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AimsThere are few published data on the putative association between the ABO blood group/rhesus (Rh) factor and the risk of developing gestational diabetes mellitus (GDM). Our aim was to explore the link between each one factor and GDM development.MethodsAll women having given birth at Lille University Medical Center (Lille, France) between August 1st, 2017, and February 28th, 2018, were tested for GDM, using the method recommended in the French national guidelines. The risk of GDM was assessed for each ABO blood group, each Rh phenotype and combinations thereof, using logistic regression models.Results1194 women had at least one GDM risk factor. The percentage of GDM varied with the ABO group (p=0.013). Relative to group O women, group AB women were more likely to develop GDM (OR = 2.50, 95% CI [1.43 to 4.36], p=0.001). Compared with the Rh-positive O group, only the Rh-positive AB group had an elevated risk of developing GDM (OR = 3.02, 95% CI [1.69 to 5.39], p < 0.001).ConclusionsOur results showed that Rh-positive group AB women have a greater risk of GDM. With a view to preventing GDM, at-risk individuals could be identified by considering the ABO blood group phenotype either as a single risk factor or in combination with other risk factors.

Introduction Type 2 diabetes is a chronic condition associated with impaired glucose tolerance and a high prevalence of comorbidity, polypharmacy and medication safety incidents. Little is known about the patient work associated with using diabetes management technologies by patients and their informal caregivers at home. This study aims to apply a systems engineering approach to better understand this work.Methods and analysis This is a qualitative focused ethnographic study using interview and photography. Adults, living independently at home, with type 2 diabetes who have been using insulin as part of their treatment regimen for a minimum of 6 months and who are using at least one diabetes management technology without support of a professional at home are eligible for inclusion. Participants will be recruited through advertisements on social media, in diabetes clinics and by contacting associations of persons living with diabetes and diabetes specialists. Participant consent will be taken, interviews will be undertaken in the participant’s home, audio-recorded and photographs securely saved. The Systems Engineering Initiative for Patient Safety (SEIPS) model will frame the data coding and we will develop new codes to accommodate data outside the SEIPS model. Results will be interpreted to produce a description of work processes, work system elements and interactions that support or jeopardise the achievement of safety. This protocol will follow the consolidated criteria for reporting qualitative research checklist for the reporting of qualitative research interviews.Ethical considerations and dissemination This protocol was approved by the University of Lille’s Behavioural Sciences Ethics Committee. The study will comply with data protection legislation: the protocol has been declared by the Data Protection Officer of the University of Lille to the National Commission on Informatics and Liberty. We plan to disseminate our findings via presentations at relevant patient/public, professional, academic and scientific meetings, and publish in a peer-reviewed journal.

Gérard Reach,1 Laurent Benarbia,2 Pierre-Yves Benhamou,3 Brigitte Delemer,4 Séverine Dubois,5 Didier Gouet,6 Bruno Guerci,7 Nathalie Jeandidier,8 Karim Lachgar,9 Gilles Le Pape,10 Rémy Leroy,11 Jean-Hugues Masgnaux,12 Philippe Raclet,13 Yves Reznik,14 Jean-Pierre Riveline,15,16 Pauline Schaepelynck,17 Anne Vambergue,18 Bruno Vergès19 1Health Education and Promotion Laboratory (LEPS EA 3412), Sorbonne Paris Nord University, Bobigny, France; 2Marketing Studio, Paris, France; 3Department of Endocrinology, Grenoble University Hospital; Grenoble Alpes University, INSERM U1055, LBFA, Grenoble, France; 4Service d’Endocrinologie – Diabète – Nutrition, CHU de Reims - Hôpital Robert Debré, and Université de Reims Champagne Ardenne, UFR Sciences Exactes Et Naturelles, Reims, France; 5Department of Diabetology and Endocrinology, CHU Angers, Angers, France; 6Department of Diabetology and Endocrinology, Saint Louis Hospital, La Rochelle, France; 7Department of Endocrinology, Diabetology and Nutrition, CHRU of Nancy, Brabois Hospital, and ILCV Lorraine University, Vandoeuvre-les-Nancy, France; 8Department of Endocrinology, Diabetes and Nutrition, Hôpitaux Universitaires de Strasbourg, and Université de Strasbourg, Strasbourg, France; 9Department of Diabetology and Endocrinology, Centre Hospitalier Simone Veil, Eaubonne, France; 10General Practice, Penmarc’h, France; 11Private Medical Practice, Endocrinology and Diabetology, Lille, France; 12M&M Conseil, Boulogne, France; 13Association Française des Diabétiques de Bourgogne Franche-Comté, Dijon, France; 14Department oEndocrinology and Diabetology, CHU Côte de Nacre, Caen, and University of Caen Basse-Normandie, Medical School, Caen, France; 15Department of Diabetology and Endocrinology, Lariboisière Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France; 16Unité INSERM U1138 Immunity and Metabolism in Diabetes, ImMeDiab Team, Centre de Recherches des Cordeliers, and Université de Paris, Paris, France; 17Department of Nutrition-Endocrinology-Metabolic Diseases, Pôle ENDO, APHM-Hôpital la Conception, Marseille, France; 18Department of Diabetology, Endocrinology, Metabolism and Nutrition, CHU Lille, and University Hospital European Genomic Institute for Diabetes, Lille, France; 19Department of Endocrinology-Diabetology,CHU Dijon, and University of Burgundy, INSERM LNC UMR1231, Dijon, FranceCorrespondence: Gérard Reach, Health Education and Promotion Laboratory (LEPS EA 3412), Sorbonne Paris Nord University, 74 Rue Marcel Cachin, Bobigny Cedex, 93017, France, Tel + 33 (0)6 60 84 53 25, Email gerardreach@icloud.comBackground: Support programs are provided to people with diabetes to help them manage their disease. However, adherence to and persistence in support programs are often low, making it difficult to demonstrate their effectiveness.Aim: To identify the determinants of patients’ perceived interest in diabetes support programs because it may be a powerful determinant of effective participation in such programs.Patients and Methods: An online study conducted in April 2021 in metropolitan France on 600 people with diabetes recruited from a consumer panel. A 64-item psychosocial questionnaire including a question asking to evaluate the helpfulness of a support program was used. Univariate, multivariate, and multiple correspondence analyses were performed.Results: The existence of a typology, known as Unsafe/Safe, was discovered, in which patients with type 2 diabetes respond in two distinct ways. Type U (unsafe) patients, who believe that a support program would be helpful, are more likely to be nonadherent to their treatment, have high hemoglobin A1c levels, have at least one diabetic complication, lack information regarding their disease and treatment, rate the burden of their disease and impairment of their quality of life as high, worry about their future, and are pessimistic. Type S (safe) patients have the opposite characteristics. Type U patients can be dichotomized into two broad classes: one in which they lack information regarding disease and treatment and the other in which alterations in the quality of life and burden of the disease predominate. Insulin-treated patients give more importance to the lack of information, whereas noninsulin-treated patients complain primarily about the burden of the disease and impairment of quality of life.Conclusion: This study describes this new U/S typology, proposes a simple method based on a nine-item questionnaire to identify type U patients by calculating a Program Helpfulness Score described herein, and clarifies the nature of the intervention to be provided to them. This novel approach could be applied to other chronic diseases.Keywords: type 2 diabetes, adherence, support programs, typology, personality traits, clinical outcomes, patients’ expectations

Purpose: The management of type 2 diabetes mellitus patients has changed over the past decade, and a large number of antidiabetic drug treatment options are now available. This complexity poses challenges for healthcare professionals and may result in potentially inappropriate prescriptions of antidiabetic drugs in patients with type 2 diabetes mellitus which can be limited using screening tools. The effectiveness of explicit tools such as lists of potentially inappropriate prescriptions has been widely demonstrated. The aim was to set up nominal groups of healthcare professionals from several disciplines and develop a list of explicit definition of potentially inappropriate prescriptions of antidiabetic drugs. Methods: In a qualitative, nominal-groups approach, 30 diabetologists, general practitioners, and pharmacists in France developed explicit definitions of potentially inappropriate prescriptions of antidiabetic drugs in patients with type 2 diabetes mellitus. A nominal group technique is a structured method that encourages all the participants to contribute and makes it easier to reach an agreement quickly. Each meeting lasted for two hours. Results: The three nominal groups comprised 14 pharmacists, 10 diabetologists, and 6 general practitioners and generated 89 explicit definitions. These definitions were subsequently merged and validated by the steering committee and nominal group participants, resulting in 38 validated explicit definitions of potentially inappropriate prescriptions of antidiabetic drugs. The definitions encompassed four contexts: (i) the temporary discontinuation of a medication during acute illness (n = 9; 24%), (ii) dose level adjustments (n = 23; 60%), (iii) inappropriate treatment initiation (n = 3; 8%), and (iv) the need for further monitoring in the management of type 2 diabetes mellitus (n = 3; 8%). Conclusion: The results of our qualitative study show that it is possible to develop a specific list of explicit definitions of potentially inappropriate prescriptions of antidiabetic drugs in patients with type 2 diabetes mellitus by gathering the opinions of healthcare professionals caring for these patients. This list of 38 explicit definitions necessitates additional confirmation by expert consensus before use in clinical practice. [ABSTRACT FROM AUTHOR]

Aims: The objective of the study was to describe the impact of a clinical decision support system (CDSS) on antidiabetic drug management by clinical pharmacists for hospitalized patients with T2DM. Methods: We performed a retrospective, single‐centre study in a teaching hospital, where clinical pharmacists analysed prescriptions and issued pharmacist interventions (PIs) through a computerized physician order entry (CPOE) system. A CDSS was integrated into the pharmacists' workflow in July 2019. We analysed PIs during 2 periods of interest: one before the introduction of the CDSS (from November 2018 to April 2019, PIs issued through the CPOE alone) and one afterwards (from November 2020 to April 2021, PIs issued through the CPOE and/or the CDSS). The study covered nondiabetology wards as endocrinology, diabetes and metabolism departments were not computerized at the time of the study. Results: There were 203 PIs related to antidiabetic drugs in period 1 and 319 in period 2 (a 57.5% increase). Sixty‐four of the 319 PIs were generated by the CDSS. Noncompliance/contraindication was the main problem identified by the CDSS (41 PIs, 68.4%), and 57.8% led to discontinuation of the drug. Most of the PIs issued through the CDSS corresponded to orders that had not been flagged up by clinical pharmacists using the CPOE. Conversely, most alerts about indications that were not being treated were detected by the clinical pharmacists using the CPOE and not by the CDSS. Conclusion: Use of CDSS by clinical pharmacists improved antidiabetic drug management for hospitalized patients with T2DM. The CDSS might add value to diabetes care in nondiabetology wards by decreasing the frequency of potentially inappropriate prescriptions and adverse drug reactions. [ABSTRACT FROM AUTHOR]