Screening for diabetic kidney disease in primary care: A quality improvement initiative

Intelligent Algorithm-Based Ultrasound Image for Evaluating the Effect of Comprehensive Nursing Scheme on Patients with Diabetic Kidney Disease

This study was aimed at exploring the effect of ultrasound image evaluation of comprehensive nursing scheme based on artificial intelligence algorithms on patients with diabetic kidney disease (DKD). 44 patients diagnosed with DKD were randomly divided into two groups: group A (no nursing intervention) and group B (comprehensive nursing). In the same period, 32 healthy volunteers were selected as the control group. Ultrasonographic images based on the $K$ non-local-means (KNL-Means) filtering algorithm were used to perform imaging examinations in healthy people and DKD patients before and after care. The results suggested that compared with those of the SAE reconstruction algorithm and KAVD reconstruction algorithm, the PSNR value of artificial bee colony algorithm reconstruction of image was higher and the MSE value was lower. The resistant index (RI) of DKD patients in group B after nursing was $0.63\pm 0.06$ , apparently distinct from the RI of the healthy people (controls) in the same group ( $0.58\pm 0.06$ ) and the RI of DKD patients in group A ( $0.68\pm 0.07$ ) ( $P<0.05$ ). The incidence rate of complications in DKD patients in group B was apparently inferior to that in group A. After comprehensive nursing intervention (CNI), the scores of all dimensions of quality of life (QoL) in DKD patients in group B were obviously superior versus those in DKD patients in group A. It suggests that implementation of nursing intervention for DKD patients can effectively help patients improve and control the level of renal function, while ultrasound images based on intelligent algorithm can dynamically detect the changes in the level of renal function in patients, which has the value of clinical promotion.

Improving annual albuminuria testing for individuals with diabetes

Background

Annual albuminuria screening detects the early stages of nephropathy in individuals with diabetes. Because early detection of albuminuria allows for interventions that lower the risk of developing chronic kidney disease, guidelines recommend annual testing for all individuals with type 2 diabetes mellitus and for those with type 1 diabetes for at least 5 years. However, at the Eskind Diabetes Clinic at the Vanderbilt University Medical Center, testing occurred less frequently than desired.

Methods

A quality improvement team first analysed the clinic’s processes, identifying the lack of a systematic approach to testing as the likely cause for the low rate. The team then implemented two successive interventions in a pilot of patients seen by nurse practitioners in the clinic. In the first intervention, staff used a dashboard within the electronic health record while triaging each patient, pending an albuminuria order if testing had not been done within the past year. In the second intervention, clinic leadership sent daily reminders to the triage staff. A statistical process control chart tracked monthly testing rates.

Results

After 6 months, annual albuminuria testing increased from a baseline of 69% to 82%, with multiple special-cause signals in the control chart.

Conclusions

This project demonstrates that a series of simple interventions can significantly impact annual albuminuria testing. This project’s success likely hinged on using an existing workflow to systematically determine if a patient was due for testing and prompting the provider to sign a pended order for an albuminuria test. Other diabetes/endocrinology and primary care clinics can likely implement a similar process and so improve testing rates in other settings. When coupled with appropriate interventions to reduce the development of chronic kidney disease, such interventions would improve patient outcomes, in addition to better adhering to an established quality metric.

The effect of monomeric and oligomeric FLAVAnols in patients with type 2 diabetes and microalbuminuria (FLAVA-trial): A double-blind randomized controlled trial

BACKGROUND & AIMS

Microalbuminuria is an early sign of vascular complications of type 2 diabetes and predicts cardiovascular disease and mortality. Monomeric and oligomeric flavanols (MOFs) are linked to improved vascular health. The aim of this study was to assess the effect of 3 months MOFs on albuminuria and endothelial function markers in patients with type 2 diabetes and microalbuminuria.

METHODS

We conducted a double-blind, placebo-controlled trial among patients with type 2 diabetes and microalbuminuria. Patients with type 2 diabetes received either 200 mg MOFs or placebo daily on top of their habitual diet and medication. The primary endpoint was the between-group difference of the change in 24-h Albumin Excretion Rate (AER) over three months. Secondary endpoints were the between-group differences of the change in plasma levels of different markers of endothelial dysfunction. Mixed-modelling was applied for the longitudinal analyses.

RESULTS

Participants (n = 97) were 63.0 ± 9.5 years old; diabetes-duration was 15.7 ± 8.5 years. Median baseline AER was 60 (IQR 20-120) mg/24 h. There was no within-group difference in median change of AER from baseline to 3 months in the intervention (0 (-35-21) mg/24 h, p = 0.41) or the control group (0 (-20-10) mg/24 h, p = 0.91). There was no between-group difference in the course of AER over three months (log-transformed data: β = -0.02 (95%CI -0.23-0.20), p = 0.88), nor in the plasma levels of the endothelial dysfunction markers.

CONCLUSION

Daily 200 mg MOFs for three months on top of habitual diet and usual care did not reduce AER and plasma markers of endothelial dysfunction compared to placebo, in patients with long-term type 2 diabetes and microalbuminuria.

CLINICAL TRIALS REGISTRATION

NTR4669, www.trialregister.nl.

Real-World Diagnosis and Treatment of Diabetic Kidney Disease

INTRODUCTION

People with type 2 diabetes mellitus (T2DM) and diabetic kidney disease (DKD) have increased morbidity and mortality risk. Angiotensin-converting enzyme inhibitors (ACEi) or angiotensin II receptor blockers (ARB) are recommended to slow kidney function decline in DKD. This representative, real-world data analysis of patients with T2DM was performed to detect onset of DKD and determine methods and timing of DKD diagnosis and time to initiation of ACEi/ARB therapy.

METHODS

Patients diagnosed with T2DM before January 1, 2016 who developed DKD between January 1, 2017 and June 30, 2019 were identified from a longitudinal ambulatory electronic health record (EHR) dataset (Veradigm Inc). Each record was analyzed using the CLinical INTelligence engine (CLINT™, HealthPals, Inc.) to identify delays and gaps in diagnosing DKD. DKD was diagnosed through two reduced estimated glomerular filtration rate (eGFR; < 60 mL/min/1.73 m²) measurements at least 90 days apart, a single elevated urine albumin-to-creatinine ratio (UACR; > 30 mg/g) measurement, or ICD-9/10 diagnosis codes for DKD and/or albuminuria. Time to diagnose (TTD), time to treat (TTT), and diagnosis to treatment time were assessed.

RESULTS

Of 6,499,409 patients with T2DM before January 2016, 245,978 developed DKD between January 1, 2017 and June 30, 2019. In this DKD cohort, ca. 50% were first identified through EHR diagnosis and ca. 50% by UACR or eGFR lab-based diagnosis. In patients who had UACR/eGFR assessed, more than 90% exhibited DKD-level results on the first diagnostic test. Average TTD after eGFR labs was 2 years; average TTT with ACEi/ARB was 6-9 months after DKD lab evidence. The majority of patients who developed DKD received ACEi/ARB therapy 6-7 months after diagnosis.

CONCLUSION

In a contemporary, large national cohort of patients with T2DM, progression to DKD was common but likely underrepresented. The low rate of DKD-screening labs, along with sizable delays in diagnosis of DKD and initiation of ACEi/ARB therapy, indicates that many patients who progress to DKD are not being properly treated.