[NICE Consultation] Type 2 diabetes in adults: management – SGLT2 inhibitors for chronic kidney disease (update)

NICE |  September 2021 | Type 2 diabetes in adults: management – SGLT2 inhibitors for chronic kidney disease (update) In development [GID-NG10246]Expected publication date: 24 November 2021

This guidance will partially update the following:

This consultation is open until 29 September 2021 at 5pm

Full details, and consultation documents are available from NICE

Glycaemic control during the lockdown for COVID-19 in adults with type 1 diabetes #Covid19RftLks

Garofolo, M. et al | 2021| Glycaemic control during the lockdown for COVID-19 in adults with type 1 diabetes: A meta-analysis of observational studies | Diabetes Research and Clinical Practice | doi: https://doi.org/10.1016/j.diabres.
2021.109066

This review is available online ahead of print. It updates an earlier systematic systematic review and meta-analysis of studies assessing the effects of lockdown during COVID-19 pandemic on glucose metrics in adult subjects
with type 1 diabetes using continuous glucose monitoring (CGM) and flash glucose monitoring (FGM).

The reviewers report that in their meta-analysis of aggregate data shows that well-controlled people with type 1
diabetes on both MDI and CSII with continuous or flash glucose monitoring did not experience a 14 deterioration in glucose control throughout the COVID-19 lockdown, showing a modest, though statistically significant improvement in many glucose control parameters (Garofolo et al, 2021).

Abstract

Aims:

To assess the effects of lockdown due to COVID-19 pandemic on glucose metrics, measured by glucose monitoring systems, in adult individuals with type 1 diabetes.

Methods: We conducted a systematic literature search for English language articles from MEDLINE, Scopus and Web of Science up to February 28, 2021, using “diabetes”, “lockdown”, and “glucose” as key search terms. Time in range (TIR) was the main outcome; other metrics were time above range (TAR), time below range (TBR), mean blood glucose (MBG) and its variability ( per cent CV), estimated HbA1c (eA1c) or glucose management indicator (GMI).

Results: Seventeen studies for a total of 3,441 individuals with type 1 diabetes were included in the analysis. In the lockdown period, TIR 70-180 mg/dl increased by 3.05 per cent declined by 3.39 per cent (-5.14 to -1.63 per cent ) and 1.96 per cent (-2.51 to -1.42 per cent ), respectively (p less than 0.0001 for both). Both TBR less than 70 and less than 54 mg/dL remained unchanged. MBG slightly decreased by 5.40 mg/dL (-7.29 to – 3.51 mg/dL; p less than 0.0001) along with a reduction in per centCV. Pooled eA1c and GMI decreased by 0.18 per cent (-0.24 to -0.11 per cent ; p less than 0.0001) and a similar reduction was observed when GMI alone was considered (0.15 per cent, -0.23 to – 0.07 per cent; p less than 0.0001). Sensor use was only slightly but not significantly reduced during lockdown.

Conclusions: This meta-analysis shows that well-controlled people with type 1 diabetes on both MDI and CSII with continuous or flash glucose monitoring did not experience a deterioration in glucose control throughout the COVID-19 lockdown, showing a modest, though statistically significant improvement in many glucose control parameters.

Glycaemic control during the lockdown for COVID-19 in adults with type 1 diabetes: A meta-analysis of observational studies [paper ahead of print]

Mindfulness in Relation to Diet Quality in Adults with Type 1 and Type 2 Diabetes: Results from Diabetes MILES-The Netherlands

Liu, S. et al | 2021| Mindfulness in Relation to Diet Quality in Adults with Type 1 and Type 2 Diabetes: Results from Diabetes MILES-The Netherlands| Mindfulness | https://doi.org/10.1007/s12671-021-01754-x

The objective of this research was to investigate the associations between dispositional mindfulness and diet quality in Dutch adults with type 1 diabetes (T1DM) or type 2 diabetes (T2DM). They hypothesized that a higher level of mindfulness is related to greater diet quality. In the light of previous research in other populations (Sala et al., 2020), they theorised that each mindfulness facet is positively associated with diet quality. In addition, they evaluated the potential mediating role of emotional distress in these associations.

The researchers found that a higher level of dispositional mindfulness and a higher score on observing were associated with higher diet quality. The results were more robust in people with T1DM. Their findings also suggest that overall mindfulness and the facet of observing are associated with higher diet quality in people with diabetes, independent of emotional distress.

They conclude that their findings suggest that mindfulness, especially observing facet, may relate to a healthier diet in adults with diabetes (Source: Liu et al, 2021).

The full paper is available to read from Mindfulness

Quality of complementary and alternative medicine information for type 2 diabetes: a cross-sectional survey and quality assessment of websites

Ng, J.Y., Nayeni, M. & Gilotra, K. | 2021| Quality of complementary and alternative medicine information for type 2 diabetes: a cross-sectional survey and quality assessment of websites| BMC Complement Med Ther | 21 | 233| https://doi.org/10.1186/s12906-021-03390-3

This study addresses a gap in the literature, it set out to identify and assess the quality of consumer health information presented online for CAM-specific treatment and/or management options for type 2 diabetes mellitus (T2DM). They report that their subset contained low quality consumer health information; noting that the websites included for assessment often failed to provide adequate references to support their health statements (Ng, Nayeni, & Gilotra, 2021).

Abstract

Background

The global prevalence of diabetes mellitus is projected to reach approximately 700 million by the year 2045, with roughly 90–95% of all diabetes cases being type 2 in nature. Patients with type 2 diabetes mellitus (T2DM) frequently seek information about complementary and alternative medicine (CAM) online. This study assessed the quality of publicly accessible websites providing consumer health information at the intersection of T2DM and CAM.

Methods

An online search engine (Google) was searched to identify pertinent websites containing information specific to CAM for T2DM patients, and the relevant websites were then screened with an eligibility criteria. Consumer health information found on eligible websites were then assessed for quality using the DISCERN instrument, a 16-item standardized scoring system.

Results

Across the 480 webpages identified, 94 unique webpages remained following deduplication, and 37 eligible webpages belonged to and were collapsed into 30 unique websites that were each assessed using the DISCERN instrument. The mean overall quality score (question 16) across all 30 assessed websites was 3.55 (SD = 0.86), and the mean summed DISCERN score was 52.40 (SD = 12.11). Eighty percent of websites presented a wide range of CAM treatment options with the associated benefits/risks of each treatment, but in 56.7% of the websites, the sources used to collect information were unreliable.

Conclusion

This study identified, assessed, and presents findings on the quality of online CAM information for T2DM. Although there were several high scoring websites, there was variability across most of the individual DISCERN items in the assessed websites. This study highlights the importance of awareness among healthcare providers regarding the reliability of online information about CAM treatment and management options for T2DM. Healthcare providers should be aware of patients’ information seeking behaviour, guide them in navigating through the content they encounter online, and provide them with resources containing trustworthy and reliable information.

Quality of complementary and alternative medicine information for type 2 diabetes: a cross-sectional survey and quality assessment of websites [primary paper]

[Free Diabetes UK Conference] Type 1 and Tech

Diabetes UK | September 2021 | Type 1 and Tech

Diabetes UK is holding an online conference for people living with type 1 diabetes, parents of children with type 1 diabetes, carers and healthcare professionals. Professor Partha Kar is hosting the conference.

The programme covers topics from emotional health, sports, exercise and pregnancy, you’ll be joining an exciting day of discussion around improving access to diabetes technology as well as the challenges and opportunities posed by the coronavirus pandemic.

The conference is held on Saturday 16 October, 10.00am to 2.00pm 

Full details are available from Diabetes UK

Image source: Diabetes UK Image is a poster to promote the conference, this poster is available to download from Diabetes UK

Registration

Identifying adults at high-risk for change in weight and BMI in England: a longitudinal, large-scale, population-based cohort study using electronic health records

Katsoulis, M. et al | 2021 | Identifying adults at high-risk for change in weight and BMI in England: a longitudinal, large-scale, population-based cohort study using electronic health records | The Lancet Diabetes & Endocrinology | https://doi.org/10.1016/S2213-8587(21)00207-2

The researchers behind this paper use electronic health records of over 2 million people to address four research objectives:

(1) to test the extent to which temporal trends in mean BMI changes between 1998 and 2016 are replicated between EHRs and survey methods

 (2) to compare the extent and distribution of BMI changes across age groups and BMI categories

(3) to estimate the associations between age, sex, degree of social deprivation, ethnicity, and geographical region with transitions across BMI categories

(4) to produce a risk calculator (both online and in chart-form), showing how these risk factors combine to identify groups at a high risk of transitioning to higher BMI categories.

Their findings show that young adults (aged 18–24 years) had a markedly greater risk for transitioning to higher BMI categories than did older age groups (ie, those aged 65–74 years). Compared with age, the researchers found smaller additional contributions to the risk of BMI change, including being male, living in socially deprived neighbourhoods, and being from a Black ethnic background. . The authors provide the first estimates of the risks of transitioning between underweight, normal weight, overweight, and obesity BMI categories at 1, 5, and 10 years (risk charts and an online tool). They also show the value of using longitudinal population-based EHRs to identify and monitor specific population groups at risk of weight gain (Source: Katsoulis et al, 2021).

Summary

Background

Targeted obesity prevention policies would benefit from the identification of population groups with the highest risk of weight gain. The relative importance of adult age, sex, ethnicity, geographical region, and degree of social deprivation on weight gain is not known. We aimed to identify high-risk groups for changes in weight and BMI using electronic health records (EHR).

Methods

In this longitudinal, population-based cohort study we used linked EHR data from 400 primary care practices (via the Clinical Practice Research Datalink) in England, accessed via the CALIBER programme. Eligible participants were aged 18–74 years, were registered at a general practice clinic, and had BMI and weight measurements recorded between Jan 1, 1998, and June 30, 2016, during the period when they had eligible linked data with at least 1 year of follow-up time. We calculated longitudinal changes in BMI over 1, 5, and 10 years, and investigated the absolute risk and odds ratios (ORs) of transitioning between BMI categories (underweight, normal weight, overweight, obesity class 1 and 2, and severe obesity [class 3]), as defined by WHO. The associations of demographic factors with BMI transitions were estimated by use of logistic regression analysis, adjusting for baseline BMI, family history of cardiovascular disease, use of diuretics, and prevalent chronic conditions.

Findings

We included 2 092 260 eligible individuals with more than 9 million BMI measurements in our study. Young adult age was the strongest risk factor for weight gain at 1, 5, and 10 years of follow-up. Compared with the oldest age group (65–74 years), adults in the youngest age group (18–24 years) had the highest OR (4·22 [95 per cent  CI 3·86–4·62]) and greatest absolute risk (37 per cent vs 24 per cent ) of transitioning from normal weight to overweight or obesity at 10 years. Likewise, adults in the youngest age group with overweight or obesity at baseline were also at highest risk to transition to a higher BMI category; OR 4·60 (4·06–5·22) and absolute risk (42 per cent  vs 18 per cent ) of transitioning from overweight to class 1 and 2 obesity, and OR 5·87 (5·23–6·59) and absolute risk (22 per cent  vs 5 per cent ) of transitioning from class 1 and 2 obesity to class 3 obesity. Other demographic factors were consistently less strongly associated with these transitions; for example, the OR of transitioning from normal weight to overweight or obesity in people living in the most socially deprived versus least deprived areas was 1·23 (1·18–1·27), for men versus women was 1·12 (1·08–1·16), and for Black individuals versus White individuals was 1·13 (1·04–1·24). We provide an open access online risk calculator, and present high-resolution obesity risk charts over a 1-year, 5-year, and 10-year follow-up period.

Interpretation

A radical shift in policy is required to focus on individuals at the highest risk of weight gain (ie, young adults aged 18–24 years) for individual-level and population-level prevention of obesity and its long-term consequences for health and health care.

Identifying adults at high-risk for change in weight and BMI in England: a longitudinal, large-scale, population-based cohort study using electronic health records

Healthcare shift workers with type 2 needed for study

The Shift-Diabetes study | nd | Healthcare shift workers with type 2 needed for study

Researchers at King’s College London are recruiting hospital or residential care-based shift workers(any job role) with diagnosed type 2 diabetes and are interested in helping with their research to understand more about how shift work influences diet and blood sugar levels in people with type 2 diabetes as part of a Diabetes UK funded study.

The study has two parts, a monitoring study and an informal interview, participants can choose to be part of one or both.

Full details from the study’s page The Shift-Diabetes study

TikTok as a Health Information Source: Assessment of the Quality of Information in Diabetes-Related Videos

Kong, W., Song, S., Zhao, Y.C., Zhu, Q. & Sha, L. | 2021 |
TikTok as a Health Information Source: Assessment of the Quality of Information in Diabetes-Related Videos|
J Med Internet Res| 23| 9| e30409 | doi: 10.2196/30409| PMID: 34468327

Published in the Journal of Medical Internet Research this paper looks at the quality of information in diabetes-related videos on the TikTok social media platform. The study assessed almost 200 diabetes video on TikTok, the overall quality of the diabetes videos was found to be acceptable on average, although it varied significantly, depending on the type of source. The authors conclude that the health information needs of patients with diabetes might not be fully met by watching TikTok videos, and patients should exercise caution when using TikTok for diabetes-related information.

Abstract

Background: Diabetes has become one of the most prevalent chronic diseases, and many people living with diabetes use social media to seek health information. Recently, an emerging social media app, TikTok, has received much interest owing to its popularity among general health consumers. We notice that there are many videos about diabetes on TikTok. However, it remains unclear whether the information in these videos is of satisfactory quality.

Objective: This study aimed to assess the quality of the information in diabetes-related videos on TikTok.

Methods: We collected a sample of 199 diabetes-related videos in Chinese. The basic information presented in the videos was coded and analyzed. First, we identified the source of each video. Next, 2 independent raters assessed each video in terms of the completeness of six types of content (the definition of the disease, symptoms, risk factors, evaluation, management, and outcomes). Then, the 2 raters independently assessed the quality of information in the videos, using the DISCERN instrument.

Results: In regard to the sources of the videos, we found 6 distinct types of uploaders; these included 3 kinds of individual users (ie, health professionals, general users, and science communicators) and 3 types of organizational users (ie, news agencies, nonprofit organizations, and for-profit organizations). Regarding content, our results show that the videos were primarily about diabetes management and contained limited information on the definition of the disease, symptoms, risk factors, evaluation, and outcomes. The overall quality of the videos was acceptable, on average, although the quality of the information varied, depending on the sources. The videos created by nonprofit organizations had the highest information quality, while the videos contributed by for-profit organizations had the lowest information quality.

Conclusions: Although the overall quality of the information in the diabetes videos on TikTok is acceptable, TikTok might not fully meet the health information needs of patients with diabetes, and they should exercise caution when using TikTok as a source of diabetes-related information.

TikTok as a Health Information Source: Assessment of the Quality of Information in Diabetes-Related Videos [primary paper]

Insulin Treatment May Increase Adverse Outcomes in Patients With COVID-19 and Diabetes: A Systematic Review and Meta-Analysis

Yang, Y.,  Zixin, C. & Zhang, J. | 2021| Insulin Treatment May Increase Adverse Outcomes in Patients With COVID-19 and Diabetes: A Systematic Review and Meta-Analysis | Frontiers in Endocrinology | https://doi.org/10.3389/fendo.2021.696087

The reviewers invovlved in this analysis, conducted a systematic review and meta-analysis to determine the association between insulin injection and the outcomes of COVID-19 to provide certain clinical information for patients with Covid-19 and diabetes. They recognise that while their findings may provide evidence of the adverse effect of insulin treatment among patients with COVID-19 and diabetes, especially among those with type 2 diabetes (T2DM), as the subjects in most included studies suffered from T2DM. However, considering the limited number of studies concerning type 1 diabetes (T1DM) in our meta-analysis, the association between insulin treatment and adverse outcomes in patients with COVID-19 and T1DM are needed to be investigated in more large-scale clinical studies (Source: Yang, Zixin & Zhang, 2021).

Background and Objective: 

Recently, insulin treatment has been found to be associated with increased mortality and other adverse outcomes in patients with coronavirus disease 2019 (COVID-19) and diabetes, but the results remain unclear and controversial, therefore, we conducted this meta-analysis.

Methods: 

Four databases, namely, PubMed, Web of Science, EMBASE and the Cochrane Library, were used to identify all studies concerning insulin treatment and the adverse effects of COVID-19, including mortality, incidence of severe/critical complications, in-hospital admission and hospitalization time. To assess publication bias, funnel plots, Begg’s tests and Egger’s tests were used. The odds ratios (ORs) with 95% confidence intervals (CIs) were used to access the effect of insulin therapy on mortality, severe/critical complications and in-hospital admission. The association between insulin treatment and hospitalization time was calculated by the standardized mean difference (SMD) with 95% CIs.

Results: 

Eighteen articles, involving a total of 12277 patients with COVID-19 and diabetes were included. Insulin treatment was significantly associated with an increased risk of mortality (OR=2.10; 95% CI, 1.51-2.93) and incidence of severe/critical COVID-19 complications (OR=2.56; 95% CI, 1.18-5.55). Moreover, insulin therapy may increase in-hospital admission in patients with COVID-19 and diabetes (OR=1.31; 95% CI, 1.06-1.61). However, there was no significant difference in the hospitalization time according to insulin treatment (SMD=0.21 95% CI, -0.02-0.45).

Conclusions: 

Insulin treatment may increase mortality and severe/critical complications in patients with COVID-19 and diabetes, but more large-scale studies are needed to confirm and explore the exact mechanism.

Insulin Treatment May Increase Adverse Outcomes in Patients With COVID-19 and Diabetes: A Systematic Review and Meta-Analysis [primary paper]