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BACKGROUND: Comorbidities such as cardiovascular disease (CVD) and diabetic kidney disease (DKD) are major burdens of type 1 diabetes (T1D). Predicting people at high risk of developing comorbidities would enable early intervention. This study aimed to develop models incorporating socioeconomic status (SES) to predict CVD, DKD, and mortality in adults with T1D to improve early identification of comorbidities. METHODS: Nationwide Danish registry data were used. Logistic regression models were developed to predict the development of CVD, DKD, and mortality within five years of T1D diagnosis. Features included age, sex, personal income, and education. Performance was evaluated by five-fold cross-validation with area under the receiver operating characteristic curve (AUROC) and the precision-recall area under the curve (PR-AUC). The importance of SES was assessed from feature importance plots. RESULTS: Of the 6572 included adults (≥21 years) with T1D, 379 (6%) developed CVD, 668 (10%) developed DKD, and 921 (14%) died within the five-year follow-up. The AUROC (±SD) was 0.79 (±0.03) for CVD, 0.61 (±0.03) for DKD, and 0.87 (±0.01) for mortality. The PR-AUC was 0.18 (±0.01), 0.15 (±0.03), and 0.49 (±0.02), respectively. Based on feature importance plots, SES was the most important feature in the DKD model but had minimal impact on models for CVD and mortality. CONCLUSIONS: The developed models showed good performance for predicting CVD and mortality, suggesting they could help in the early identification of these outcomes in individuals with T1D. The importance of SES in individual prediction within diabetes remains uncertain.
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BACKGROUND: The prevalence of diabetes and coexisting multimorbidity rises worldwide. Treatment of this patient group can be complex. Providing an evidence-based, coherent, and patient-centred treatment of patients with multimorbidity poses a challenge in healthcare systems, which are typically designed to deliver disease-specific care. We propose an intervention comprising multidisciplinary team conferences (MDTs) to address this issue. The MDT consists of medical specialists in five different specialities meeting to discuss multimorbid diabetes patients. This protocol describes a feasibility test of MDTs designed to coordinate care and improve quality of life for people with diabetes and multimorbidity. METHODS: A mixed-methods one-arm feasibility test of the MDT. Feasibility will be assessed through prospectively collected data. We will explore patient perspectives through patient-reported outcomes (PROs) and assess the feasibility of electronic questionnaires. Feasibility outcomes are recruitment, PRO completion, technical difficulties, impact of MDT, and doctor preparation time. During 17 months, up to 112 participants will be recruited. We will report results narratively and by the use of descriptive statistics. The collected data will form the basis for a future large-scale randomised trial. DISCUSSION: A multidisciplinary approach focusing on better management of diabetic patients suffering from multimorbidity may improve functional status, quality of life, and health outcomes. Multimorbidity and diabetes are highly prevalent in our healthcare system, but we lack a solid evidence-based approach to patient-centred care for these patients. This study represents the initial steps towards building such evidence. The concept can be efficiency tested in a randomised setting, if found feasible to intervention providers and receivers. If not, we will have gained experience on how to manage diabetes and multimorbidity as well as organisational aspects, which together may generate hypotheses for research on how to handle multimorbidity in the future. ADMINISTRATIVE INFORMATION: Protocol version: 01 TRIAL REGISTRATION: NCT05913726 - registration date: 21 June 2023.
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Background: Multidisciplinary Teams (MDTs) has been suggested as an intervention to overcome some of the complexities experienced by people with diabetes and comorbidities in terms of diagnosis and treatment. However, evidence concerning MDTs within the diabetes field remains sparse. Objective: This review aims to identify and map available evidence on key characteristics of MDTs in the context of diagnosis and treatment in people with diabetes and comorbidities. Methods: This review followed the PRISMA-ScR guidelines. Databases PubMed, EMBASE, and CINAHL were systematically searched for studies assessing any type of MDT within the context of diagnosis and treatment in adult people (≥ 18 years) with diabetes and comorbidities/complications. Data extraction included details on study characteristics, MDT interventions, digital health solutions, and key findings. Results: Overall, 19 studies were included. Generally, the MDTs were characterized by high heterogeneity. Four overall components characterized the MDTs: Both medical specialists and healthcare professionals (HCPs) of different team sizes were represented; interventions spanned elements of medication, assessment, nutrition, education, self-monitoring, and treatment adjustment; digital health solutions were integrated in 58% of the studies; MDTs were carried out in both primary and secondary healthcare settings with varying frequencies. Generally, the effectiveness of the MDTs was positive across different outcomes. Conclusions: MDTs are characterized by high diversity in their outline yet seem to be effective and cost-effective in the context of diagnosis and treatment of people with diabetes and comorbidities. Future research should investigate the cross-sectorial collaboration to reduce care fragmentation and enhance care coordination.
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BACKGROUND: Few studies have investigated the underlying mechanisms for unilateral subacromial pain syndrome (SAPS). Therefore, this study examined (1) if 8-weeks of exercise could modulate clinical pain or temporal summation of pain (TSP), conditioned pain modulation (CPM), and exercise-induced hypoalgesia (EIH) and (2) if any of these parameters could predict the effect of 8-weeks of exercise in patients with unilateral SAPS. METHODS: Thirty-seven patients completed a progressive abduction exercise program every other day for 8-weeks. Worst shoulder pain in full abduction was rated on a numeric rating scale (NRS). Pain pressure thresholds (PPTs), TSP, CPM, EIH, Shoulder Pain and Disability Index (SPADI), Pain Catastrophizing Scale (PCS), PainDETECT questionnaire (PD-Q), Pain Self-Efficacy Questionnaire (PSE-Q) and Pittsburgh Sleep Quality Index (PSQI) were assessed before and after intervention. RESULTS: The intervention improved worst pain intensity (p < 0.001), increased the CPM (p < 0.001), improved the sleep scores (p < 0.005) and reduced the PainDETECT ratings (p < 0.001). No changes were observed in PPT, TSP, EIH, SPADI, PCS and PSE-Q (all p > 0.05). In a linear regression, the combination of all baseline parameters predicted 23.2% variance in absolute change in pain after 8 weeks. Applying backwards elimination to the linear regression yielded that baseline pain intensity combined with TSP predicted 33.8% variance. CONCLUSION: This explorative study suggested reduction in pain, improved sleep quality and increased CPM after 8-weeks of exercise. Furthermore, the results suggests that low pain intensity and high TSP scores (indicative for pain sensitisation) may predict a lack of pain improvement after exercise.