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 < 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 (>85%), whereas room for improvement existed during other phases (<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.

Efficacy of metformin versus sulfonylurea derivative in HNF4A-MODY.

Summary: 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. Learning points: HNF4A-MODY has a mild phenotype. Blood glucose was responsive to long-term metformin treatment in HNF4A-MODY. Metformin and gliclazide seem appropriate treatments for HNF4A-MODY.

Glucose Regulation Beyond HbA1c in Type 2 Diabetes Treated With Insulin: Real-World Evidence From the DIALECT-2 Cohort.

OBJECTIVE: To investigate glucose variations associated with glycated hemoglobin (HbA1c) 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 HbA1c 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 HbA1c categories. RESULTS: CGM was performed for a median (interquartile range) of 10 (7-12) days/patient. TIR was not different for low and intermediate HbA1c 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 HbA1c category had lower TIR (52.7% [40.9-67.3]) and higher TAR (44.1% [27.8-57.0]) than the other HbA1c 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 HbA1c did not reduce the occurrence of nocturnal hypoglycemia, and low HbA1c was not associated with the highest TIR. Optimal personalization of glycemic control requires the use of newer tools, including CGM-derived parameters.

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: <5000, 5000-6999, 7000-9999, ≥ 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 <5000 steps/day. Patients with <5000 steps/day had, in comparison to patients who took ≥10,000 steps/day, a higher body mass index (BMI) (33 ± 6 vs. 30 ± 5 kg/m2, 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 (ß = 0.26, p < 0.001) and dietary protein intake (ß = 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.

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.