Simultaneous control of glycemic, blood pressure, and lipid significantly reduce the risk of renal progression in diabetes patients

Effects of a combination of dyslipidemia and hypertension on the glycemic control of patients with type 2 diabetes mellitus: a cross-sectional study

Objectives

Both dyslipidemia and hypertension contribute to poor glycemic control in patients with type 2 diabetes mellitus, but the combined effect of dyslipidemia and hypertension on glycemic control in patients with type 2 diabetes mellitus has not been evaluated. The aim of this study was to analyze the interaction effect between dyslipidemia and hypertension on glycemic control in patients with type 2 diabetes mellitus.

Methods

A total of 2485 patients with type 2 diabetes mellitus were selected from the Xuzhou community of China by multi-stage cluster random sampling for a cross-sectional survey. Their glycated hemoglobin, dyslipidemia, and hypertension were assessed, and the interaction effects between dyslipidemia and hypertension on glycemic control were analyzed using relative excess risk due to the interaction, the synergy index, and the attributable proportion of the additive interaction.

Results

Of the participants, 62.13% (1544/2485) had dyslipidemia and 55.01% (1367/2485) had hypertension. Of the participants, 76.66% (1905/2485) who had both dyslipidemia and hypertension also had poor glycemic control. The prevalence of poor glycemic control was higher in those with both dyslipidemia and hypertension (odds ratio 2.735, 95% confidence interval 2.117-3.532; p < 0.001) compared with those who had normal blood lipids and without hypertension, after adjustment for confounders. The relative excess risk due to the interaction, the attributable proportion, and the synergy index were 1.077 (95% confidence interval 0.558-1.596), 2.637 (95% confidence interval 1.268-4.006), and 0.394 (95% confidence interval 0.230-0.558), respectively, for the interaction between dyslipidemia and hypertension.

Conclusions

Dyslipidemia and hypertension have an additive interaction on poor glycemic control in patients with type 2 diabetes mellitus.

Exposure to ambient air pollutants with kidney function decline in chronic kidney disease patients

Chronic kidney disease (CKD) has been a global public health problem with many adverse outcomes, but data are lacking regarding the relationship between air pollutants and risk of renal progression in patients with CKD. This study was to investigate whether 1-year average exposure to ambient air pollutants -CO, NO, NO₂, SO₂, O₃, PM_2.5, and PM₁₀-is related to renal function deterioration among patients with CKD. A total of 5301 CKD patients were included in this study between October 2008 and February 2016. To estimate each patient's exposure to ambient air pollution, we used the 24-h ambient air pollution concentration monitoring data collected one year prior to renal progression or their last renal function assessment. Renal progression was considered when estimated glomerular filtration rate (eGFR) decreased more than 25% from the baseline eGFR. Cox proportional hazard regression was performed to calculate hazard ratios (HRs). Among 5301 patients with CKD, 1813 (34.20%) developed renal progression during the 30.48 ± 14.99-month follow-up. Patients with the highest quartile exposure to CO [HR = 1.53 (95% CI: 1.24, 1.88)], NO [HR = 1.38 (95% CI: 1.11, 1.71)], NO₂ [HR = 1.63 (95% CI: 1.36, 1.97)], SO₂ [HR = 2.27 (95% CI: 1.83, 2.82)], PM_2.5 [HR = 7.58 (95% CI: 5.97, 9.62)], and PM₁₀ [HR = 3.68 (95% CI: 2.84, 4.78)] had a significantly higher risk of renal progression than those with the lowest quartile exposure. In the multipollutant model, the analyses yielded to similar results. These results reinforce the importance of measures to mitigate air pollution and strategies to prevent worsening of kidney function in patients with CKD. One-year high exposure to ambient CO, NO, NO₂, SO₂, PM_2.5, and PM₁₀ is significantly associated with deteriorated kidney function in patients with CKD among Taiwanese adults.

Effect of Telemedicine on Quality of Care in Patients with Coexisting Hypertension and Diabetes: A Systematic Review and Meta-Analysis

Background: With the development of technology and the need for individualized and continuous support for patients with chronic conditions, telemedicine has been widely used. Despite the potential benefits of telemedicine, little is known about its effect on the quality of care (QoC) in people with hypertension and comorbid diabetes, who face more challenges in disease management than those with hypertension or diabetes alone. This study aimed to examine the effect of telemedicine on QoC for patients with hypertension and comorbid diabetes by synthesizing findings from clinical trials. Methods: This systematic review and meta-analysis were developed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Four major electronic databases from inception to March 2020 were searched. Studies were screened using predetermined criteria. Data were extracted and tabulated into tables. The primary outcomes were QoC indicators, including outcomes (e.g., blood pressure [BP] and glycemic control), process, and experience of care. Quantitative data were pooled and presented in forest plots. Qualitative narratives were also used. Results: Five studies from four clinical trials were included in this review, with intervention durations ranging from 3 to 6 months. Telemedicine significantly decreased BP by 10.4/4.8 mm/Hg, but its effect on glycemic control was inconsistent. Telemedicine also improved experience of care (e.g., patient perception and engagement). Various indicators for process of care were assessed, including medication adherence, BP monitoring, and self-efficacy, with mixed findings. Conclusions: Telemedicine has great potential to improve the QoC, particularly outcomes of care, for patients with hypertension and comorbid diabetes. Health care professionals may consider using available telemedicine to facilitate communication and interaction with their patients, thereby helping them with disease management. Long-term, large-scale studies are needed to test the generalizability and sustainability of the telemedicine programs.

Addressing Diabetes and Poorly Controlled Hypertension: Pragmatic mHealth Self-Management Intervention

BACKGROUND

Patients with diabetes and poorly controlled hypertension are at increased risk for adverse renal and cardiovascular outcomes. Identifying these patients early and addressing modifiable risk factors is central to delaying renal complications such as diabetic kidney disease. Mobile health (mHealth), a relatively inexpensive and easily scalable technology, can facilitate patient-centered care and promote engagement in self-management, particularly for patients of lower socioeconomic status. Thus, mHealth may be a cost-effective way to deliver self-management education and support.

OBJECTIVE

This feasibility study aimed to build a population management program by identifying patients with diabetes and poorly controlled hypertension who were at risk for adverse renal outcomes and evaluate a multifactorial intervention to address medication self-management. We recruited patients from a federally qualified health center (FQHC) in an underserved, diverse county in the southeastern United States.

METHODS

Patients were identified via electronic health record. Inclusion criteria were age between 18 and 75 years, diagnosis of type 2 diabetes, poorly controlled hypertension over the last 12 months (mean clinic systolic blood pressure [SBP] ≥140 mm Hg and/or diastolic blood pressure [DBP] ≥90 mm Hg), access to a mobile phone, and ability to receive text messages and emails. The intervention consisted of monthly telephone calls for 6 months by a case manager and weekly, one-way informational text messages. Engagement was defined as the number of phone calls completed during the intervention; individuals who completed 4 or more calls were considered engaged. The primary outcome was change in SBP at the conclusion of the intervention.

RESULTS

Of the 141 patients enrolled, 84.0% (118/141) of patients completed 1 or more phone calls and had follow-up SBP measurements for analysis. These patients were on average 56.9 years of age, predominately female (73/118, 61.9%), and nonwhite by self-report (103/118, 87.3%). The proportion of participants with poor baseline SBP control (50/118, 42.4%) did not change significantly at study completion (53/118, 44.9%) (P=.64). Participants who completed 4 or more phone calls (98/118, 83.1%) did not experience a statistically significant decrease in SBP when compared to those who completed fewer calls.

CONCLUSION

We did not reduce uncontrolled hypertension even among the more highly engaged. However, 83% of a predominately minority and low-income population completed at least 67% of the multimodal mHealth intervention. Findings suggest that combining an automated electronic health record system to identify at-risk patients with a tailored mHealth protocol can provide education to this population. While this intervention was insufficient to effect behavioral change resulting in better hypertension control, it does suggest that this FQHC population will engage in low-cost population health applications with a potentially promising impact.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02418091; https://clinicaltrials.gov/ct2/show/NCT02418091 (Archived by WebCite at http://www.webcitation.org/76RBvacVU).

Higher pulse pressure predicts initiation of dialysis in Japanese patients with diabetes

AIMS

To determine incidence and predictors of starting dialysis in patients with diabetes emphasizing blood pressure variables.

METHODS

A nationwide database with claim data on 18 935 people (15 789 men and 3146 women) with diabetes mellitus aged 19 to 72 years in Japan was used to elucidate predictors for starting dialysis. Initiation of dialysis was determined from claims using ICD-10 codes and medical procedures. Using multivariate Cox modelling, interactions between glycaemic and blood pressure values were determined.

RESULTS

During a median follow-up of 5.3 years, incidence of dialysis was 0.81 per 1000 person-years. Multivariate analysis of a model involving systolic and diastolic blood pressure (SBP and DBP) simultaneously as covariates showed that hazard ratios (HRs) for starting dialysis for each 1-SD elevation in SBP and DBP were 2.05 (95% confidence interval 1.58-2.64) and 0.66 (0.50-0.88), respectively, implying that pulse pressure (PP) was a promising predictor. For confirmation, a model involving SBP and PP simultaneously as covariates demonstrated that HRs for each 1-SD elevation in SBP and PP were 1.09 (0.81-1.48) and 1.54 (1.14-2.08), respectively, with PP the more potent predictor. Compared with HbA_1c <8% and PP <60 mmHg, the HR for those with HbA_1c ≥8% and PP ≥60 mmHg was 6.32 (3.42-11.7).

CONCLUSIONS

In our historical cohort analysis, SBP and PP were independent predictors for starting dialysis. PP was the more potent, suggesting the contribution of increased arterial stiffness to the incidence of dialysis. Future studies are needed to conclude the independent influence of PP and HbA_1c on dialysis considering other risk factors.

Continuity of care with physicians and risk of subsequent hospitalization and end-stage renal disease in newly diagnosed type 2 diabetes mellitus patients

Purpose

Effective management for type 2 diabetes mellitus (DM) can slow the progression of kidney outcomes and reduce hospital admissions. Better continuity of care (COC) was found to improve patients’ adherence and self-management. This study examined the associations between COC, hospitalization, and end-stage renal disease (ESRD) in DM patients.

Patients and methods

In the cohort study, data from 1996 to 2012 were retrieved from the Longitudinal Health Insurance Database, using inverse probability weighted analysis. A total of 26,063 patients with newly diagnosed type 2 DM who had been treated with antihyperglycemic agents were included. COC is to assess the extent to which a DM patient visited the same physician during the study period. This study categorized COC into 3 groups – low, intermediate, and high, – according to the distribution of scores in our sample.

Results

The number of ESRD patients in the high, intermediate, and low COC groups were 92 (22.33%), 130 (31.55%), and 190 (46.12%), respectively, and the mean follow-up periods for the 3 groups were 7.13, 7.12, and 7.27 years, respectively. After using inverse probability weighting, the intermediate and low COC groups were significantly associated with an increased risk of ESRD compared with the high COC group (adjusted hazard ratio (aHR) 1.36 [95% CI, 1.03–1.80] and aHR 1.76 [95% CI, 1.35–2.30], respectively). The intermediate and low COC groups were also significantly associated with the subsequent hospitalization compared with the high COC group (aHR 1.15 [95% CI, 0.99–1.33] and aHR 1.72 [95% CI, 1.50–1.97], respectively).

Conclusion

COC is related to ESRD onset and subsequent hospitalization among patients with DM. This study suggested that when DM patients keep visiting the same physician for managing their diseases, the progression of renal disease can be prevented.