312 results match your criteria models cgm

Penalty weighted glucose prediction models could lead to better clinically usage.

Comput Biol Med 2021 Sep 15;138:104865. Epub 2021 Sep 15.

Department of Health Science and Technology, Aalborg University, Denmark.

Background And Objective: Numerous attempts to predict glucose value from continuous glucose monitors (CGM) have been published. However, there is a lack of proper analysis and modeling of penalty for errors in different glycemic ranges. The aim of this study was to investigate the potential for developing glucose prediction models with focus on the clinical aspects. Read More

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September 2021

Relationship between time-in-range, HbA1c and the glucose management indicator in pregnancies complicated by type 1 diabetes.

Diabetes Technol Ther 2021 Sep 15. Epub 2021 Sep 15.

University of Colorado Denver Barbara Davis Center for Childhood Diabetes, 21610, Department of Medicine and Pediatrics, 1775 Aurora Court, MS A140, Aurora, Colorado, United States, 80045;

Objective: We aimed to evaluate relationships between time-in-range (TIR 63-140 mg/dL), HbA1c level, and the glucose management indicator (GMI) in pregnant women with type 1 diabetes.

Research Design And Methods: Continuous glucose monitoring (CGM) data from 27 women with type 1 diabetes were collected prospectively throughout pregnancy. Up to 90-days of CGM data were correlated with point-of-care HbA1c levels measured in the clinic at each trimester. Read More

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September 2021

Comparison of cgmanalysis, a free, open-source continuous glucose monitoring (CGM) data management and analysis software to commercially available CGM platforms: Data standardization for diabetes technology research.

Diabetes Technol Ther 2021 Sep 15. Epub 2021 Sep 15.

University of Colorado Denver, Pediatrics, Aurora, Colorado, United States.

Background: Cgmanalysis is open-source software based on the R programming language for data management and descriptive analysis of data from continuous glucose monitors (CGM). We sought to validate the summary measures calculated by cgmanalysis against the results from proprietary software associated with 4 CGM commercially available models.

Methods: Two weeks of data from 188 patients with type 1 diabetes using commercially available CGMs. Read More

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September 2021

Eating architecture in adults at increased risk of type 2 diabetes: associations with body fat and glycaemic control.

Br J Nutr 2021 Aug 5:1-28. Epub 2021 Aug 5.

Adelaide Medical School, University of Adelaide, Adelaide, South Australia 5000, Australia.

Eating architecture is a term that describes meal frequency, meal timing, and meal size and the daily variation in each of these. The aim of this study was to determine the relationship between components of eating architecture on body fat and markers of glycaemic control in healthy adults at increased risk of type 2 diabetes (T2DM). Participants (N=73, 39 males, age 58. Read More

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Simulation Platform Development for Diabetes and Technology Self-Management.

J Diabetes Sci Technol 2021 Jul 22:19322968211029303. Epub 2021 Jul 22.

The Ohio State University Medical Center, Columbus, OH, USA.

Background: Specialized education is critical for optimal insulin pump use but is not widely utilized or accessible. We aimed to (1) test the usability and acceptability of A1Control, a simulation platform supporting insulin pump education, and (2) determine predictors of performance.

Method: Rural adult insulin pump users with type 1 diabetes (T1D) participated in a mixed methods usability study in 2 separate rounds. Read More

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Association of HbA1c with all-cause mortality across varying degrees of glycemic variability in type 2 diabetes.

J Clin Endocrinol Metab 2021 Jul 19. Epub 2021 Jul 19.

Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital; Shanghai Clinical Center for Diabetes; Shanghai Key Clinical Center for Metabolic Disease; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China.

Context: The interaction of glycated hemoglobin A1c (HbA1c) and glycemic variability in relation to diabetes-related outcomes remains unknown.

Objective: To evaluate the relationship between HbA1c and all-cause mortality across varying degrees of glycemic variability in patients with type 2 diabetes.

Design, Setting, And Patients: This was a prospective study conducted in a single referral center. Read More

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Longitudinal Observation of Insulin Use and Glucose Sensor Metrics in Pregnant Women with Type 1 Diabetes Using Continuous Glucose Monitors and Insulin Pumps: The LOIS-P Study.

Diabetes Technol Ther 2021 Aug 17. Epub 2021 Aug 17.

Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA.

Suboptimal glycemic control is associated with maternal and neonatal morbidity and mortality in pregnancy complicated by type 1 diabetes (T1D). Prospective analysis of continuous glucose monitoring (CGM) metrics, insulin pump settings, and insulin delivery can better characterize the changes in glycemic levels and insulin use throughout pregnancy with T1D. Prescribed parameters, insulin delivery, carbohydrate intake, and CGM data for 25 pregnant women with T1D from three U. Read More

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Deep transfer learning and data augmentation improve glucose levels prediction in type 2 diabetes patients.

NPJ Digit Med 2021 Jul 14;4(1):109. Epub 2021 Jul 14.

Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 02215, USA.

Accurate prediction of blood glucose variations in type 2 diabetes (T2D) will facilitate better glycemic control and decrease the occurrence of hypoglycemic episodes as well as the morbidity and mortality associated with T2D, hence increasing the quality of life of patients. Owing to the complexity of the blood glucose dynamics, it is difficult to design accurate predictive models in every circumstance, i.e. Read More

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Modified conventional gait model vs. Six degrees of freedom model: A comparison of lower limb kinematics and associated error.

Gait Posture 2021 Sep 22;89:1-6. Epub 2021 Jun 22.

Sport and Physical Activity, Edge Hill University, Ormskirk, Lancashire, L39 4QP, UK.

Background: The conventional gait model (CGM) is commonly utilised within clinical motion analysis but has a number of inherent limitations. To overcome some of these limitations modifications have been made to the CGM and six-degrees of freedom models (6DoF) have been developed.

Research Question: How comparable are lower limb kinematics calculated using modified CGM and 6DoF models and what is the error associated with the output of each model during walking?

Methods: Ten healthy males attended two gait analysis sessions, in which they walked at a self-selected pace, while a 10-camera motion capture system recorded lower limb kinematics. Read More

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September 2021

Machine learning-based glucose prediction with use of continuous glucose and physical activity monitoring data: The Maastricht Study.

PLoS One 2021 24;16(6):e0253125. Epub 2021 Jun 24.

CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands.

Background: Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown to improve glycaemic control. The ability to predict future glucose values can further optimize such devices. In this study, we used machine learning to train models in predicting future glucose levels based on prior CGM and accelerometry data. Read More

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Sleep quality and glycaemic variability in a real-life setting in adults with type 1 diabetes.

Diabetologia 2021 Oct 17;64(10):2159-2169. Epub 2021 Jun 17.

Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA.

Aims/hypothesis: Suboptimal subjective sleep quality is very common in adults with type 1 diabetes. Reducing glycaemic variability is a key objective in this population. To date, no prior studies have examined the associations between objectively measured sleep quality and overnight glycaemic variability in adults with type 1 diabetes. Read More

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October 2021

Association of Body Fat Percentage with Time in Range Generated by Continuous Glucose Monitoring during Continuous Subcutaneous Insulin Infusion Therapy in Type 2 Diabetes.

J Diabetes Res 2021 28;2021:5551216. Epub 2021 May 28.

Department of Endocrinology, Zhujiang Hospital, Southern Medical University, Guangzhou, 510282 Guangdong, China.

Background: Obesity is a crucial risk factor associated with type 2 diabetes mellitus (T2DM). Excessive accumulation of body fat may affect the glycemia control in T2DM. This study investigated the relationship between body fat percentage and time in range (TIR) assessed by continuous glucose monitoring (CGM) during short-term continuous subcutaneous insulin infusion (CSII) therapy in T2DM patients. Read More

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Improved individual and population-level HbA1c estimation using CGM data and patient characteristics.

J Diabetes Complications 2021 08 17;35(8):107950. Epub 2021 May 17.

Department of Management Science and Engineering, Stanford School of Engineering, Stanford, CA, USA; Division of Pediatric Endocrinology, Stanford School of Medicine, Stanford, CA, USA; Lucile Packard Children's Hospital, Stanford, CA, USA; Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA, USA; Clinical Excellence Research Center, Stanford School of Medicine, Stanford, CA, USA. Electronic address:

Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by COVID-19. Read More

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Identification of maternal continuous glucose monitoring metrics related to newborn birth weight in pregnant women with gestational diabetes.

Endocrine 2021 Jun 14. Epub 2021 Jun 14.

Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.

Purpose: To identify the specific glucose metrics derived from maternal continuous glucose monitoring (CGM) data, which were associated with a higher percentile of offspring birth weight.

Methods: In this cohort study, we recruited singleton pregnant women with GDM who underwent CGM for 5-14 days at a mean of 28.8 gestational weeks between Jan 2017 and Nov 2018. Read More

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A Worldwide Perspective on COVID-19 and Diabetes Management in 22,820 Children from the SWEET Project: Diabetic Ketoacidosis Rates Increase and Glycemic Control Is Maintained.

Diabetes Technol Ther 2021 09 18;23(9):632-641. Epub 2021 Aug 18.

Department of Paediatric Endocrinology, Diabetes and Metabolic Diseases, UMC-University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia.

To investigate the short-term effects of the first wave of COVID-19 on clinical parameters in children with type 1 diabetes (T1D) from 82 worldwide centers participating in the Better Control in Pediatric and Adolescent Diabete: orking to Crate Cners of Reference (SWEET) registry. Aggregated data per person with T1D ≤21 years of age were compared between May/June 2020 (first wave), August/September 2020 (after wave), and the same periods in 2019. Hierarchic linear and logistic regression models were applied. Read More

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September 2021

Glucose Prediction under Variable-Length Time-Stamped Daily Events: A Seasonal Stochastic Local Modeling Framework.

Sensors (Basel) 2021 May 4;21(9). Epub 2021 May 4.

Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, Camino de Vera, s/n, 46022 València, Spain.

Accurate glucose prediction along a long-enough time horizon is a key component for technology to improve type 1 diabetes treatment. Subjects with diabetes might benefit from supervision and control systems that accurately predict risks and trigger corrective actions early enough with improved mitigation. However, large intra-patient variability poses big challenges to glucose prediction. Read More

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Probabilistic Model of Transition between Categories of Glucose Profiles in Patients with Type 1 Diabetes Using a Compositional Data Analysis Approach.

Sensors (Basel) 2021 May 21;21(11). Epub 2021 May 21.

Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28029 Madrid, Spain.

The time spent in glucose ranges is a common metric in type 1 diabetes (T1D). As the time in one day is finite and limited, Compositional Data (CoDa) analysis is appropriate to deal with times spent in different glucose ranges in one day. This work proposes a CoDa approach applied to glucose profiles obtained from six T1D patients using continuous glucose monitor (CGM). Read More

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A Conditional Generative Adversarial Network for Synthesis of Continuous Glucose Monitoring Signals.

J Diabetes Sci Technol 2021 May 30:19322968211014255. Epub 2021 May 30.

Department of Health Science and Technology, Aalborg University, Denmark.

This report describes how a Conditional Generative Adversarial Network (CGAN) was used to synthesize realistic continuous glucose monitoring systems (CGM) from healthy individuals and individuals with type 1 diabetes over a range of different HbA1c levels. The results showed that even though the CGAN generated data, did not perfectly reflect real world CGM, many of the important features were captured and reflected in the synthetic signals. It is briefly discussed how heterogenous data sources constitutes a challenge for comparison of predictive CGM models. Read More

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Greater daily glucose variability and lower time in range assessed with continuous glucose monitoring are associated with greater aortic stiffness: The Maastricht Study.

Diabetologia 2021 Aug 15;64(8):1880-1892. Epub 2021 May 15.

CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, the Netherlands.

Aims: CVD is the main cause of morbidity and mortality in individuals with diabetes. It is currently unclear whether daily glucose variability contributes to CVD. Therefore, we investigated whether glucose variability is associated with arterial measures that are considered important in CVD pathogenesis. Read More

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The importance of a consistent workflow to estimate muscle-tendon lengths based on joint angles from the conventional gait model.

Gait Posture 2021 07 27;88:1-9. Epub 2021 Apr 27.

Center for Gait and Motion Analysis, Gillette Children's Specialty Healthcare, St Paul, MN, USA; Department of Orthopedic Surgery, University of Minnesota, Minneapolis, MN, USA.

Background: Musculoskeletal models enable us to estimate muscle-tendon length, which has been shown to improve clinical decision-making and outcomes in children with cerebral palsy. Most clinical gait analysis services, however, do not include muscle-tendon length estimation in their clinical routine. This is due, in part, to a lack of knowledge and trust in the musculoskeletal models, and to the complexity involved in the workflow to obtain the muscle-tendon length. Read More

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The effects of professional continuous glucose monitoring as an adjuvant educational tool for improving glycemic control in patients with type 2 diabetes.

BMC Endocr Disord 2021 Apr 23;21(1):79. Epub 2021 Apr 23.

Epidemiology and Health Services Research Unit, CMN Siglo XXI, Mexican Institute of Social Security, Av. Cuauhtemoc 330, Col. Doctores, Del. Cuauhtemoc, 06720, Mexico City, Mexico.

Background: The study objective was to evaluate the effects of professional continuous glucose monitoring (CGM) as an adjuvant educational tool for improving glycemic control in patients with type 2 diabetes (T2D).

Methods: We conducted a three-month quasi-experimental study with an intervention (IGr) and control group (CGr) and ex-ante and ex-post evaluations in one family medicine clinic in Mexico City. Participants were T2D patients with HbA1c > 8% attending a comprehensive diabetes care program. Read More

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Exploring the inter-subject variability in the relationship between glucose monitoring metrics and glycated hemoglobin for pediatric patients with type 1 diabetes.

J Pediatr Endocrinol Metab 2021 May 7;34(5):619-625. Epub 2021 Apr 7.

Department of Electrical, Computer and Biomedical Engineering, Università degli Studi di Pavia, Pavia, Italy.

Objectives: Despite the widespread diffusion of continuous glucose monitoring (CGM) systems, which includes both real-time CGM (rtCGM) and intermittently scanned CGM (isCGM), an effective application of CGM technology in clinical practice is still limited. The study aimed to investigate the relationship between isCGM-derived glycemic metrics and glycated hemoglobin (HbA1c), identifying overall CGM targets and exploring the inter-subject variability.

Methods: A group of 27 children and adolescents with type 1 diabetes under multiple daily injection insulin-therapy was enrolled. Read More

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Critical Comparison of MaxCal and Other Stochastic Modeling Approaches in Analysis of Gene Networks.

Entropy (Basel) 2021 Mar 17;23(3). Epub 2021 Mar 17.

Molecular and Cellular Biophysics, University of Denver, Denver, CO 80208, USA.

Learning the underlying details of a gene network with feedback is critical in designing new synthetic circuits. Yet, quantitative characterization of these circuits remains limited. This is due to the fact that experiments can only measure partial information from which the details of the circuit must be inferred. Read More

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Continuous glucose monitoring indices predict poor FEV recovery following cystic fibrosis pulmonary exacerbations.

J Cyst Fibros 2021 Mar 26. Epub 2021 Mar 26.

Monash Centre for Health Research and Implementation, Monash University, Melbourne, Victoria, Australia.

Background: Little is known about the effect of dysglycemia during cystic fibrosis pulmonary exacerbation (PEx) on recovery of FEV percentage predicted (ppFEV) METHODS: Continuous glucose monitoring (CGM) was commenced at the time of admission to hospital for PEx and continued for 6 weeks. The CGM indices, percentage of time glucose greater than 7.8 mmol/L (%T>7. Read More

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A "Slide Rule" to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life.

Diabetes Ther 2021 May 16;12(5):1313-1324. Epub 2021 Mar 16.

Department of Information Engineering, University of Padova, Padova, Italy.

Introduction: In persons with type 1 diabetes (T1D) insulin dosing can be adjusted based on trend arrows derived from continuous glucose monitoring (CGM). We propose a slide rule with narrower blood glucose intervals and more classes of insulin sensitivity than are available in current models.

Methods: The slide rule was tested in silico, in which a meal was simulated in 100 virtual subjects and the insulin bolus was calculated either in the standard way based on the insulin-to-carbohydrate ratio and the correction factor or according to the slide rule, following which the percentage time spent in range (70-180 mg/dl; %T), hypoglycemia (< 70 mg/dl; %T), and hyperglycemia (> 180 mg/dl; %T) was compared between the methods during the 4 h after the meal. Read More

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Forecasting of Glucose Levels and Hypoglycemic Events: Head-to-Head Comparison of Linear and Nonlinear Data-Driven Algorithms Based on Continuous Glucose Monitoring Data Only.

Sensors (Basel) 2021 Feb 27;21(5). Epub 2021 Feb 27.

Department of Information Engineering, University of Padova, 35131 Padova, Italy.

In type 1 diabetes management, the availability of algorithms capable of accurately forecasting future blood glucose (BG) concentrations and hypoglycemic episodes could enable proactive therapeutic actions, e.g., the consumption of carbohydrates to mitigate, or even avoid, an impending critical event. Read More

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February 2021

Glycemic Outcome Associated With Insulin Pump and Glucose Sensor Use in Children and Adolescents With Type 1 Diabetes. Data From the International Pediatric Registry SWEET.

Diabetes Care 2021 May 2;44(5):1176-1184. Epub 2021 Mar 2.

The Department of Paediatrics and Endocrinology, Cork University Hospital, Cork, Ireland.

Objective: Insulin delivery methods, glucose-monitoring modalities, and related outcomes were examined in a large, international, diverse cohort of children and adolescents with type 1 diabetes from the Better Control in Pediatric and Adolescent Diabetes: Working to Create Centers of Reference (SWEET) -Registry.

Research Design And Methods: Participants with type 1 diabetes of ≥1 year, aged ≤18 years, and who had documented pump or sensor usage during the period August 2017-July 2019 were stratified into four categories: injections-no sensor (referent); injections + sensor; pump-no sensor; and pump + sensor. HbA and proportion of patients with diabetic ketoacidosis (DKA) or severe hypoglycemia (SH) were analyzed; linear and logistic regression models adjusted for demographics, region, and gross domestic product per capita were applied. Read More

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Previous diabetic ketoacidosis as a risk factor for recurrence in a large prospective contemporary pediatric cohort: Results from the DPV initiative.

Pediatr Diabetes 2021 05 21;22(3):455-462. Epub 2021 Feb 21.

Institute of Epidemiology and Medical Biometry, ZIBMT, Ulm University, Ulm, Germany.

Objective: To assess the role of previous episodes of diabetic ketoacidosis (DKA) and their time-lag as risk factors for recurring DKA in youth with type 1 diabetes (T1D).

Research Design And Methods: In a population-based analysis, data from 29,325 children and adolescents with T1D and at least 5 years of continuous follow-up were retrieved from the "Diabetes Prospective Follow-up" (DPV) multi-center registry in March 2020. Statistical analyses included unadjusted comparisons, logistic and negative binomial regression models. Read More

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Time in range-A1c hemoglobin relationship in continuous glucose monitoring of type 1 diabetes: a real-world study.

BMJ Open Diabetes Res Care 2021 01;9(1)

Endocrinology, Ospedale Molinette, Torino, Piemonte, Italy

Introduction: The availability of easily accessible continuous glucose monitoring (CGM) metrics can improve glycemic control in diabetes, and they may even become a viable alternative to hemoglobin A1c (HbA1c) laboratory tests in the next years. The REALISM-T1D study (REAl-Life glucoSe Monitoring in Type 1 Diabetes) was aimed at contributing, with real-world data, to a deeper understanding of these metrics, including the time in range (TIR)-HbA1c relationship, to facilitate their adoption by diabetologists in everyday practice.

Research Design And Methods: 70 adults affected by type 1 diabetes were monitored for 1 year by means of either flash (FGM) or real-time (rtCGM) glucose monitoring devices. Read More

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January 2021

Associations between continuous glucose monitoring-derived metrics and arterial stiffness in Japanese patients with type 2 diabetes.

Cardiovasc Diabetol 2021 01 7;20(1):15. Epub 2021 Jan 7.

Department of Metabolism & Endocrinology, Juntendo University Graduate School of Medicine, Hongo 2-1-1 Bunkyo-ku, Tokyo, Japan.

Background: Previous studies have suggested that high mean glucose levels and glycemic abnormalities such as glucose fluctuation and hypoglycemia accelerate the progression of atherosclerosis in patients with type 2 diabetes. Although continuous glucose monitoring (CGM) that could evaluate such glycemic abnormalities has been rapidly adopted, the associations between CGM-derived metrics and arterial stiffness are not entirely clear.

Methods: This exploratory cross-sectional study used baseline data from an ongoing prospective, multicenter, observational study with 5 years of follow-up. Read More

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January 2021