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Abdelmalak N, Burns J, Suhlrie L, Laxy M, Stephan AJ. Consideration of inequalities in effectiveness trials of mHealth applications - a systematic assessment of studies from an umbrella review. Int J Equity Health 2024; 23:181. [PMID: 39261871 PMCID: PMC11389088 DOI: 10.1186/s12939-024-02267-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2024] [Accepted: 09/01/2024] [Indexed: 09/13/2024] Open
Abstract
BACKGROUND The growing use of mobile health applications (apps) for managing diabetes and hypertension entails an increased need to understand their effectiveness among different population groups. It is unclear if efficacy and effectiveness trials currently provide evidence of differential effectiveness, and if they do, a summary of such evidence is missing. Our study identified to what extent sociocultural and socioeconomic inequalities were considered in effectiveness trials of mobile health apps in diabetic and hypertensive patients and if these inequalities moderated app effectiveness. METHODS We built on our recent umbrella review that synthesized systematic reviews (SRs) of randomized controlled trials (RCTs) on the effectiveness of health apps. Using standard SR methodologies, we identified and assessed all primary RCTs from these SRs that focused on diabetes and/or hypertension and reported on health-related outcomes and inequality-related characteristics across intervention arms. We used the PROGRESS-Plus framework to define inequality-related characteristics that affect health opportunities and outcomes. We used harvest plots to summarize the subgroups (stratified analyses or interaction terms) on moderating effects of PROGRESS-Plus. We assessed study quality using the Risk of Bias 2 tool. RESULTS We included 72 published articles of 65 unique RCTs. Gender, age, and education were the most frequently described PROGRESS-Plus characteristics at baseline in more than half of the studies. Ethnicity and occupation followed in 21 and 15 RCTs, respectively. Seven trials investigated the moderating effect of age, gender or ethnicity on app effectiveness through subgroup analyses. Results were equivocal and covered a heterogenous set of outcomes. Results showed some concerns for a high risk of bias, mostly because participants could not be blinded to their intervention allocation. CONCLUSIONS Besides frequently available gender, age, and education descriptives, other relevant sociocultural or socioeconomic characteristics were neither sufficiently reported nor analyzed. We encourage researchers to investigate how these characteristics moderate the effectiveness of health apps to better understand how effect heterogeneity for apps across different sociocultural or socioeconomic groups affects inequalities, to support more equitable management of non-communicable diseases in increasingly digitalized systems. REGISTRATION https://osf.io/89dhy/ .
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Affiliation(s)
- Nancy Abdelmalak
- Professorship of Public Health and Prevention, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany.
| | - Jacob Burns
- Professorship of Public Health and Prevention, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Laura Suhlrie
- Professorship of Public Health and Prevention, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Michael Laxy
- Professorship of Public Health and Prevention, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
| | - Anna-Janina Stephan
- Professorship of Public Health and Prevention, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany
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Hermanns N, Ehrmann D, Finke-Groene K, Krichbaum M, Roos T, Haak T, Freckmann G, Kulzer B. Use of smartphone application versus written titration charts for basal insulin titration in adults with type 2 diabetes and suboptimal glycaemic control (My Dose Coach): multicentre, open-label, parallel, randomised controlled trial. THE LANCET REGIONAL HEALTH. EUROPE 2023; 33:100702. [PMID: 37954005 PMCID: PMC10636267 DOI: 10.1016/j.lanepe.2023.100702] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/07/2023] [Accepted: 07/12/2023] [Indexed: 11/14/2023]
Abstract
Background The majority of people with type 2 diabetes who require insulin therapy use only basal insulin in combination with other anti-diabetic agents. We tested whether using a smartphone application to titrate insulin could improve glycaemic control in people with type 2 diabetes who use basal insulin. Methods This was a 12-week, multicentre, open-label, parallel, randomised controlled trial conducted in 36 diabetes practices in Germany. Eligible participants had type 2 diabetes, a BMI ≥25.0 kg/m2, were on basal insulin therapy or were initiating basal insulin therapy, and had suboptimal glycaemic control (HbA1c >7.5%; 58.5 mmol/mol). Block randomisation with 1:1 allocation was performed centrally. Participants in the intervention group titrated their basal insulin dose using a smartphone application (My Dose Coach) for 12 weeks. Control group participants titrated their basal insulin dose according to a written titration chart. The primary outcome was the baseline-adjusted change in HbA1c at 12 weeks. The intention-to-treat analysis included all randomised participants. Results Between 13 July 2021 and 21 March 2022, 251 study participants were randomly assigned (control group: n = 123; intervention group: n = 128), and 236 completed the follow-up phase (control group: n = 119; intervention group: n = 117). Regarding the HbA1c a model-based adjusted between-group difference of -0.31% (95% CI: 0.01%-0.69%; p = 0.0388) in favour of the intervention group was observed. There were 30 adverse events reported: 16 in the control group, 14 in the intervention group. Of these, 15 adverse events were serious. No event was considered to be related to the investigational device. Interpretation Study results suggest that utilizing this digital health smartphone application for basal insulin titration may have resulted in a comparatively greater reduction in HbA1c levels among individuals with type 2 diabetes, as compared to basal insulin titration guided by a written titration schedule. No negative effect on safety outcomes was observed. Funding Sanofi-Aventis Deutschland GmbH.
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Affiliation(s)
- Norbert Hermanns
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, Bad Mergentheim 97980, Germany
- Diabetes Centre Bad Mergentheim, Theodor-Klotzbuecher-Str. 12, Bad Mergentheim 97980, Germany
- Department of Clinical Psychology and Psychotherapy, University of Bamberg, Markusplatz 3, Bamberg 96047, Germany
| | - Dominic Ehrmann
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, Bad Mergentheim 97980, Germany
- Department of Clinical Psychology and Psychotherapy, University of Bamberg, Markusplatz 3, Bamberg 96047, Germany
| | - Katharina Finke-Groene
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, Bad Mergentheim 97980, Germany
| | - Michael Krichbaum
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, Bad Mergentheim 97980, Germany
| | - Timm Roos
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, Bad Mergentheim 97980, Germany
| | - Thomas Haak
- Diabetes Centre Bad Mergentheim, Theodor-Klotzbuecher-Str. 12, Bad Mergentheim 97980, Germany
| | - Guido Freckmann
- IfDT - Institut für Diabetes-Technologie Forschungs- und Entwicklungsgesellschaft mbH, Helmholtzstr. 20, Ulm 89081, Germany
| | - Bernhard Kulzer
- Research Institute of the Diabetes Academy Mergentheim (FIDAM), Johann-Hammer-Str. 24, Bad Mergentheim 97980, Germany
- Diabetes Centre Bad Mergentheim, Theodor-Klotzbuecher-Str. 12, Bad Mergentheim 97980, Germany
- Department of Clinical Psychology and Psychotherapy, University of Bamberg, Markusplatz 3, Bamberg 96047, Germany
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Park S, Kum HC, Zheng Q, Lawley MA. Real-World Adherence and Effectiveness of Remote Patient Monitoring Among Medicaid Patients With Diabetes: Retrospective Cohort Study. J Med Internet Res 2023; 25:e45033. [PMID: 37606977 PMCID: PMC10481216 DOI: 10.2196/45033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 06/28/2023] [Accepted: 07/20/2023] [Indexed: 08/23/2023] Open
Abstract
BACKGROUND The prevalence of diabetes in the United States is high and increasing, and it is also the most expensive chronic condition in the United States. Self-monitoring of blood glucose or continuous glucose monitoring are potential solutions, but there are barriers to their use. Remote patient monitoring (RPM) with appropriate support has the potential to provide solutions. OBJECTIVE We aim to investigate the adherence of Medicaid patients with diabetes to daily RPM protocols, the relationship between adherence and changes in blood glucose levels, and the impact of daily testing time on blood glucose changes. METHODS This retrospective cohort study analyzed real-world data from an RPM company that provides services to Texas Medicaid patients with diabetes. Overall, 180 days of blood glucose data from an RPM company were collected to assess transmission rates and blood glucose changes, after the first 30 days of data were excluded due to startup effects. Patients were separated into adherent and nonadherent cohorts, where adherent patients transmitted data on at least 120 of the 150 days. z tests and t tests were performed to compare transmission rates and blood glucose changes between 2 cohorts. In addition, we analyzed blood glucose changes based on their testing time-between 1 AM and 10 AM, 10 AM and 6 PM, and 6 PM and 1 AM. RESULTS Mean patient age was 70.5 (SD 11.8) years, with 66.8% (n=255) of them being female, 91.9% (n=351) urban, and 89% (n=340) from south Texas (n=382). The adherent cohort (n=186, 48.7%) had a mean transmission rate of 82.8% before the adherence call and 91.1% after. The nonadherent cohort (n=196, 51.3%) had a mean transmission rate of 45.9% before and 60.2% after. The mean blood glucose levels of the adherent cohort decreased by an average of 9 mg/dL (P=.002) over 5 months. We also found that variability of blood glucose level of the adherent cohort improved 3 mg/dL (P=.03) over the 5-month period. Both cohorts had the majority of their transmissions between 1 AM and 10 AM, with 70.5% and 53.2% for the adherent and nonadherent cohorts, respectively. The adherent cohort had decreasing mean blood glucose levels over 5 months, with the largest decrease during the 6 PM to 1 AM time period (30.9 mg/dL). Variability of blood glucose improved only for those tested from 10 AM to 6 PM, with improvements of 6.9 mg/dL (P=.02). Those in the nonadherent cohort did not report significant changes. CONCLUSIONS RPM can help manage diabetes in Medicaid clients by improving adherence rates and glycemic control. Adherence calls helped improve adherence rates, but some patients still faced challenges in transmitting blood glucose levels. Nonetheless, RPM has the potential to reduce the risk of adverse outcomes associated with diabetes.
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Affiliation(s)
- Sulki Park
- Population Informatics Lab, Texas A&M University, College Station, TX, United States
- Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States
| | - Hye-Chung Kum
- Population Informatics Lab, Texas A&M University, College Station, TX, United States
- Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States
- Department of Health Policy and Management, Texas A&M University, College Station, TX, United States
| | - Qi Zheng
- Department of Epidemiology and Biostatistics, Texas A&M University, College Station, TX, United States
| | - Mark A Lawley
- Population Informatics Lab, Texas A&M University, College Station, TX, United States
- Department of Industrial and Systems Engineering, Texas A&M University, College Station, TX, United States
- Department of Epidemiology and Biostatistics, Texas A&M University, College Station, TX, United States
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Takeishi S, Inoue T. Ideal automation for insulin management - with interpretation of risk ratio. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 35:100761. [PMID: 37424681 PMCID: PMC10326712 DOI: 10.1016/j.lanwpc.2023.100761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 03/23/2023] [Indexed: 07/11/2023]
Affiliation(s)
- Soichi Takeishi
- Department of Diabetes, Inuyama Chuo General Hospital, Japan
| | - Tatsuo Inoue
- Department of Diabetes, Inuyama Chuo General Hospital, Japan
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Luo Y, Chang Y, Zhao Z, Xia J, Xu C, Bee YM, Li X, Sheu WHH, McGill M, Chan SP, Deodat M, Suastika K, Thy KN, Chen L, Shan Kong AP, Chen W, Deerochanawong C, Yabe D, Zhao W, Lim S, Yao X, Ji L. Device-supported automated basal insulin titration in adults with type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 35:100746. [PMID: 37424694 PMCID: PMC10326709 DOI: 10.1016/j.lanwpc.2023.100746] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 02/14/2023] [Accepted: 03/07/2023] [Indexed: 07/11/2023]
Abstract
Background Technological advances make it possible to use device-supported, automated algorithms to aid basal insulin (BI) dosing titration in patients with type 2 diabetes. Methods A systematic review and meta-analysis of randomized controlled trials were performed to evaluate the efficacy, safety, and quality of life of automated BI titration versus conventional care. The literature in Medline, Embase, Web of Science, and the Cochrane databases from January 2000 to February 2022 were searched to identify relevant studies. Risk ratios (RRs), mean differences (MDs), and their 95% confidence intervals (CIs) were calculated using random-effect meta-analyses. Certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach. Findings Six of the 7 eligible studies (889 patients) were included in meta-analyses. Low- to moderate-quality evidence suggests that patients who use automated BI titration versus conventional care may have a higher probability of reaching a target of HbA1c <7.0% (RR, 1.82 [95% CI, 1.16-2.86]); and a lower level of HbA1c (MD, -0.25% [95% CI, -0.43 to -0.06%]). No statistically significant differences were detected between the two groups in fasting glucose results, incidences of hypoglycemia, severe or nocturnal hypoglycemia, and quality of life, with low to very low certainty for all the evidence. Interpretation Automated BI titration is associated with small benefits in reducing HbA1c without increasing the risk of hypoglycemia. Future studies should explore patient attitudes and the cost-effectiveness of this approach. Funding Sponsored by the Chinese Geriatric Endocrine Society.
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Affiliation(s)
- Yingying Luo
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Beijing 100044, China
| | - Yaping Chang
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario L8S 4L8, Canada
| | - Zhan Zhao
- Tianjin Tiantian Biotechnology Co., Ltd., Tianjin 300000, China
| | - Jun Xia
- Nottingham Ningbo GRADE Centre, University of Nottingham Ningbo China, Ningbo, Zhejiang 315100, China
- Academic Unit of Lifespan and Population Health, School of Medicine, The University of Nottingham, Nottingham NG7 2UH, UK
| | - Chenchen Xu
- Tianjin Tiantian Biotechnology Co., Ltd., Tianjin 300000, China
| | - Yong Mong Bee
- Department of Endocrinology, Singapore General Hospital, Singapore 169608, Singapore
| | - Xiaoying Li
- Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Wayne H.-H. Sheu
- Division of Endocrinology and Metabolism, Taipei Veterans General Hospital, Taipei 222, Taiwan
| | - Margaret McGill
- Diabetes Centre, Royal Prince Alfred Hospital, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales 2050, Australia
| | - Siew Pheng Chan
- Department of Medicine, Faculty of Medicine, University of Malaya, Lembah Pantai, Kuala Lumpur 59100, Malaysia
| | - Marisa Deodat
- Michael G. DeGroote Cochrane Canada and McMaster GRADE Centres, McMaster University, Hamilton, Ontario L8V 5C2, Canada
- Department of Oncology, McMaster University, Hamilton, Ontario L8V 5C2, Canada
| | - Ketut Suastika
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Faculty of Medicine, Prof. IGNG Ngoerah Hospital, Udayana University, Denpasar, Bali 80114, Indonesia
| | - Khue Nguyen Thy
- Ho Chi Minh University of Medicine and Pharmacy Medic Medical Center, Ho Chi Minh City 700000, Vietnam
| | - Liming Chen
- Chu Hsien-I Memorial (Metabolic Diseases) Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin 300134, China
| | - Alice Pik Shan Kong
- Division of Endocrinology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region 999077, China
| | - Wei Chen
- Department of Clinical Nutrition, Department of Health Medicine, Chinese Academy of Medical Sciences-Peking Union Medical College, Peking Union Medical College Hospital, Beijing 100730, China
| | | | - Daisuke Yabe
- Departments of Diabetes, Endocrinology and Metabolism/Rheumatology and Clinical Immunology, Gifu University Graduate School of Medicine, Gifu 501-1194, Japan
- Center for One Medicine Innovative Translational Research, Gifu University Institute for Advanced Study, Gifu 501-1194, Japan
| | - Weigang Zhao
- Department of Endocrinology, Peking Union Medical College Hospital, Beijing 100730, China
| | - Soo Lim
- Department of Internal Medicine, Seoul National University College of Medicine and Seoul National University Bundang Hospital, Seongnam 13620, South Korea
| | - Xiaomei Yao
- Center for Clinical Practice Guideline Conduction and Evaluation, Children's Hospital of Fudan University, Shanghai 201100, China
- Department of Oncology, McMaster University, Hamilton, Ontario L8V 5C2, Canada
| | - Linong Ji
- Department of Endocrinology and Metabolism, Peking University People's Hospital, Beijing 100044, China
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Konnyu KJ, Yogasingam S, Lépine J, Sullivan K, Alabousi M, Edwards A, Hillmer M, Karunananthan S, Lavis JN, Linklater S, Manns BJ, Moher D, Mortazhejri S, Nazarali S, Paprica PA, Ramsay T, Ryan PM, Sargious P, Shojania KG, Straus SE, Tonelli M, Tricco A, Vachon B, Yu CH, Zahradnik M, Trikalinos TA, Grimshaw JM, Ivers N. Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes. Cochrane Database Syst Rev 2023; 5:CD014513. [PMID: 37254718 PMCID: PMC10233616 DOI: 10.1002/14651858.cd014513] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
BACKGROUND There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision-makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations. OBJECTIVES To update existing systematic reviews of diabetes QI programmes and apply novel meta-analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care. SEARCH METHODS We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top-up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section. SELECTION CRITERIA We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system- or provider-targeted QI strategy alone or in combination with a patient-targeted strategy. - System-targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). - Provider-targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). - Patient-targeted: patient education (PE); promotion of self-management (PSM); patient reminders (PR). Patient-targeted QI strategies needed to occur with a minimum of one provider or system-targeted strategy. DATA COLLECTION AND ANALYSIS We dual-screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta-regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outcomes. To explore this further, we extended the main additive model for continuous outcomes (HbA1c, SBP and LDL-C) to include an interaction term between each strategy and average baseline risk for each study (baseline thresholds were based on a data-driven approach; we used the median of all baseline values reported in the trials). Based on model diagnostics, the baseline interaction models for HbA1c, SBP and LDL-C performed better than the main model and are therefore presented as the primary analyses for these outcomes. Based on the model results, we qualitatively ordered each QI strategy within three tiers (Top, Middle, Bottom) based on its magnitude of effect relative to the other QI strategies, where 'Top' indicates that the QI strategy was likely one of the most effective strategies for that specific outcome. Secondary analyses explored the sensitivity of results to choices in model specification and priors. Additional information about the methods and results of the review are available as Appendices in an online repository. This review will be maintained as a living systematic review; we will update our syntheses as more data become available. MAIN RESULTS We identified 553 trials (428 patient-randomised and 125 cluster-randomised trials), including a total of 412,161 participants. Of the included studies, 66% involved people living with type 2 diabetes only. Participants were 50% female and the median age of participants was 58.4 years. The mean duration of follow-up was 12.5 months. HbA1c was the commonest reported outcome; screening outcomes and outcomes related to cardiovascular medications, smoking and harms were reported infrequently. The most frequently evaluated QI strategies across all study arms were PE, PSM and CM, while the least frequently evaluated QI strategies included AF, FI and CQI. Our confidence in the evidence is limited due to a lack of information on how studies were conducted. Four QI strategies (CM, TC, PE, PSM) were consistently identified as 'Top' across the majority of outcomes. All QI strategies were ranked as 'Top' for at least one key outcome. The majority of effects of individual QI strategies were modest, but when used in combination could result in meaningful population-level improvements across the majority of outcomes. The median number of QI strategies in multicomponent QI programmes was three. Combinations of the three most effective QI strategies were estimated to lead to the below effects: - PR + PSM + CE: decrease in HbA1c by 0.41% (credibility interval (CrI) -0.61 to -0.22) when baseline HbA1c < 8.3%; - CM + PE + EPR: decrease in HbA1c by 0.62% (CrI -0.84 to -0.39) when baseline HbA1c > 8.3%; - PE + TC + PSM: reduction in SBP by 2.14 mmHg (CrI -3.80 to -0.52) when baseline SBP < 136 mmHg; - CM + TC + PSM: reduction in SBP by 4.39 mmHg (CrI -6.20 to -2.56) when baseline SBP > 136 mmHg; - TC + PE + CM: LDL-C lowering of 5.73 mg/dL (CrI -7.93 to -3.61) when baseline LDL < 107 mg/dL; - TC + CM + CR: LDL-C lowering by 5.52 mg/dL (CrI -9.24 to -1.89) when baseline LDL > 107 mg/dL. Assuming a baseline screening rate of 50%, the three most effective QI strategies were estimated to lead to an absolute improvement of 33% in retinopathy screening (PE + PR + TC) and 38% absolute increase in foot screening (PE + TC + Other). AUTHORS' CONCLUSIONS There is a significant body of evidence about QI programmes to improve the management of diabetes. Multicomponent QI programmes for diabetes care (comprised of effective QI strategies) may achieve meaningful population-level improvements across the majority of outcomes. For health system decision-makers, the evidence summarised in this review can be used to identify strategies to include in QI programmes. For researchers, this synthesis identifies higher-priority QI strategies to examine in further research regarding how to optimise their evaluation and effects. We will maintain this as a living systematic review.
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Affiliation(s)
- Kristin J Konnyu
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Sharlini Yogasingam
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Johanie Lépine
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Katrina Sullivan
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | - Alun Edwards
- Department of Medicine, University of Calgary, Calgary, Canada
| | - Michael Hillmer
- Institute for Health Policy, Management, and Evaluation, University of Toronto, Toronto, Canada
| | - Sathya Karunananthan
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Interdisciplinary School of Health Sciences, University of Ottawa, Ottawa, Canada
| | - John N Lavis
- McMaster Health Forum, Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
| | - Stefanie Linklater
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Braden J Manns
- Department of Medicine and Community Health Sciences, University of Calgary, Calgary, Canada
| | - David Moher
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Sameh Mortazhejri
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - Samir Nazarali
- Department of Ophthalmology and Visual Sciences, University of Alberta, Edmonton, Canada
| | - P Alison Paprica
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
| | - Timothy Ramsay
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | - Peter Sargious
- Department of Medicine, University of Calgary, Calgary, Canada
| | - Kaveh G Shojania
- University of Toronto Centre for Patient Safety, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Sharon E Straus
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital and University of Toronto, Toronto, Canada
| | - Marcello Tonelli
- Department of Medicine and Community Health Sciences, University of Calgary, Calgary, Canada
| | - Andrea Tricco
- Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital and University of Toronto, Toronto, Canada
- Epidemiology Division and Institute of Health Policy, Management, and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
- Queen's Collaboration for Health Care Quality: A JBI Centre of Excellence, Queen's University, Kingston, Canada
| | - Brigitte Vachon
- School of Rehabilitation, Occupational Therapy Program, University of Montreal, Montreal, Canada
| | - Catherine Hy Yu
- Department of Medicine, St. Michael's Hospital, Toronto, Canada
| | - Michael Zahradnik
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Thomas A Trikalinos
- Departments of Health Services, Policy, and Practice and Biostatistics, Center for Evidence Synthesis in Health, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Jeremy M Grimshaw
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
- Department of Medicine, University of Ottawa, Ottawa, Canada
| | - Noah Ivers
- Department of Family and Community Medicine, Women's College Hospital, Toronto, Canada
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7
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Cai J, Xu H, Jiang S, Sung J, Sawhney R, Broadley S, Sun J. Effectiveness of telemonitoring intervention on glycaemic control in patients with type 2 diabetes mellitus: A systematic review and meta-analysis. Diabetes Res Clin Pract 2023; 201:110727. [PMID: 37217016 DOI: 10.1016/j.diabres.2023.110727] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 02/18/2023] [Accepted: 05/18/2023] [Indexed: 05/24/2023]
Abstract
BACKGROUND Type 2 diabetes mellitus (T2DM) is a rising global health concern that requires long-term treatment and close monitoring. Telemonitoring has been shown to be a promising tool to facilitate patient-physician interaction and improve glycaemic control. METHOD Randomised controlled trials (RCT) of telemonitoring in T2DM published between 1990 and 2021 were searched through multiple electronic databases. The primary outcome variables included HbA1c and fasting blood glucose (FBG), and BMI was a secondary outcome variable. RESULTS Thirty RCT with a total of 4,678 participants were included in this study. Twenty-six studies reported on HbA1c, which was shown to be significantly lower in participants on telemonitoring when compared to conventional care. Ten studies investigated FBG which collectively showed no statistically significant difference. Subgroup analysis demonstrated the effect of telemonitoring on glycaemic control is influenced by a range of factors concerning system practicality, user engagement, patient characteristics and disease education. CONCLUSION Telemonitoring exhibited a great potential to improve T2DM management. Several technical features and patient factors may influence the effectiveness of telemonitoring. Further studies are needed to verify the findings and address limitations before its implementation into routine practice.
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Affiliation(s)
- Jinxuan Cai
- School of Medicine and Dentistry Griffith University, Q4215, Australia.
| | - Huaying Xu
- School of Medicine and Dentistry Griffith University, Q4215, Australia.
| | - Stephen Jiang
- School of Medicine and Dentistry Griffith University, Q4215, Australia.
| | - Jerry Sung
- School of Medicine and Dentistry Griffith University, Q4215, Australia.
| | - Rakshat Sawhney
- School of Medicine and Dentistry Griffith University, Q4215, Australia.
| | - Simon Broadley
- School of Medicine and Dentistry Griffith University, Q4215, Australia; Menzies Health Institute Queensland, Griffith University, Q4215, Australia; Department of Neurology, Gold Coast University Hospital, Q4222, Australia.
| | - Jing Sun
- School of Medicine and Dentistry Griffith University, Q4215, Australia; Menzies Health Institute Queensland, Griffith University, Q4215, Australia; Institute for Integrated and Intelligent System, Griffith University, Q4222, Australia.
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8
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Nevoret C, Gervaise N, Delemer B, Bekka S, Detournay B, Benkhelil A, Bahloul A, d'Orsay G, Penfornis A. The Effectiveness of an App (Insulia) in Recommending Basal Insulin Doses for French Patients With Type 2 Diabetes Mellitus: Longitudinal Observational Study. JMIR Diabetes 2023; 8:e44277. [PMID: 36749650 PMCID: PMC10018375 DOI: 10.2196/44277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/26/2023] [Accepted: 02/03/2023] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND For patients with type 2 diabetes (T2D), calculating the daily dose of basal insulin may be challenging. Insulia is a digital remote monitoring solution that uses clinical algorithms to recommend basal insulin doses. A predecessor device was evaluated in the TeleDiab-2 randomized controlled trial, showing that a higher percentage of patients using the app achieved their target fasting blood glucose (FBG) level compared to the control group, and insulin doses were adjusted to higher levels without hypoglycemia. OBJECTIVE This study aims to analyze how the glycemic control of Insulia users has evolved when using the app in a real-life setting in France. METHODS A retrospective observational analysis of data collected through the device in adult French patients with T2D treated with basal insulin and oral antihyperglycemic agents using the system for ≥6 months was conducted. Analyses were descriptive and distinguished the results in a subpopulation of regular and compliant users of the app. Glycemic outcomes were estimated considering the percentage of patients who achieved their individualized FBG target between 5.5 and 6 months following the initiation of device use, the frequency of hypoglycemia resulting in a treatment change over the 6-month period of exposure, and the evolution of the average hemoglobin A1c (HbA1c) level over the same period. RESULTS Of the 484 users, 373 (77.1%) performed at least one dose calculation. A total of 221 (59.2%) users were men. When app use started, the mean age, BMI, HbA1c, and basal insulin dose were 55.8 (SD 11.9) years, 30.6 (SD 5.9) kg/m2, 10.1% (SD 2.0%), and 25.5 (SD 15.8) IU/day, respectively. Over a median use duration of 5.0 (95% CI 3.8-5.7) months, patients used the system 5.8 (SD 1.6) times per week on average, and 73.4% of their injected doses were consistent with the app's suggested doses. Among regular and compliant user patients (n=91, ≥5 measurements/week and ≥80% adherence to calculated doses), 60% (55/91) achieved the FBG target (±5%) at 6 months (5.5-6 months) versus 51.5% (145/282) of the other patients (P=.15). There was an increase in the proportion of patients achieving their target FBG for regular and compliant users (+1.86% every 2 weeks) without clear improvement in other patients. A logistic model did not identify the variables that were significantly associated with this outcome among regular and compliant users. In the overall population, the incidence of reported hypoglycemia decreased simultaneously (-0.16%/month). Among 82 patients, the mean HbA1c decreased from 9.9% to 7.2% at 6 months. CONCLUSIONS An improvement in glycemic control as measured by the percentage of patients reaching their FBG individualized target range without increasing hypoglycemic risk was observed in patients using the Insulia app, especially among regular users following the dose recommendations of the algorithm.
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Affiliation(s)
| | | | - Brigitte Delemer
- Endocrinology, Diabetology and Nutrition Department, Robert Debre University Hospital, Reims, France
| | - Said Bekka
- Institut de Diabétologie et Nutrition du Centre, Mainvilliers, France
| | | | | | - Amar Bahloul
- Diabetes Department, Sanofi France, Gentilly, France
| | | | - Alfred Penfornis
- Endocrinology, Diabetology and Metabolic Diseases Department, Sud-Francilien Hospital, Université Paris-Saclay, Corbeil-Essonnes, France
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Joshi SR, Singh G, Marwah A, Mittra S, Suvarna VR, Athalye SN. Comparative clinical efficacy and safety of insulin glargine 300 U/ml (Toujeo) versus insulin glargine 100 U/ml in type 2 diabetes and type 1 diabetes: A systematic literature review and meta-analysis. Diabetes Obes Metab 2023; 25:1589-1606. [PMID: 36748186 DOI: 10.1111/dom.15007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 01/31/2023] [Accepted: 02/02/2023] [Indexed: 02/08/2023]
Abstract
AIM To compare the clinical efficacy and safety of glargine-U100 (Lantus/Gla-100) with glargine-U300 (Toujeo/Gla-300) in adult patients with type 2 diabetes (T2D) and type 1 diabetes (T1D). MATERIALS AND METHODS A literature search on Gla-300/Gla-100 in diabetes management was conducted using the MEDLINE/Embase/Cochrane databases from inception to 10 January 2021. Eligible studies considered for inclusion were parallel-design, randomized controlled trials (RCTs). The Cochrane risk-of-bias tool was used to evaluate the quality of the included studies. The random-effects model was applied for interpretation of the results. RESULTS Of 5348 records screened, 592 were assessed for eligibility and 15 RCTs were considered for data extraction and meta-analysis (T2D [N = 10; n = 7082]; T1D [N = 5; n = 2222]). In patients with T1D, all safety parameters were comparable between Gla-100 and Gla-300. In T2D, statistically significant differences were observed in favour of Gla-300 over Gla-100 for nocturnal and total hypoglycaemia. For efficacy parameters, a statistically and clinically significant difference favouring Gla-100 in basal insulin dose requirement was observed for both T2D and T1D. Change in HbA1c showed a statistically but not clinically significant reduction with Gla-100 compared with Gla-300 in T1D. Statistically significant but clinically less relevant differences favoured Gla-300 for control of body weight in T1D and T2D and Gla-100 for fasting blood glucose in T2D. CONCLUSIONS Gla-100 and Gla-300 had comparable efficacy and safety profiles in both T1D and T2D populations. Gla-300 showed a lower risk of nocturnal and total hypoglycaemia, significant in insulin-experienced/exposed patients with T2D. Patients on Gla-300 required significantly more units of insulin daily than the Gla-100 group to achieve equivalent efficacy.
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Affiliation(s)
- Shashank R Joshi
- Department of Diabetology and Endocrinology, Lilavati Hospital and Research Center, Mumbai, India
| | - Gursharan Singh
- Clinical Development and Medical Affairs, Biocon Biologics India Ltd., Bengaluru, India
| | - Ashwani Marwah
- Clinical Development and Medical Affairs, Biocon Biologics India Ltd., Bengaluru, India
| | - Shivani Mittra
- Clinical Development and Medical Affairs, Biocon Biologics India Ltd., Bengaluru, India
| | - Viraj R Suvarna
- Clinical Development and Medical Affairs, Biocon Biologics India Ltd., Bengaluru, India
| | - Sandeep N Athalye
- Clinical Development and Medical Affairs, Biocon Biologics India Ltd., Bengaluru, India
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10
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Unnikrishnan AG, Viswanathan V, Zhou FL, Hao L, Kamath P, Bertolini M, Botero JF, Mancillas-Adame L. Impact of My Dose Coach App Frequency of Use on Clinical Outcomes in Type 2 Diabetes. Diabetes Ther 2022; 13:983-993. [PMID: 35316509 PMCID: PMC8938735 DOI: 10.1007/s13300-022-01245-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 02/28/2022] [Indexed: 11/21/2022] Open
Abstract
INTRODUCTION My Dose Coach (MDC) is a US Food and Drug Administration-approved digital smartphone application designed to help users with type 2 diabetes (T2D) titrate their basal insulin (BI) according to a clinician-prescribed individualized titration plan. The aim of this analysis was to assess the impact of the frequency of MDC use on clinical outcomes. METHODS This retrospective observational analysis included people with T2D who were registered for MDC (August 1st, 2018-April 30th, 2020) and received BI. Users with an activated care plan and ≥2 fasting blood glucose (FBG) observations spanning ≥2 weeks were defined as active. Outcomes included percentage achieving their individual FBG target, time to FBG target, change in FBG, change in insulin dose and hypoglycemia. Users were stratified into high (>3 days per week), moderate (>1- ≤3 days per week), and low (≤1 day per week) MDC usage groups. RESULTS The analysis included 2517 active MDC users. Approximately 49% of users had high MDC usage. Overall, 44% of users across all usage frequencies achieved their individual FBG target. High MDC use was associated with significantly better FBG target achievement and less time to FBG target versus moderate- and low-usage groups (p≤0.01 for all). Insulin dose change was significantly greater in the high- versus moderate-usage group (p=0.01). There was no significant difference in hypoglycemia incidence among MDC usage groups (12%-16% of users in any usage group). CONCLUSIONS More frequent MDC usage was associated with better FBG outcomes without increased hypoglycemia risk.
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Affiliation(s)
| | | | | | | | | | | | | | - Leonardo Mancillas-Adame
- Endocrinology Division, Medical School and University Hospital, Universidad Autonoma de Nuevo Leon, Nuevo Leon, Mexico
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Tews D, Gouveri E, Simon J, Marck C. A Smartphone-Based Application to Assist Insulin Titration in Patients Undergoing Basal Insulin-Supported Oral Antidiabetic Treatment. J Diabetes Sci Technol 2022:19322968221090521. [PMID: 35491554 DOI: 10.1177/19322968221090521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
INTRODUCTION INSULIA is an insulin-titration app developed for patients with type 2 diabetes treated with basal insulin as part of a basal insulin-supported oral therapy (BOT). The app uses patient-logged fasting blood glucose (FBG) values and a titration plan defined by the treating physician to provide basal insulin dosing recommendations. Physicians use the web portal to monitor their patients' therapy progress and, if necessary, adjust therapy. The aim of this study was to assess the app, specifically its features, handling and impact on diabetes treatment and self-management in Germany. METHODS This German retrospective pilot study included physicians (diabetologists, general practitioners, and internists) and patients with type 2 diabetes who either receive or start BOT using the app. Both groups completed group-specific questionnaires between December 2018 and June 2019. RESULTS Overall, 10 physicians and 34 patients with type 2 diabetes completed their respective questionnaires. Physicians perceived their app-using patients to be more involved and more confident in managing their insulin therapy than patients not using the app. The majority of patients considered the app as a tool that assists with safer insulin treatment. The physicians perceived that due to the app use, FBG and HbA1c target values were achieved more often than patients not using the app and the number and severity of hypoglycemic episodes was reduced. CONCLUSION The titration app seems to have a positive impact on BOT patients' FBG and HbA1c target achievement and was highly appreciated by both physicians and patients alike.
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Affiliation(s)
| | | | - Jörg Simon
- MVZ im Altstadt-Carree Fulda GmbH, Fulda, Germany
| | - Cornelia Marck
- Centrum für Diabetologie und Allgemeinmedizin, Pohlheim, Germany
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12
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Kerr D, Edelman S, Vespasiani G, Khunti K. New digital health technologies for insulin initiation and optimization for people with type 2 diabetes. Endocr Pract 2022; 28:811-821. [PMID: 35452813 DOI: 10.1016/j.eprac.2022.04.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 03/31/2022] [Accepted: 04/11/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE The health and economic burden of type 2 diabetes (T2D) is of global significance. Many people with T2D eventually need insulin to help reduce their risk of serious associated complications. However, barriers in initiating and/or optimizing insulin expose people with diabetes to sustained hyperglycemia. In this review, we investigate how new and future technologies may provide opportunities to help overcome barriers to insulin initiation and/or optimization. METHODS A focused literature search of PubMed and key scientific congresses was conducted. Software tools and devices developed to support insulin initiation and/or optimization were identified by manually filtering over 300 publications and conference abstracts. RESULTS Most software tools have been developed for a smartphone platform. At present, published data suggest that use of these technologies is associated with equivalent or improved glycemic outcomes compared with standard care with additional benefits such as reduced healthcare provider (HCP) time burden and improved diabetes knowledge. However, there remains a paucity of good quality evidence. Most new devices to support insulin therapy help track the dose and timing of insulin use. CONCLUSIONS New digital health tools may help to reduce barriers to optimal insulin therapy. An integrated solution that connects glucose monitoring, dose recording, titration advice, and records comorbidities and lifestyle factors has the potential to reduce the complexity and burden of treatment and may improve titration and treatment adherence, resulting in better outcomes for people with diabetes.
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Affiliation(s)
- David Kerr
- Sansum Diabetes Research Institute, Santa Barbara, California.
| | - Steven Edelman
- University of California San Diego Veterans Affairs Medical Center, San Diego, California
| | | | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester General Hospital, Leicester, United Kingdom
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Fung BM, Perumpail M, Patel YA, Tabibian JH. Telemedicine in Hepatology: Current Applications and Future Directions. Liver Transpl 2022; 28:294-303. [PMID: 34506686 DOI: 10.1002/lt.26293] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 09/02/2021] [Accepted: 09/06/2021] [Indexed: 12/13/2022]
Abstract
Telemedicine refers to the use of information and communication technologies for providing health care at a distance. Through the use of telecommunication technologies such as cell phones, computers, and other electronic devices, health care providers are able to conduct patient visits, mentor/train other providers, and monitor patients' chronic diseases remotely, potentially hundreds or thousands of miles away. Over the past 2 decades, the use of telemedicine has grown in the field of hepatology. In this review, we provide a focused primer on telemedicine and its current applications in hepatology. In particular, we discuss the use of telemedicine in the management of chronic hepatitis C, the complications of liver disease, as well as preliver transplantation evaluation and posttransplantation care. In addition, we provide a synopsis of the effect of the coronavirus disease 2019 (COVID-19) pandemic on the use of telemedicine in hepatology.
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Affiliation(s)
- Brian M Fung
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, University of Arizona College of Medicine - Phoenix, Phoenix, AZ.,Banner - University Medical Center Phoenix, Phoenix, AZ
| | | | - Yuval A Patel
- Division of Gastroenterology, Department of Medicine, Duke University, Durham, NC
| | - James H Tabibian
- Division of Gastroenterology, Department of Medicine, Olive View - UCLA Medical Center, Sylmar, CA.,David Geffen School of Medicine at UCLA, Los Angeles, CA
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Development features and study characteristics of mobile health apps in the management of chronic conditions: a systematic review of randomised trials. NPJ Digit Med 2021; 4:144. [PMID: 34611287 PMCID: PMC8492762 DOI: 10.1038/s41746-021-00517-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 09/13/2021] [Indexed: 11/21/2022] Open
Abstract
COVID-19 pandemic challenges have accelerated the reliance on digital health fuelling the expanded incorporation of mobile apps into healthcare services, particularly for the management of long-term conditions such as chronic diseases (CDs). However, the impact of health apps on outcomes for CD remains unclear, potentially owing to both the poor adoption of formal development standards in the design process and the methodological quality of studies. A systematic search of randomised trials was performed on Medline, ScienceDirect, the Cochrane Library and Scopus to provide a comprehensive outlook and review the impact of health apps on CD. We identified 69 studies on diabetes (n = 29), cardiovascular diseases (n = 13), chronic respiratory diseases (n = 13), cancer (n = 10) or their combinations (n = 4). The apps rarely adopted developmental factors in the design stage, with only around one-third of studies reporting user or healthcare professional engagement. Apps differed significantly in content, with a median of eight behaviour change techniques adopted, most frequently pertaining to the ‘Feedback and monitoring’ (91%) and ‘Shaping knowledge’ (72%) categories. As for the study methodologies, all studies adopted a traditional randomised control trial (RCT) design, with relatively short follow-ups and limited sample sizes. Findings were not significant for the majority of studies across all CD, with most RCTs revealing a high risk of bias. To support the adoption of apps for CD management, this review reinforces the need for more robust development and appropriate study characteristics to sustain evidence generation and elucidate whether study results reflect the true benefits of apps or a biased estimate due to unsuitable designs.
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Oikonomidi T, Ravaud P, Cosson E, Montori V, Tran VT. Evaluation of Patient Willingness to Adopt Remote Digital Monitoring for Diabetes Management. JAMA Netw Open 2021; 4:e2033115. [PMID: 33439263 PMCID: PMC7807289 DOI: 10.1001/jamanetworkopen.2020.33115] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Accepted: 11/18/2020] [Indexed: 01/21/2023] Open
Abstract
Importance Patients will decide whether to adopt remote digital monitoring (RDM) for diabetes by weighing its health benefits against the inconvenience it may cause. Objective To identify the minimum effectiveness patients report they require to adopt 36 different RDM scenarios. Design, Setting, and Participants This survey study was conducted among adults with type 1 or type 2 diabetes living in 30 countries from February to July 2019. Exposures Survey participants assessed 3 randomly selected scenarios from a total of 36. Scenarios described different combinations of digital monitoring tools (glucose, physical activity, food monitoring), duration and feedback loops (feedback in consultation vs real-time telefeedback by a health care professional or by artificial intelligence), and data handling modalities (by a public vs private company), reflecting different degrees of RDM intrusiveness in patients' personal lives. Main Outcomes and Measures Participants assessed the minimum effectiveness for 2 diabetes-related outcomes (reducing hypoglycemic episodes and preventing ophthalmologic complications) for which they would adopt each RDM (from much less effective to much more effective than their current monitoring). Results Of 1577 individuals who consented to participate, 1010 (64%; 572 [57%] women, median [interquartile range] age, 51 [37-63] years, 524 [52%] with type 1 diabetes) assessed at least 1 vignette. Overall, 2860 vignette assessments were collected. In 1025 vignette assessments (36%), participants would adopt RDM only if it was much more effective at reducing hypoglycemic episodes compared with their current monitoring; in 1835 assessments (65%), participants would adopt RDM if was just as or somewhat more effective. The main factors associated with required effectiveness were food monitoring (β = 0.32; SE, 0.12; P = .009), real-time telefeedback by a health care professional (β = 0.49; SE, 0.15; P = .001), and perceived intrusiveness (β = 0.36; SE, 0.06; P < .001). Minimum required effectiveness varied among participants; 34 of 36 RDM scenarios (94%) were simultaneously required to be just as or less effective by at least 25% of participants and much more effective by at least 25% of participants. Results were similar for participant assessments of scenarios regarding the prevention of ophthalmologic complications. Conclusions and Relevance The findings of this study suggest that patients require greater health benefits to adopt more intrusive RDM modalities, food monitoring, and real-time feedback by a health care professional. Patient monitoring devices should be designed to be minimally intrusive. The variability in patients' requirements points to a need for shared decision-making.
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Affiliation(s)
- Theodora Oikonomidi
- Université de Paris, Centre of Research in Epidemiology and Statistics, French National Institute of Health and Medical Research, National Institute for Agricultural Research, Paris, France
- Clinical Epidemiology Unit, Hôtel-Dieu Hospital, Assistance Publique–Hôpitaux de Paris, Paris, France
| | - Philippe Ravaud
- Université de Paris, Centre of Research in Epidemiology and Statistics, French National Institute of Health and Medical Research, National Institute for Agricultural Research, Paris, France
- Clinical Epidemiology Unit, Hôtel-Dieu Hospital, Assistance Publique–Hôpitaux de Paris, Paris, France
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York
| | - Emmanuel Cosson
- Sorbonne Paris Nord, Sorbonne Paris Cité, Assistance Publique–Hôpitaux de Paris, Avicenne Hospital, Department of Endocrinology, Research Centre in Human Nutrition–Ile de France, North Ile-de-France Integrated Obesity Centre, Bobigny, France
- Sorbonne Paris Nord, Centre of Research in Epidemiology and Statistics, Research Unit 1153, French National Institute of Health and Medical Research, U1125 National Institute for Agricultural Research, National Conservatory of Arts and Crafts, Bobigny, France
| | - Victor Montori
- Department of Health and Human Services, Center for Evidence and Practice Improvement of the Agency for Healthcare Research and Quality, Rockville, Maryland
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota
| | - Viet Thi Tran
- Université de Paris, Centre of Research in Epidemiology and Statistics, French National Institute of Health and Medical Research, National Institute for Agricultural Research, Paris, France
- Clinical Epidemiology Unit, Hôtel-Dieu Hospital, Assistance Publique–Hôpitaux de Paris, Paris, France
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Cui L, Schroeder PR, Sack PA. Inpatient and Outpatient Technologies to Assist in the Management of Insulin Dosing. Clin Diabetes 2020; 38:462-473. [PMID: 33384471 PMCID: PMC7755045 DOI: 10.2337/cd20-0054] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Several new technologies use computer algorithms to analyze a person's blood glucose response to insulin treatment, calculate the person's next recommended insulin dose, advise the person regarding when to check blood glucose next, and provide alerts regarding glucose control for the individual patient or across a hospital system. This article reviews U.S. Food and Drug Administration (FDA)-approved products designed to help manage insulin dosing for inpatients, as well as those available to provide people with insulin-requiring diabetes support in making adjustments to their basal and/or mealtime insulin doses. Many of these products have a provider interface that allows for remote monitoring of patients' glucose readings and insulin doses. By alleviating some of the burdens of insulin initiation and dose adjustment, these products may facilitate improved glycemic management and patient outcomes.
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Affiliation(s)
- Ling Cui
- Department of Medicine, MedStar Union Memorial Hospital, Baltimore, MD
| | | | - Paul A Sack
- Department of Medicine, MedStar Union Memorial Hospital, Baltimore, MD
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Franc S, Hanaire H, Benhamou PY, Schaepelynck P, Catargi B, Farret A, Fontaine P, Guerci B, Reznik Y, Jeandidier N, Penfornis A, Borot S, Chaillous L, Serusclat P, Kherbachi Y, d'Orsay G, Detournay B, Simon P, Charpentier G. DIABEO System Combining a Mobile App Software With and Without Telemonitoring Versus Standard Care: A Randomized Controlled Trial in Diabetes Patients Poorly Controlled with a Basal-Bolus Insulin Regimen. Diabetes Technol Ther 2020; 22:904-911. [PMID: 32407148 PMCID: PMC7757616 DOI: 10.1089/dia.2020.0021] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background: The DIABEO® system (DS) is a telemedicine solution that combines a mobile app for patients with a web portal for health care providers. DS allows real-time monitoring of basal-bolus insulin therapy as well as therapeutic decision-making, integrating both basal and bolus dose calculation. Real-life studies have shown a very low rate of use of mobile health applications by patients. Therefore, we conducted a large randomized controlled trial study to investigate the efficacy of DS in conditions close to real life (TELESAGE study). Methods: TELESAGE was a multicenter, randomized, open study with three parallel arms: arm 1 (standard care), arm 2 (DIABEO alone), and arm 3 (DIABEO+telemonitoring by trained nurses). The primary outcome assessed the reduction in HbA1c levels after a 12-month follow-up. Results: Six hundred sixty-five patients were included in the study. Participants who used DIABEO once or more times a day (DIABEO users) showed a significant and meaningful reduction of HbA1c versus standard care after a 12-month follow-up: mean difference -0.41% for arm 2-arm 1 (P = 0.001) and -0.51% for arm 3-arm 1 (P ≤ 0.001). DIABEO users included 25.1% of participants in arm 2 and 37.6% in arm 3. In the intention-to-treat population, HbA1c changes and incidence of hypoglycemia were comparable between arms. Conclusions: A clinical and statistically significant reduction in HbA1c levels was found in those patients who used DIABEO at least once a day.
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Affiliation(s)
- Sylvia Franc
- Department of Diabetes, Sud-Francilien Hospital, Corbeil-Essonnes, and Centre d'étude et de Recherche pour l'Intensification du Traitement du Diabète (CERITD), Evry, France
- Address correspondence to: Sylvia Franc, MD, Department of Diabetes, Sud-Francilien Hospital, Corbeil-Essonnes, Centre d'étude et de Recherche pour l'Intensification du Traitement du Diabète (CERITD), 116 Bd Jean Jaures, Evry 91100, France
| | - Hélène Hanaire
- Department of Diabetology, Metabolic Diseases and Nutrition, CHU Toulouse, University of Toulouse, Toulouse, France
| | | | - Pauline Schaepelynck
- Department of Nutrition-Endocrinology-Metabolic Disorders, Marseille University Hospital, Sainte Marguerite Hospital, Marseille, France
| | - Bogdan Catargi
- Department of Endocrinology and Diabetes, University Hospital, Bordeaux, France
| | - Anne Farret
- Department of Endocrinology, Diabetes and Nutrition, University Hospital, Montpellier, France
| | - Pierre Fontaine
- Department of Diabetology, University Hospital, Lille, France
| | - Bruno Guerci
- Endocrinology-Diabetes Care Unit, University of Lorraine, Vandoeuvre Lès Nancy, France
| | - Yves Reznik
- Department of Endocrinology, University of Caen Côte de Nacre Regional Hospital Center, Caen, France
| | - Nathalie Jeandidier
- Department of Endocrinology, Diabetes and Nutrition, CHU of Strasbourg, Strasbourg, France
| | - Alfred Penfornis
- Department of Diabetology, Metabolic Diseases and Nutrition, CHU Toulouse, University of Toulouse, Toulouse, France
- Professor at the University Paris-Sud, University Paris-Sud, Orsay, France
| | - Sophie Borot
- Centre Hospitalier Universitaire Jean Minjoz, Service d'Endocrinologie-Métabolisme et Diabétologie-Nutrition, Besançon, France
| | | | - Pierre Serusclat
- Endocrinology, Diabetology and Nutrition, Clinique Portes du Sud, Venissieux, France
| | | | | | | | - Pierre Simon
- National Association of Telemedicine, Evry, France
| | - Guillaume Charpentier
- Department of Diabetes, Sud-Francilien Hospital, Corbeil-Essonnes, and Centre d'étude et de Recherche pour l'Intensification du Traitement du Diabète (CERITD), Evry, France
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Ceriello A, deValk HW, Guerci B, Haak T, Owens D, Canobbio M, Fritzen K, Stautner C, Schnell O. The burden of type 2 diabetes in Europe: Current and future aspects of insulin treatment from patient and healthcare spending perspectives. Diabetes Res Clin Pract 2020; 161:108053. [PMID: 32035117 DOI: 10.1016/j.diabres.2020.108053] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 01/23/2020] [Accepted: 02/04/2020] [Indexed: 02/08/2023]
Abstract
Due to the progressive nature of type 2 diabetes (T2DM), initiation of insulin therapy is very likely in the disease continuum. This article aims at highlighting the current situation with regard to insulin therapy in people with T2DM in Europe and at presenting the associated unmet need. Challenges for both people with T2DM and healthcare professionals include clinical inertia also derived from fear of hypoglycaemia, weight gain and injections as well as increased need for a comprehensive diabetes management. We compare national and international guidelines and recommendations for the initiation and intensification of insulin therapy with the real-world situation in six European countries, demonstrating that glycaemic targets are only met in a minority of people with T2DM on insulin therapy. Furthermore, this work evaluates currently recorded numbers of people with T2DM treated with insulin in Europe, the proportion not achieving the stated glycaemic targets and thus in need to enhance insulin therapy e.g. by a change in means of insulin delivery including, but not limited to, insulin pens, wearable mealtime insulin delivery patches, patch pumps, and conventional insulin pumps with continuous subcutaneous insulin infusion.
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Affiliation(s)
| | - Harold W deValk
- Department of Internal Medicine, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Bruno Guerci
- Endocrinology, Diabetology & Nutrition Clinical Unit, Brabois Hospital & Center of Clinical Investigation ILCV, Centre Hospitalier Universitaire of Nancy, University of Lorraine Vandoeuvre-lès-Nancy, France
| | - Thomas Haak
- Diabetes Klinik Bad Mergentheim, Bad Mergentheim, Germany
| | - David Owens
- Diabetes Research Unit Cymru, Swansea University, Swansea, Wales, UK
| | | | | | | | - Oliver Schnell
- Sciarc GmbH, Baierbrunn, Germany; Forschergruppe Diabetes e.V., Muenchen-Neuherberg, Germany.
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Doupis J, Festas G, Tsilivigos C, Efthymiou V, Kokkinos A. Smartphone-Based Technology in Diabetes Management. Diabetes Ther 2020; 11:607-619. [PMID: 31983028 PMCID: PMC7048878 DOI: 10.1007/s13300-020-00768-3] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Indexed: 12/12/2022] Open
Abstract
Diabetes is a group of metabolic disorders characterized by elevated levels of blood glucose which leads over time to serious complications and significant morbidity and mortality worldwide. Self-management tasks in diabetes may be quite challenging because of lack of training, difficulties in sustaining lifestyle modifications, and limited access to specialized healthcare. Nowadays, the evolution of mobile technology provides a large number of health-related smartphone applications (apps), aiming to increase the self-management skills of the patient in chronic diseases, to facilitate the communication between the patient and healthcare providers, and to increase also the patient's compliance with the treatment. In the field of diabetes there are also many diabetes-related mobile apps mainly focusing on self-management of diabetes, lifestyle modification, and medication adherence motivation. The aim of this paper is to review the most important diabetes-related mobile smartphone applications, including only those supported by prospective randomized controlled trials.
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Affiliation(s)
- John Doupis
- Department of Internal Medicine and Diabetes, Salamis Naval and Veterans Hospital, Salamis Naval Base, 18900, Salamis Island, Attiki, Greece.
| | - Georgios Festas
- Department of Internal Medicine and Diabetes, Salamis Naval and Veterans Hospital, Salamis Naval Base, 18900, Salamis Island, Attiki, Greece
| | - Christos Tsilivigos
- Department of Internal Medicine and Diabetes, Salamis Naval and Veterans Hospital, Salamis Naval Base, 18900, Salamis Island, Attiki, Greece
| | - Vasiliki Efthymiou
- First Department of Pediatrics, Center for Adolescent Medicine and UNESCO Chair on Adolescent Health Care, School of Medicine, National and Kapodistrian University of Athens, Aghia Sophia Children's Hospital, Athens, Greece
| | - Alexander Kokkinos
- First Department of Propaedeutic Internal Medicine, Diabetes Centre, Laiko General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
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20
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Franc S, Joubert M, Daoudi A, Fagour C, Benhamou P, Rodier M, Boucherie B, Benamo E, Schaepelynck P, Guerci B, Dardari D, Borot S, Penfornis A, D'Orsay G, Mari K, Reznik Y, Randazzo C, Charpentier G. Efficacy of two telemonitoring systems to improve glycaemic control during basal insulin initiation in patients with type 2 diabetes: The TeleDiab-2 randomized controlled trial. Diabetes Obes Metab 2019; 21:2327-2332. [PMID: 31173451 PMCID: PMC6771866 DOI: 10.1111/dom.13806] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2019] [Revised: 05/24/2019] [Accepted: 06/05/2019] [Indexed: 11/27/2022]
Abstract
TeleDiab-2 was a 13-month randomized controlled trial evaluating the efficacy and safety of two telemonitoring systems to optimize basal insulin (BI) initiation in subjects with inadequately controlled type 2 diabetes (HbA1c, 7.5%-10%). A total of 191 participants (mean age 58.7 years, mean HbA1c 8.9%) were randomized into three groups: group 1(G1, standard care, n = 63), group 2 (G2, interactive voice response system, n = 64) and group 3 (G3, Diabeo-BI app software, n = 64). The two telemonitoring systems proposed daily adjustments of BI doses, in order to facilitate the achievement of fasting blood glucose (FBG) values targeted at ~100 mg/dL. At 4 months follow-up, HbA1c reduction was significantly higher in the telemonitoring groups (G2: -1.44% and G3: -1.48% vs. G1: -0.92%; P < 0.002). Moreover, target FBG was reached by twice as many patients in the telemonitoring groups as in the control group, and insulin doses were also titrated to higher levels. No severe hypoglycaemia was observed in the telemonitoring groups and mild hypoglycaemia frequency was similar in all groups. In conclusion, both telemonitoring systems improved glycaemic control to a similar extent, without increasing hypoglycaemic episodes.
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Affiliation(s)
- Sylvia Franc
- CERITD (Centre for Studies and Research for the Intensification of Diabetes Treatment)Bioparc Genopole CampusEvryFrance
- Department of DiabetesSud‐Francilien HospitalCorbeil‐EssonnesFrance
| | | | - Ahmed Daoudi
- CERITD (Centre for Studies and Research for the Intensification of Diabetes Treatment)Bioparc Genopole CampusEvryFrance
| | - Cédric Fagour
- Department of Diabetology and EndocrinologyFort‐de‐France University HospitalFort de FranceFrance
| | - Pierre‐Yves Benhamou
- Department of Diabetology, Endocrinology and Nutrition DiseasesGrenoble University HospitalGrenobleFrance
| | - Michel Rodier
- Department of Metabolic Diseases and EndocrinologyNimes University HospitalNimesFrance
| | - Beatrix Boucherie
- CERITD (Centre for Studies and Research for the Intensification of Diabetes Treatment)Bioparc Genopole CampusEvryFrance
| | - Eric Benamo
- Department of Endocrinology and Metabolic DiseasesAvignon University HospitalAvignonFrance
| | - Pauline Schaepelynck
- Department of Endocrinology, Diabetes and Metabolic DiseasesMarseille University HospitalMarseilleFrance
| | - Bruno Guerci
- Department of Endocrinology, Diabetes and NutritionNancy University HospitalNancyFrance
| | - Dured Dardari
- CERITD (Centre for Studies and Research for the Intensification of Diabetes Treatment)Bioparc Genopole CampusEvryFrance
- Department of DiabetesSud‐Francilien HospitalCorbeil‐EssonnesFrance
| | - Sophie Borot
- Department of Diabetology and EndocrinologyBesançon University HospitalBesançonFrance
| | - Alfred Penfornis
- Department of DiabetesSud‐Francilien HospitalCorbeil‐EssonnesFrance
| | | | - Karine Mari
- Randomised Clinical Trials (RCTs') Department of StatisticsLyonFrance
| | - Yves Reznik
- Diabetes Care UnitCaen University HospitalCaenFrance
| | - Caroline Randazzo
- CERITD (Centre for Studies and Research for the Intensification of Diabetes Treatment)Bioparc Genopole CampusEvryFrance
| | - Guillaume Charpentier
- CERITD (Centre for Studies and Research for the Intensification of Diabetes Treatment)Bioparc Genopole CampusEvryFrance
- Department of DiabetesSud‐Francilien HospitalCorbeil‐EssonnesFrance
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