemic variability (GV) confers a significantly higher risk of diabetic-related complications, especially cardiovascular. Despite extensive research in this area, data on end-stage kidney disease (ESKD) patients on chronic hemodialysis are scarce. This study aims to determine the magnitude of GV among ESKD (diabetic vs nondiabetic) patients and its associated factors on hemodialysis days (HDD) and non-hemodialysis days (NHDD) where postulation of a higher GV observed among diabetic on HDD.We recruited 150 patients on hemodialysis, 93 patients with type 2 diabetic (DM-ESKD), and 57 with nondiabetic (NDM-ESKD). The GV indices (standard deviation [SD] and percentage coefficient variant [%CV]) were obtained from 11-point and 7-point self-monitoring blood glucose (fasting to post-meal) (SMBG) profiles on HDD and NHDD. The GV indices and its associated factors of both DM-ESKD and NDM-ESKD were analyzed to compare HDD vs NHDD.Mean blood glucose on HDD was 9.33 [SD 2.7, %CV 30.6%] mmol/L in DM-ESKD compared with 6.07 [SD 0.85, %CV 21.3%] mmol/L in NDM-ESKD (P = <.01). The DM-ESKD group experienced significantly above target GV indices compared to NDM-ESKD on both HDD and NHDD, particularly in the subgroup with HbA1c 8-10% (P = <.01). Presence of diabetes, older age, hyperlipidemia, HbA1c, ferritin levels, and albumin were identified as factors associated with GV.DM-ESKD patients have above-target GV indices, especially on HDD, therefore increasing their risk of developing future complications. We identified high HbA1c, older age group, presence of hyperlipidemia, ferritin levels, and albumin as factors associated with GV indices that may be used as surrogate markers for GV. Since these groups of patients are vulnerable to CVD mortality, urgent attention is needed to rectify it.

Flash Glucose Monitoring to Assess Glycemic Control and Variability in Hemodialysis Patients: The GIOTTO Study

Background: Flash glucose monitoring (FGM) is a technology with considerable differences compared to continuous glucose monitoring (CGM), but it has been scarcely studied in hemodialysis patients. Thus, we aimed assessing the performance of FGM in such patients by comparison to self-monitoring of blood glucose (SMBG). We will also focus on estimation of glycemic control and variability, and their relationships with parameters of glucose homeostasis.

Methods: Thirty-one patients (20 with type 2 diabetes, T2DM, 11 diabetes-free, NODM) collected readings by FGM and SMBG for about 12 days on average. Readings by FGM and SMBG were compared by linear regression, Clarke error grid, and Bland-Altman analyses. Several indices of glycemic control and variability were computed. Ten patients also underwent oral glucose tolerance test (OGTT) for assessment of insulin sensitivity/resistance and insulin secretion/beta-cell function.

Results: Flash glucose monitoring and SMBG readings showed very good agreement in both T2DM and NODM (on average, 97 and 99% of readings during hemodialysis in A+B Clarke regions, respectively). Some glycemic control and variability indices were similar by FGM and SMBG (p = 0.06–0.9), whereas others were different (p = 0.0001–0.03). The majority of control and variability indices were higher in T2DM than in NODM, according to both FGM and SMBG (p = 0.0005–0.03). OGTT-based insulin secretion was inversely related to some variability indices according to FGM (R < −0.72, p < 0.02).

Conclusions: Based on our dataset, FGM appeared acceptable for glucose monitoring in hemodialysis patients, though partial disagreement with SMBG in glycemic control/variability assessment needs further investigations.

Predictors of Survival in Chronic Hemodialysis Patients: A 10-Year Longitudinal Follow-Up Analysis

BACKGROUND

Risk factors of mortality in chronic hemodialysis patients have not yet been sufficiently evaluated. In particular, chronological transits and interactions of the impact of risk factors have rarely been described.

METHODS

This study is a post hoc analysis of the participants in the Olme-sartan Clinical Trial in Okinawan Patients under OKIDS (OCTOPUS) study conducted between June 2006 and June 2011. We additionally followed up on the prognosis of the participants until July 31, 2018. Standardized univariable and multivariable Cox regression analyses were used to evaluate the influences of the participants' baseline characteristics on all-cause mortality. We also evaluated chronological changes in the impacts of risk factors, interactions among predictors, and the influence of missing values using sensitivity analyses.

RESULTS

Of the 469 original trial participants, 461 participants were evaluated. The median time of follow-up was 10.2 years. A total of 211 (45.8%) participants were deceased. The leading causes of death were infection (n = 72, 34.1%) and cardiovascular disease (n = 66, 31.3%). Univariate and multivariate Cox regression analyses revealed that the impact of diabetes mellitus, history of coronary intervention, and hypoalbuminemia were significant risk factors for mortality during the whole follow-up period. During the early follow-up period (≤3 years), standardized univariate Cox regression analyses revealed that history of amputation (hazard ratio [HR] = 4.61, p < 0.001), lower dry weight, higher cardiothoracic ratio, and lower potassium levels were statistically significant risks. In those who survived for longer than 3 years, a history of stroke (HR = 1.73, p = 0.006), higher systolic blood pressure, lower serum sodium levels, and higher levels of hemoglobin, and serum phosphate were significant risks. We also observed a stable interaction between the impacts of serum phosphate and albumin on all-cause mortality.

CONCLUSION

In chronic hemodialysis patients, targets to improve the short-term prognosis and long-term prognosis are not equivalent. Hyperphosphatemia was a significant risk factor for the all-cause mortality among patients with normal serum albumin levels but not among patients with compromised albumin levels.

Are residents receiving the training needed within their residency programs to optimally manage patients with diabetes?

Objective: Diabetes is a prevalent and growing problem in the United States (U.S.); primary care physicians need to be prepared to initiate and progressively advance treatment. The objective of this study was to understand how diabetes management is taught in U.S. Family Medicine (FM) and Internal Medicine (IM) residency programs.Methods: Invitations to complete an online survey were sent via postal mail to U.S. FM and IM residency programs in 2019.Results: Directors/associate directors from 68 FM residencies and 66 IM residencies completed the online survey out of 645 (10.5%) and 505 (13.1%) programs, respectively. Most respondents rated cardiovascular disease and risk management in diabetes as 'very important' (90%), but only about half (47%) did so for newer generation insulin analogs and 27% for digital health technologies. About two-thirds of programs cover non-insulin options for type 2 diabetes (66%) and types of insulin (63%) to a great extent, but only about one-third of programs cover social determinants of health (36%) and pre-diabetes (35%) to this degree. Many programs report plans to expand training on cardiovascular disease and diabetes (59%), but only 32% plan to expand training on digital technology for diabetes care. Lack of faculty time and competing priorities are cited as being the biggest barriers to expanding diabetes training.Conclusions: Our study found that the current U.S. FM and IM residency program diabetes curricula are dominantly oriented toward cardiovascular disease and 'traditional' insulins. A variety of training materials and resources could help overcome some of the current barriers to curriculum expansion of other important components of diabetes care that may help future physicians successfully manage diabetes with newer generation insulin and glucose monitoring technologies.Abbreviations: U.S: United States; PCP: Primary Care Physician; FM: Family Medicine; IM: Internal Medicine; CGM: Continuous Glucose Monitor; AAFP: American Academy of Family Physicians; ACGME: Accreditation Council for Graduate Medical Education; U/mL: units per milliliter; CME: Continuing Medical Education.