Efficacy of metformin versus sulfonylurea derivative in HNF4A-MODY

This study compares the effects of metformin, sulfonylurea derivative (SU) and no treatment in HNF4A-MODY on glycemic control. In two patients with HNF4A-MODY, we changed the existing metformin treatment to SU derivative. The effect on the glycemic control was registered with a Freestyle Libre Flash glucose monitoring device. Each treatment period had a duration of 2 consecutive weeks, and in between, an intermediate period without medication. Data from the first 2 days after changing medications were excluded. We calculated time in range (TIR), and differences in the mean glucose level were tested with a one-way ANOVA test. The 24-h average glucose levels were significantly lower with either metformin (7.7 mmol/L; P < 0.001 and 6.3 mmol/L; P < 0.001) or gliclazide (7.6 mmol/L; P < 0.001 and 5.8 mmol/L; P < 0.001) compared to no treatment (9.4 and 8.9 mmol/L). The TIR with metformin or gliclazide was higher than without treatment (patient 1: 87 and 83 vs 61% and patient 2: 83 and 93 vs 67%). Treatment with either metformin or gliclazide effectively decreases blood glucose, rendering both drugs appropriate for treating HNF4A-MODY

Urinary creatinine excretion is an indicator of physical performance and function

Muscle mass is essential for performing physical activity, and low muscle mass (sarcopenia) has been found to have a strong association with all-cause mortality in patients with type 2 diabetes (T2D).1 However, muscle mass is not routinely assessed in clinical practice and low muscle mass can easily go unnoticed in obese patients (sarcopenic obesity), which was emphasized in previous DIALECT findings.2 The current definition of sarcopenia requires presence of either low muscle mass, low muscle strength or poor physical performance rather than low muscle mass alone.3 Two methods for estimating muscle mass independent of kidney function in clinical practice are the 24 h urinary creatinine excretion rate (CER) and bioelectric impedance analysis (BIA), but their association with physical performance and function is unclear.4 In this study we investigate whether CER or BIA-derived predicted muscle mass also indicate physical performance and function in patients with T2D, in order to indirectly screen patients on sarcopenia

Glucose regulation beyond hba_1c in type 2 diabetes treated with insulin:Real-world evidence from the dialect-2 cohort

OBJECTIVE: To investigate glucose variations associated with glycated hemoglobin (HbA(1c)) in insulin-treated patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: Patients included in Diabetes and Lifestyle Cohort Twente (DIALECT)-2 (n = 79) were grouped into three HbA(1c) categories: low, intermediate, and high (≤53, 54–62, and ≥63 mmol/mol or ≤7, 7.1–7.8, and ≥7.9%, respectively). Blood glucose time in range (TIR), time below range (TBR), time above range (TAR), glucose variability parameters, day and night duration, and frequency of TBR and TAR episodes were determined by continuous glucose monitoring (CGM) using the FreeStyle Libre sensor and compared between HbA(1c) categories. RESULTS: CGM was performed for a median (interquartile range) of 10 (7–12) days/patient. TIR was not different for low and intermediate HbA(1c) categories (76.8% [68.3–88.2] vs. 76.0% [72.5.0–80.1]), whereas in the low category, TBR was higher and TAR lower (7.7% [2.4–19.1] vs. 0.7% [0.3–6.1] and 8.2% [5.7–17.6] vs. 20.4% [11.6–27.0], respectively; P < 0.05). Patients in the highest HbA(1c) category had lower TIR (52.7% [40.9–67.3]) and higher TAR (44.1% [27.8–57.0]) than the other HbA(1c) categories (P < 0.05), but did not have less TBR during the night. All patients had more (0.06 ± 0.06/h vs. 0.03 ± 0.03/h; P = 0.002) and longer (88.0 [45.0–195.5] vs. 53.4 [34.4–82.8] minutes; P < 0.001) TBR episodes during the night than during the day. CONCLUSIONS: In this study, a high HbA(1c) did not reduce the occurrence of nocturnal hypoglycemia, and low HbA(1c) was not associated with the highest TIR. Optimal personalization of glycemic control requires the use of newer tools, including CGM-derived parameters

Transparency in hip fracture recovery over institutional boundaries:The transmural monitoring pathway

Objectives: To develop a transmural pathway for healthcare professionals across institutions to monitor the recovery of hip fracture patients. The secondary objectives were to evaluate the pathway's feasibility and initial outcomes. Design: Prospective cohort study. Method: Stakeholders of the hospital and geriatric rehabilitation institutions implemented a transmural monitoring pathway in which different geriatric health domains were monitored during three phases: The in-hospital, inpatient rehabilitation, and outpatient follow-up phase. The outcomes for the first 291 patients and the feasibility of the pathway were evaluated. If the outcomes of the clinimetrics significantly improved over time, progress in functional recovery was assumed. Feasibility was assessed according to the rate of adherence to the clinimetric tests. Results: During the in-hospital phase, patients showed a decline in functional level (the Katz index of independence in Activities of Daily Living (Katz-ADL) pre-fracture vs. discharge: 0 (0–2) vs. 4 (4–5), P &lt; 0.001). Patients, in which 78.6% (n = 140) had cognitive impairment and 41.2% had malnutrition, showed the most progress (Katz-ADL 2 (1–3)) during the inpatient rehabilitation phase. In the outpatient follow-up phase, recovery remained ongoing, but most patients had not returned to their pre-fracture functional levels (Katz-ADL 1 (1–3)). The pathway feasibility during the first phase was excellent (&gt;85%), whereas room for improvement existed during other phases (&lt;85%). Conclusion: The transmural monitoring pathway provides insight into the entire recovery process for all involved healthcare professionals. Patients showed the most progress during the rehabilitation phase. The pathway feasibility was excellent during the in-hospital phase, but improvements could be made during other phases.</p

Low Physical Activity in Patients with Complicated Type 2 Diabetes Mellitus Is Associated with Low Muscle Mass and Low Protein Intake

Objective: In order to promote physical activity (PA) in patients with complicated type 2 diabetes, a better understanding of daily movement is required. We (1) objectively assessed PA in patients with type 2 diabetes, and (2) studied the association between muscle mass, dietary protein intake, and PA. Methods: We performed cross-sectional analyses in all patients included in the Diabetes and Lifestyle Cohort Twente (DIALECT) between November 2016 and November 2018. Patients were divided into four groups: = 10,000 steps/day. We studied the association between muscle mass (24 h urinary creatinine excretion rate, CER) and protein intake (by Maroni formula), and the main outcome variable PA (steps/day, Fitbit Flex device) using multivariate linear regression analyses. Results: In the 217 included patients, the median steps/day were 6118 (4115-8638). Of these patients, 48 patients (22%) took 7000-9999 steps/day, 37 patients (17%) took >= 10,000 steps/day, and 78 patients (36%) took = 10,000 steps/day, a higher body mass index (BMI) (33 +/- 6 vs. 30 +/- 5 kg/m(2), p = 0.009), lower CER (11.7 +/- 4.8 vs. 14.8 +/- 3.8 mmol/24 h, p = 0.001), and lower protein intake (0.84 +/- 0.29 vs. 1.08 +/- 0.22 g/kg/day, p < 0.001). Both creatinine excretion (beta = 0.26, p < 0.001) and dietary protein intake (beta = 0.31, p < 0.001) were strongly associated with PA, which remained unchanged after adjustment for potential confounders. Conclusions: Prevalent insufficient protein intake and low muscle mass co-exist in obese patients with low physical activity. Dedicated intervention studies are needed to study the role of sufficient protein intake and physical activity in increasing or maintaining muscle mass in patients with type 2 diabetes

A Pilot Study on the Diameter app: Lifestyle Support for Type 2 Diabetes Mellitus Patients

Background: Diabetes mellitus is one of the most common non-communicable diseases worldwide. In patients with Diabetes Mellitus type 2 (T2DM), a healthy lifestyle is essential as it has positive effects on glucose regulation and therefore reduces the risk of complications. ZiekenhuisGroep Twente (ZGT), University of Twente (UT) and Roessingh Research & Development (RRD) developed ‘the Diameter’ in close corporation with T2DM patients and professionals from the outset. The Diameter is a mobile application that supports patients with T2DM to develop a healthy lifestyle to support optimal glucose regulation. The Diameter enables continuous monitoring of nutrition (via a food diary), physical activity (via activity tracker Fitbit) and glucose values (via Freestyle libre sensor). Furthermore, the Diameter offers guided goal setting, personal lifestyle coaching via daily informative and motivating coaching messages and weekly exercises aimed at learning to cope with barriers that arise in daily life to maintain a healthy lifestyle. Methods: A mixed-method approach was used to explore intervention usage and acceptability regarding the Diameter. Ten patients with T2DM who were treated at the diabetes outpatient clinic of ZGT hospital used the Diameter for 10 weeks. Study participants monitored physical activity, nutrition, blood glucose values and the achievement of lifestyle goals. In addition, participants received digital coaching offered by two short coaching messages per day and one exercise per week. Log-data was analyzed to assess the number of times and duration the Diameter and each component was used. To assess acceptability, questionnaires and open-ended interviews were used to gain insight into perceptions of participants regarding the determinants of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model and perceived barriers and facilitating conditions concerning Diameter usage. Findings: The first results revealed that participants appreciated the self-monitoring functionalities the most as it provided new insights into lifestyle and how glucose levels respond accordingly. This resulted in the monitoring functions being used frequently over the entire period of use. About 80% of the coaching message was liked. Feedback included that messages often contained already known knowledge, but also provided useful advice to improve lifestyle. The purpose of the weekly exercises was unclear for some participants and this functionality was hardly used by them. About 85% of the exercises were completed by participants who understood the purpose of the exercise. Points for improvement can mainly be found in expanding the food diary with additional nourishments and offering more tailored coaching based on real-time data. According to the participants, the Diameter can lead to more personalized care by providing healthcare professionals with insight into lifestyle data and might have the potential to improve diabetes management if used in blended-care setting. Discussion: The first perceptions regarding the Diameter were predominantly positive, although mainly the coaching components contain points for improvement. Clear information about the purpose of functionalities seems important to stimulate their use. Moreover, good integration of the Diameter in current diabetes care is considered an important condition for contributing to diabetes management

Consequences of Data Loss on Clinical Decision-Making in Continuous Glucose Monitoring:Retrospective Cohort Study

Background: The impact of missing data on individual continuous glucose monitoring (CGM) data is unknown but can influenceclinical decision-making for patients.Objective: We aimed to investigate the consequences of data loss on glucose metrics in individual patient recordings fromcontinuous glucose monitors and assess its implications on clinical decision-making.Methods: The CGM data were collected from patients with type 1 and 2 diabetes using the FreeStyle Libre sensor (AbbottDiabetes Care). We selected 7-28 days of 24 hours of continuous data without any missing values from each individual patient.To mimic real-world data loss, missing data ranging from 5% to 50% were introduced into the data set. From this modified dataset, clinical metrics including time below range (TBR), TBR level 2 (TBR2), and other common glucose metrics were calculatedin the data sets with and that without data loss. Recordings in which glucose metrics deviated relevantly due to data loss, asdetermined by clinical experts, were defined as expert panel boundary error (εEPB). These errors were expressed as a percentageof the total number of recordings. The errors for the recordings with glucose management indicator &lt;53 mmol/mol wereinvestigated.Results: A total of 84 patients contributed to 798 recordings over 28 days. With 5%-50% data loss for 7-28 days recordings,the εEPB varied from 0 out of 798 (0.0%) to 147 out of 736 (20.0%) for TBR and 0 out of 612 (0.0%) to 22 out of 408 (5.4%)recordings for TBR2. In the case of 14-day recordings, TBR and TBR2 episodes completely disappeared due to 30% data lossin 2 out of 786 (0.3%) and 32 out of 522 (6.1%) of the cases, respectively. However, the initial values of the disappeared TBRand TBR2 were relatively small (&lt;0.1%). In the recordings with glucose management indicator &lt;53 mmol/mol the εEPB was 9.6%for 14 days with 30% data loss.Conclusions: With a maximum of 30% data loss in 14-day CGM recordings, there is minimal impact of missing data on theclinical interpretation of various glucose metrics

Requirements of an Application to Monitor Diet, Physical Activity and Glucose Values in Patients with Type 2 Diabetes: The Diameter

Adherence to a healthy diet and regular physical activity are two important factors in sufficient type 2 diabetes mellitus management. It is recognized that the traditional treatment of outpatients does not meet the requirements for sufficient lifestyle management. It is hypothesised that a personalized diabetes management mHealth application can help. Such an application ideally measures food intake, physical activity, glucose values, and medication use, and then integrates this to provide patients and healthcare professionals insight in these factors, as well as the effect of lifestyle on glucose values in daily life. The lifestyle data can be used to give tailored coaching to improve adherence to lifestyle recommendations and medication use. This study describes the requirements for such an application: the Diameter. An iterative mixed method design approach is used that consists of a cohort study, pilot studies, literature search, and expert meetings. The requirements are defined according to the Function and events, Interactions and usability, Content and structure and Style and aesthetics (FICS) framework. This resulted in 81 requirements for the dietary (n = 37), activity and sedentary (n = 15), glycaemic (n = 12), and general (n = 17) parts. Although many applications are currently available, many of these requirements are not implemented. This stresses the need for the Diameter as a new personalized diabetes application