Eric Renard

Prof. Eric Renard

orcid

Research Focus & Metrics

Academic Career Length

32Years (1995-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 June 2019 in Diabetes Care
Verified
Journal Article
Closed access
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TBTadej Battelino
Tadej Battelino
TDThomas Danne
Thomas Danne
RBRichard M. Bergenstal
Richard M. Bergenstal
SAStephanie A. Amiel
Stephanie A. Amiel
RBRoy Beck
Roy Beck
MPMoshe Phillip
Moshe Phillip
Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations.

18 October 2021 in Diabetes Care
Verified
Journal Article
Closed access
PDF file
RHRichard I.G. Holt
Richard I.G. Holt
JDJ. Hans DeVries
J. Hans DeVries
AHAmy Hess-Fischl
Amy Hess-Fischl
IHIrl B. Hirsch
Irl B. Hirsch
MKM. Sue Kirkman
M. Sue Kirkman
APAnne Peters
Anne Peters
The American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) convened a writing group to develop a consensus statement on the management of type 1 diabetes in adults. The writing group has considered the rapid development of new treatments and technologies and addressed the following topics: diagnosis, aims of management, schedule of care, diabetes self-management education and support, glucose monitoring, insulin therapy, hypoglycemia, behavioral considerations, psychosocial care, diabetic ketoacidosis, pancreas and islet transplantation, adjunctive therapies, special populations, inpatient management, and future perspectives. Although we discuss the schedule for follow-up examinations and testing, we have not included the evaluation and treatment of the chronic microvascular and macrovascular complications of diabetes as these are well-reviewed and discussed elsewhere. The writing group was aware of both national and international guidance on type 1 diabetes and did not seek to replicate this but rather aimed to highlight the major areas that health care professionals should consider when managing adults with type 1 diabetes. Though evidence-based where possible, the recommendations in the report represent the consensus opinion of the authors.

6 September 2022 in Endocrine Reviews
Verified
Journal Article
Open access
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MPMoshe Phillip
Moshe Phillip
RNRevital Nimri
Revital Nimri
RBRichard M Bergenstal
Richard M Bergenstal
KBKatharine Barnard-Kelly
Katharine Barnard-Kelly
TDThomas Danne
Thomas Danne
TBTadej Battelino
Tadej Battelino
The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage.

1 January 2011 in Genome Medicine
Verified
Journal Article
Open access
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PBPhilippe Jean Bousquet
Philippe Jean Bousquet
JAJosep M Anto
Josep M Anto
PSPeter J Sterk
Peter J Sterk
IAIan Adcock
Ian Adcock
KCKian Chung
Kian Chung
CACharles Auffray
Charles Auffray
We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems.

17 April 2016 in Diabetes Care
Verified
Journal Article
Open access
PDF file
EREric Renard
Eric Renard
AFAnne Farret
Anne Farret
JKJort Kropff
Jort Kropff
DBDaniela Bruttomesso
Daniela Bruttomesso
MMMirko Messori
Mirko Messori
JDJ. Hans DeVries
J. Hans DeVries
OBJECTIVE: After testing of a wearable artificial pancreas (AP) during evening and night (E/N-AP) under free-living conditions in patients with type 1 diabetes (T1D), we investigated AP during day and night (D/N-AP) for 1 month. RESEARCH DESIGN AND METHODS: Twenty adult patients with T1D who completed a previous randomized crossover study comparing 2-month E/N-AP versus 2-month sensor augmented pump (SAP) volunteered for 1-month D/N-AP nonrandomized extension. AP was executed by a model predictive control algorithm run by a modified smartphone wirelessly connected to a continuous glucose monitor (CGM) and insulin pump. CGM data were analyzed by intention-to-treat with percentage time-in-target (3.9–10 mmol/L) over 24 h as the primary end point. RESULTS: Time-in-target (mean ± SD, %) was similar over 24 h with D/N-AP versus E/N-AP: 64.7 ± 7.6 vs. 63.6 ± 9.9 (P = 0.79), and both were higher than with SAP: 59.7 ± 9.6 (P = 0.01 and P = 0.06, respectively). Time below 3.9 mmol/L was similarly and significantly reduced by D/N-AP and E/N-AP versus SAP (both P < 0.001). SD of blood glucose concentration (mmol/L) was lower with D/N-AP versus E/N-AP during whole daytime: 3.2 ± 0.6 vs. 3.4 ± 0.7 (P = 0.003), morning: 2.7 ± 0.5 vs. 3.1 ± 0.5 (P = 0.02), and afternoon: 3.3 ± 0.6 vs. 3.5 ± 0.8 (P = 0.07), and was lower with D/N-AP versus SAP over 24 h: 3.1 ± 0.5 vs. 3.3 ± 0.6 (P = 0.049). Insulin delivery (IU) over 24 h was higher with D/N-AP and SAP than with E/N-AP: 40.6 ± 15.5 and 42.3 ± 15.5 vs. 36.6 ± 11.6 (P = 0.03 and P = 0.0004, respectively). CONCLUSIONS: D/N-AP and E/N-AP both achieved better glucose control than SAP under free-living conditions. Although time in the different glycemic ranges was similar between D/N-AP and E/N-AP, D/N-AP further reduces glucose variability.

28 December 2020 in Diabetes/Metabolism Research and Reviews
Verified
Journal Article
Open access
PDF file
EREric Renard
Eric Renard
HIHiroshi Ikegami
Hiroshi Ikegami
AVAndré Gustavo Daher Vianna
André Gustavo Daher Vianna
PPPaolo Pozzilli
Paolo Pozzilli
SBSandrine Brette
Sandrine Brette
EWEmma G. Wilmot
Emma G. Wilmot
Aims: To describe glycaemic control and diabetes management in adults with type 1 diabetes (T1DM), in a real‐life global setting.Materials and Methods: Study of Adults' GlycEmia (SAGE) was a multinational, multicentre, single visit, noninterventional, cross‐sectional study in adult patients with T1DM. Data were collected at a single visit, analysed according to predefined age groups (26–44, 45–64 and ≥65 years) and reported across different regions. The primary endpoint was the proportion of participants achieving HbA1c less than 7.0 % in each age group. Secondary endpoints included incidence of hypoglycaemia, severe hypoglycaemia and severe hyperglycaemia leading to diabetic ketoacidosis (DKA) and therapeutic management of T1DM.Results: Of 3903 included participants, 3858 (98.8%) were eligible for the study. Overall, 24.3% (95% confidence interval [CI]: 22.9–25.6) of participants achieved the glycaemic target of HbA1c less than 7.0 %, with more participants achieving this target in the 26–44 years group (27.6% [95% CI: 25.5–29.8]). Target achievement was highest in Eastern and Western Europe, and lowest in the Middle East. The incidence of hypoglycaemia and of severe hyperglycaemia leading to DKA tended to decrease with age, and varied across regions. Age and regional differences were observed in therapeutic management, including types of device/insulin usage, frequency of insulin dose adjustment and technology usage.Conclusions: Glycaemic control remains poor in adults with T1DM globally. Several areas of treatment may be optimised to improve outcomes, including supporting patient self‐management of insulin therapy, increasing use of technologies such as CGM, and greater provision of healthcare support.