Explore the vast range of titles available.

To appraise the Diabetes Self-Management Questionnaire (DSMQ)'s measurement of diabetes self-management as a statistical predictor of glycaemic control relative to the widely used SDSCA. 248 patients with type 1 diabetes and 182 patients with type 2 diabetes were cross-sectionally assessed using the two self-report measures of diabetes self-management DSMQ and SDSCA; the scales were used as competing predictors of HbA1c. We developed a structural equation model of self-management as measured by the DSMQ and analysed the amount of variation explained in HbA1c; an analogue model was developed for the SDSCA. The structural equation models of self-management and glycaemic control showed very good fit to the data. The DSMQ's measurement of self-management showed associations with HbA1c of -0.53 for type 1 and -0.46 for type 2 diabetes (both P < 0.001), explaining 21% and 28% of variation in glycaemic control, respectively. The SDSCA's measurement showed associations with HbA1c of -0.14 (P = 0.030) for type 1 and -0.31 (P = 0.003) for type 2 diabetes, explaining 2% and 10% of glycaemic variation. Predictive power for glycaemic control was significantly higher for the DSMQ (P < 0.001). This study supports the DSMQ as the preferred tool when analysing self-reported behavioural problems related to reduced glycaemic control. The scale may be useful for clinical assessments of patients with suboptimal diabetes outcomes or research on factors affecting associations between self-management behaviours and glycaemic control.

The treatment of diabetes requires substantial self-management. Digital tools can help reduce the burden of self-management and may improve glycemic control. This study aims to determine whether the use of a digital diabetes logbook increased the likelihood of achieving optimal glycemic control (glycated hemoglobin [HbA ] ≤6.5%) after 3 months, based on a secondary analysis of randomized controlled trial (RCT) data. A secondary objective was to evaluate the long-term impact of the logbook on mean blood glucose levels over 3 and 12 months using observational, real-world data (RWD). Data from 342 participants with type 1 or type 2 diabetes enrolled in the mySugr PRO-RCT were analyzed. A robust logistic regression was performed to examine the likelihood of achieving optimal glycemic control, defined as an HbA1c value ≤6.5% at the 3-month follow-up. The dependent variable was the dichotomous outcome indicating whether this threshold was met. The primary independent variable was group allocation, with baseline HbA1c included as a covariate. For the analysis of RWD, a total of 2861 participants with type 1 or type 2 diabetes were identified using propensity score matching to align their characteristics with those of the RCT participants closely. One-sample t tests were conducted to analyze changes in mean blood glucose separately for each diabetes type, from baseline to 3 months of app use, and from baseline to 12 months of app use (in a subcohort of 1176 participants). The RCT data showed that the likelihood of achieving optimal glycemic control was nearly doubled in the intervention group compared with the control group (odds ratio 2.24, 95% CI 1.12-4.47; P=.02). RWD indicated that mean blood glucose levels significantly improved over 3 months of app use in both groups (type 1: -16.3 mg/dL; 95% CI -20.6 to -12.4; P<.001 and type 2: -27.3 mg/dL, 95% CI -28.7 to -25.9; P<.001). Participants with an estimated HbA >8.5% at baseline (before app use) showed the greatest reductions in mean blood glucose (type 1: -82.2 mg/dL; 95% CI -102.0 to -61.8; P<.001; type 2: -104.6 mg/dL, 95% CI -109.1 to -100.3; P<.001). Long-term analyses revealed a sustained reduction in mean blood glucose over a 12-month period, with a mean decrease of -19.8 mg/dL (95% CI -21.8 to -17.9; P<.001) after 12 months of app use in the total RWD sample. The secondary analysis of the RCT demonstrated a significant increase in the likelihood of achieving optimal glycemic control after 3 months of using the mySugr logbook. This finding was supported by observational, real-world data, which showed significant reductions in mean blood glucose after 3 and 12 months of app use-particularly among individuals with elevated baseline HbA1c levels. German Clinical Trials Register DRKS00022923; https://drks.de/search/en/trial/DRKS00022923/details.

Inflammation is a probable biological pathway underlying the relationship between diabetes and depression, but data on differences between diabetes types and symptom clusters of depression are scarce. Therefore, this cross-sectional study aimed to compare associations of a multimarker panel of biomarkers of inflammation with depressive symptoms and its symptom clusters between people with type 1 diabetes (T1D) and type 2 diabetes (T2D). This cross-sectional study combined data from five studies including 1260 participants ( n  = 706 T1D, n  = 454 T2D). Depressive symptoms were assessed using the Center for Epidemiological Studies-Depression Scale (CES-D). Serum levels of 92 biomarkers of inflammation were quantified with proximity extension assay technology. After quality control, 76 biomarkers of inflammation remained for statistical analysis. Associations between biomarkers and depressive symptom scores and clusters (cognitive-affective, somatic, anhedonia) were estimated with multivariable linear regression models. Nine biomarkers were positively associated with depressive symptoms in the total sample (CCL11/eotaxin, CCL25, CDCP1, FGF-21, IL-8, IL-10RB, IL-18, MMP-10, TNFRSF9; all p  < 0.05) without interaction by diabetes type. Associations differed for eight biomarkers ( p interaction  < 0.05). TNFβ was inversely associated with depressive symptoms in T1D, whereas three biomarkers (GDNF, IL-18R1, LIF-R) were positively associated with depressive symptoms in T2D. For the remaining four biomarkers (CD6, CD244, FGF-5, IFNγ) associations were not significant in either subgroup. Biomarker associations were more pronounced with somatic and anhedonia than with cognitive-affective symptoms. These results indicate that different proinflammatory pathways may contribute to depression in T1D and T2D and that there may be a symptom specificity in the link between subclinical inflammation and depression.

Heart rate variability (HRV) is widely recognized as an indicator of general health, particularly time domain measures like the root mean square of successive differences (RMSSD) between consecutive heartbeats. Consumer wearables measuring HRV have potential for wide accessibility meaning that their broad use to capture HRV as a health biomarker is possible. Our objective was to investigate the validity of HRV measured by wearables as a general health indicator. We examined whether resting HRV assessed by wearables across five studies—two using smartwatches, two using heart rate chest straps, and one using a smartring—exhibited expected associations with diverse health domains, including mental, physical, behavioral, functional, and physiological. We focused on resting HRV measures recorded while in primarily stationary conditions, either upon waking or while sleeping, because such measures would theoretically reduce the effects of potential confounders such as movement artifacts, daytime caffeine intake, and postural changes. Wearables measured resting HRV had small-to-moderate associations with more clinically oriented and trait-like (or slow-changing) health measures like Hba1c (average blood glucose, r = −0.21, p = 0.014), depressive symptoms (r = −0.22, p = 0.024), and sleep difficulty (r = −0.11, p = 0.003). Wearable-measured resting HRV can potentially serve as a health biomarker, but further research is needed.

Depressive symptoms in people with diabetes are associated with increased risk of adverse outcomes. Although successful psychosocial treatment options are available, little is known about factors that facilitate treatment response for depression in diabetes. This prospective study aims to examine the impact of known risk factors on improvement of depressive symptoms with a special interest in the role of diabetes-related distress. 181 people with diabetes participated in a randomized controlled trial. Diabetes-related distress was assessed using the Problem Areas In Diabetes (PAID) scale; depressive symptoms were assessed using the Center for Epidemiologic Studies Depression (CES-D) scale. Multiple logistic and linear regression analyses were used to assess associations between risk factors for depression (independent variables) and improvement of depressive symptoms (dependent variable). Reliable change indices were established as criteria of meaningful reductions in diabetes distress and depressive symptoms. A reliable reduction of diabetes-related distress (15.43 points in the PAID) was significantly associated with fourfold increased odds for reliable improvement of depressive symptoms (OR = 4.25, 95% CI: 2.05-8.79; P<0.001). This result was corroborated using continuous measures of diabetes distress and depressive symptoms, showing that greater reduction of diabetes-related distress independently predicted greater improvement in depressive symptoms (ß = -0.40; P<0.001). Higher age had a positive (Odds Ratio = 2.04, 95% CI: 1.21-3.43; P<0.01) and type 2 diabetes had a negative effect on the meaningful reduction of depressive symptoms (Odds Ratio = 0.12, 95% CI: 0.04-0.35; P<0.001). The reduction of diabetes distress is a statistical predictor of improvement of depressive symptoms. Diabetes patients with comorbid depressive symptomatology might benefit from treatments to reduce diabetes-related distress.

The effectiveness of an intervention in clinical practice is often reduced compared to the efficacy demonstrated in a randomised controlled trial (RCT). In this comparative effectiveness study, the RCT-proven efficacy of a diabetes education programme for type 1 diabetic patients (PRIMAS) was compared to the effectiveness observed in an implementation trial (IT) under routine care conditions. 75 patients with type 1 diabetes received PRIMAS through an RCT, whereas 179 patients were observed in an implementation trial. Baseline characteristics and treatment outcomes at the 6-month follow-up (improvement of HbA1c, hypoglycaemia problems, and diabetes-related distress) were compared. At baseline, the type 1 diabetic patients in the RCT had a significant longer diabetes duration (18.7 ± 12.3 vs. 13.8 ± 12.7 yrs., p = .005), lower self-efficacy scores (21.9 ± 4.7 vs. 23.7 ± 6.1, p = .02) and a greater number of diabetes complications (0.8 ± 1.3 vs. 0.4 ± 0.9, p = .02). After 6 months, PRIMAS achieved comparable effects under RCT and implementation trial conditions, as demonstrated by improvement in HbA1c (-0.36% ± 1.1 vs. -0.37 ± 1.2; Δ -0.01, 95% CI -0.33 to 0.31) and hypoglycaemia unawareness (-0.5 ± 1.4 vs. -0.3 ± 1.4; Δ 0.18, 95% CI -0.21 to 0.57). The likelihood of clinical improvement did not depend on the trial setting (RCT vs. IT: OR 1.18, 95% CI 0.60 to 2.33). The participants with worse glycaemic control (OR 1.40, 95% CI 1.02 to 1.92), hypoglycaemia problems (OR 2.13, 95% CI 1.53 to 2.97) or elevated diabetes distress (OR 1.40, 95% CI 1.03 to 1.89) had a better chance of clinical improvement. The effectiveness of PRIMAS under routine care conditions was comparable to the efficacy demonstrated in the RCT. Clinical improvement was independent of the setting in which PRIMAS was evaluated. The PRIMAS education programme for type 1 diabetes can be delivered under conditions of routine care without a loss of effectiveness, compared to its original evaluation in an RCT.

User satisfaction and ease of use of continuous glucose monitoring (CGM) systems are key factors in patients' device acceptance. CGM user satisfaction is often assessed through questionnaires, but item selection varies widely across studies. The aim of this study was to design, develop and validate a Questionnaire for User Satisfaction Standardized for CGM performance studies (QUSS-CGM). Selection of attributes and design of questionnaire items was based on a systematic literature search of publications on CGM performance evaluation studies. Content and response process validation of a draft-questionnaire was performed by experts (n=9) and people with diabetes (n=10), respectively. The resulting German pre-QUSS-CGM questionnaire underwent validation in two CGM performance studies (\"pilot\" studies) performed between June and August of 2024, via a pooled psychometric evaluation (exploratory factor analysis (EFA) and reliability) of n=126 questionnaires from these studies, followed by bidirectional translation to English. Two hundred and five items on user satisfaction in CGM performance studies were identified by systematic literature search and classified into six attributes according to their content. Items were summarized in a 25-item draft-questionnaire on a 5-point Likert scale. Content and face validity were considered acceptable with a scale-level content validity index (S-CVI/Ave) of 0.90 and a scale-level face validity index (S-FVI/Ave) of 0.93, both based on the average method. EFA revealed a two-factor structure for the final QUSS-CGM questionnaire summarized to 11 items, demonstrating high internal consistency (Cronbach's α of 0.84). The QUSS-CGM was designed, developed, and validated as a reliable and standardized tool to measure user satisfaction in CGM performance evaluation studies.

Aims While depression has been linked to serious adverse outcomes in diabetes, associations with glycemic control are not conclusive. Inconsistencies could be due to the complex symptomatology of depression. Aim of this study was to analyze the associations of depressive subtypes with glycemic control in people with type 1 and type 2 diabetes. Methods Patients completed the Center for Epidemiological Studies-Depression scale which comprises affective, somatic, and anhedonic symptoms. These subtypes were analyzed in a joint linear regression analysis with glycemic control as a dependent variable. Subtype scores were calculated as mean item scores. Separate analyses for people with type 1 and type 2 diabetes were conducted. All analyses were controlled for demographic and medical confounders. Results The sample comprised 604 patients with type 1 and 382 patients with type 2 diabetes. In people with type 1 diabetes, the somatic and affective subtype showed diametrically opposed associations with glycemic control (somatic: β  =+0.23, p  < .05; affective: β  = −0.23, p  < .05). Anhedonia was not significantly associated with glycemic control. In people with type 2 diabetes, none of the depressive subtypes was significantly associated with glycemic control. Conclusions For people with type 1 diabetes, the distinction of subtypes offered a detailed picture of the associations of depressive symptoms with glycemic control. However, due to the cross-sectional design, inferences about the direction of these associations cannot be made. In clinical practice, instead of focusing on overall depression, healthcare providers should examine the nature of depressive symptoms and how they might be related to having diabetes.

IntroductionStudies have shown beneficial effects of real-time continuous glucose monitoring (rtCGM) usage on clinical outcomes. The objective of this analysis was to identify which therapy adjustments were made by people with type 1 diabetes with impaired hypoglycemia awareness during rtCGM usage enabling reductions in the number of low glucose events observed in the HypoDE (Hypoglycemia in Deutschland) study.Research design and methodsIn the multicenter randomized controlled trial in people with type 1 diabetes on multiple daily injections with impaired hypoglycemia awareness, participants recorded their diabetes therapy in 7-day logbooks at baseline and at 6-month follow-up. They used rtCGM or self-monitoring of blood glucose for therapy adjustments. This mechanistic analysis looked at changes in various aspects of therapy.ResultsLogbooks were completed by 70 participants in the rtCGM group and 65 participants in the control group. Participants in the rtCGM group kept their total carbohydrate consumption, daily insulin doses and distribution constant during the study. However, they reported an increased intake of rescue carbohydrates (0.8±0.6 (mean±SD) vs 1.0±0.8 intake/day; baseline-adjusted between-group difference 0.3 intake (0.1–0.5), p=0.031). The glucose threshold at which rescue carbohydrate intake was initiated was elevated from 71±13 mg/dL (3.9±0.7 mmol/L) to 79±14 mg/dL (4.4±0.8 mmol/L) (adjusted between-group difference +7.6 mg/dL (2.4–12.8) (+0.4 mmol/L (0.1–0.7)); p=0.005) in the rtCGM group. Regression analysis showed that follow-up low glucose events were associated with group allocation (p<0.001), low glucose events at baseline (p=0.016) and rescue threshold (p=0.001).ConclusionsNo major adjustments in insulin therapy were made by study participants with impaired hypoglycemia awareness; however, they were more active in preventing hypoglycemia by taking rescue carbohydrates earlier and more often.Trial registration numberNCT02671968.

Background People with diabetes on intensive insulin therapy need sufficient glycaemic control to prevent the onset or progression of diabetic complications. The burden of multiple daily blood glucose self-testing can be lessened by novel diabetes technology like flash glucose monitoring systems which provide more information compared to self-monitoring of blood glucose. Despite this delivered additional information studies are showing no significant effect on HbA 1c reduction, but a reduced time spent in a hypoglycaemic glucose range. We assume that users of these devices need additional education and training to integrate the delivered information into treatment decisions. Therefore, FLASH, an education and treatment programme, was developed. The programme evaluation follows herein. Methods/design Patients are recruited through 40 diabetes outpatient study centres located across Germany. They will be randomly assigned to participate in the education and treatment programme (intervention group) or to obtain treatment as usual (control group). All patients have to give blood samples and to answer a bench of questionnaires during baseline assessment, at the end of the intervention, and 6 months after the end of the intervention. Physicians will be asked to declare some additional clinical data (such as details of the diabetes therapy) for every patient at every one of the three assessment points. Discussion This study is conducted as a randomised controlled trial to test the hypothesis that the newly developed education and treatment programme combined with the use of a flash glucose monitoring device (intervention group) is superior to reduce HbA 1c compared to the use of flash glucose monitoring alone (control group). The first results will be expected in 2018. Trial registration ClinicalTrials.gov, ID: NCT03175315 . Registered on 2 May 2017.