ABSTRACT
The study aims to develop a system for insulin titration in type 2 diabetes to assist primary healthcare providers. Usability testing with end-users is ongoing.
Subject(s)
Diabetes Mellitus, Type 2 , Diabetes Mellitus, Type 2/drug therapy , Humans , Insulin/administration & dosage , Insulin/therapeutic use , Hypoglycemic Agents/therapeutic use , Hypoglycemic Agents/administration & dosage , Drug Therapy, Computer-AssistedABSTRACT
Protocol for a three-arm randomized controlled trial investigating telemonitoring with decision support in insulin-treated people with type 2 diabetes.
Subject(s)
Diabetes Mellitus, Type 2 , Insulin , Telemedicine , Humans , Diabetes Mellitus, Type 2/drug therapy , Insulin/therapeutic use , Blood Glucose Self-Monitoring , Hypoglycemic Agents/therapeutic use , Decision Support Systems, ClinicalABSTRACT
Collaborative care interventions have been proposed as a promising strategy for the management of patients with multimorbidity. This systematic review and meta-analysis aims to assess the effectiveness of collaborative care interventions for adult patients with multimorbidity. Furthermore, a meta-regression analysis is planned to determine if certain participant or intervention characteristics can explain variance in effect.
Subject(s)
Multimorbidity , Systematic Reviews as Topic , Humans , Meta-Analysis as Topic , Cooperative BehaviorABSTRACT
The increased utilization of continuous glucose monitors (CGM) and smart insulin pens (SIP) among people with type 2 diabetes generates significant health data. This study explored possible patterns in long term CGM and SIP data.
Subject(s)
Blood Glucose Self-Monitoring , Diabetes Mellitus, Type 2 , Insulin Infusion Systems , Insulin , Humans , Diabetes Mellitus, Type 2/blood , Diabetes Mellitus, Type 2/drug therapy , Insulin/therapeutic use , Blood Glucose/analysis , Hypoglycemic Agents/therapeutic useABSTRACT
INTRODUCTION: Basal insulin non-adherence is a challenge in people with type 2 diabetes (T2D). METHODS: Using injection data recorded by a connected insulin pen, we employed a novel three-step methodology to assess three aspects of adherence (overall adherence, adherence distribution, and dose deviation) in individuals with insulin-treated T2D undergoing telemonitoring. RESULTS: Among participants, 52% were considered overall adherent. However, deviations from the recommended dose were observed in all participants, with increased and reduced doses being the predominant forms of non-adherence. CONCLUSIONS: Our study underscores the prevalence of basal insulin dosing irregularities in individuals with insulin-treated T2D undergoing telemonitoring.
Subject(s)
Diabetes Mellitus, Type 2 , Insulin , Medication Adherence , Diabetes Mellitus, Type 2/drug therapy , Humans , Insulin/therapeutic use , Insulin/administration & dosage , Hypoglycemic Agents/therapeutic use , Hypoglycemic Agents/administration & dosage , Male , Middle Aged , Female , Telemedicine , AgedABSTRACT
Pulmonary Disease (COPD) exacerbations. However, the effect of telehealth for COPD remains uncertain, which may be due to a lack of attention to usability during the development of telehealth solutions. The aim was to evaluate the usability of a telehealth system for COPD using the Danish Telehealth Usability Questionnaire. A total of 96 people with COPD, who were already using a telehealth system consisting of weekly measurements of physiological parameters and symptom-related questionnaires, were included. The D-TUQ was used to assess the usability of the telehealth system. The overall experience with the usability of the telehealth system was mainly positive, but there was room for improvement.
Subject(s)
Pulmonary Disease, Chronic Obstructive , Telemedicine , Pulmonary Disease, Chronic Obstructive/therapy , Humans , Cross-Sectional Studies , Male , Female , Denmark , Aged , Middle Aged , Surveys and Questionnaires , Patient SatisfactionABSTRACT
OBJECTIVE: This study aims to investigate the continuum of glucose control from normoglycemia to dysglycemia (HbA1c ≥ 5.7% / 39 mmol/mol) using metrics derived from Continuous Glucose Monitoring (CGM). Additionally, we aim to develop a machine learning-based classification model to classify dysglycemia based on observed patterns. METHODS: Data from five distinct studies, each featuring at least two days of CGM, were pooled. Participants included individuals classified as healthy, with prediabetes, or with type 2 diabetes mellitus (T2DM). Various CGM indices were extracted and compared across groups. The dataset was split 70/30 for training and testing two classification models (XGBoost / Logistic Regression) to differentiate between prediabetes or dysglycemia and the healthy group. RESULTS: The analysis included 836 participants (healthy: n=282; prediabetes: n=133; T2DM: n=432). Across all CGM indices, a progressive shift was observed from the healthy group to those with diabetes (p<0.001). Statistically significant differences (p<0.01) were noted in mean glucose, Time Below Range, Time Above 140 mg/dl, Mmobility, Multiscale Complexity Index and Glycemic Risk Index when transitioning from health to prediabetes. The XGBoost models achieved the highest Receiver Operating Characteristic Area Under the Curve (ROC-AUC) values on the test dataset ranging from 0.91 [CI: 0.87-0.95] (prediabetes identification) to 0.97 [CI: 0.95-0.98] (Dysglycemia identification). CONCLUSION: Our findings demonstrate a gradual deterioration of glucose homeostasis and increased glycemic variability across the spectrum from normo- to dysglycemia, as evidenced by CGM metrics. The performance of CGM-based indices in classifying healthy individuals and those with prediabetes and diabetes is promising.
ABSTRACT
BACKGROUND: Collaborative care interventions have been proposed as a promising strategy to support patients with multimorbidity. Despite this, the effectiveness of collaborative care interventions requires further evaluation. Existing systematic reviews describing the effectiveness of collaborative care interventions in multimorbidity management tend to focus on specific interventions, patient subgroups, and settings. This necessitates a comprehensive review that will provide an overview of the effectiveness of collaborative care interventions for adult patients with multimorbidity. OBJECTIVE: This systematic review aims to systematically assess the effectiveness of collaborative care interventions in comparison to usual care concerning health-related quality of life (HRQoL), mental health, and mortality among adult patients with multimorbidity. METHODS: Randomized controlled trials evaluating collaborative care interventions designed for adult patients (18 years and older) with multimorbidity compared with usual care will be considered for inclusion in this review. HRQoL will be the primary outcome. Mortality and mental health outcomes such as rating scales for anxiety and depression will serve as secondary outcomes. The systematic search will be conducted in the CENTRAL, PubMed, CINAHL, and Embase databases. Additional reference and citation searches will be performed in Google Scholar, Web of Science, and Scopus. Data extraction will be comprehensive and include information about participant characteristics, study design, intervention details, and main outcomes. Included studies will be assessed for limitations according to the Cochrane Risk of Bias tool. Meta-analysis will be conducted to estimate the pooled effect size. Meta-regression or subgroup analysis will be undertaken to explore if certain factors can explain the variation in effect between studies, if feasible. The certainty of evidence will be evaluated using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) approach. RESULTS: The preliminary literature search was performed on February 16, 2024, and yielded 5255 unique records. A follow-up search will be performed across all databases before submission. The findings will be presented in forest plots, a summary of findings table, and in narrative format. This systematic review is expected to be completed by late 2024. CONCLUSIONS: This review will provide an overview of pooled estimates of treatment effects across HRQoL, mental health, and mortality from randomized controlled trials evaluating collaborative care interventions for adults with multimorbidity. Furthermore, the intention is to clarify the participant, intervention, or study characteristics that may influence the effect of the interventions. This review is expected to provide valuable insights for researchers, clinicians, and other decision-makers about the effectiveness of collaborative care interventions targeting adult patients with multimorbidity. TRIAL REGISTRATION: International Prospective Register of Systematic Reviews (PROSPERO) CRD42024512554; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=512554. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58296.
Subject(s)
Meta-Analysis as Topic , Multimorbidity , Systematic Reviews as Topic , Humans , Quality of Life , Regression Analysis , Cooperative Behavior , Randomized Controlled Trials as TopicABSTRACT
BACKGROUND: While health care providers (HCPs) are generally aware of the challenges concerning insulin adherence in adults with insulin-treated type 2 diabetes (T2D), data guiding identification of insulin nonadherence and understanding of injection patterns have been limited. Hence, the aim of this study was to examine detailed injection data and provide methods for assessing different aspects of basal insulin adherence. METHOD: Basal insulin data recorded by a connected insulin pen and prescribed doses were collected from 103 insulin-treated patients (aged ≥18 years) with T2D from an ongoing clinical trial (NCT04981808). We categorized the data and analyzed distributions of correct doses, increased doses, reduced doses, and missed doses to quantify adherence. We developed a three-step model evaluating three aspects of adherence (overall adherence, adherence distribution, and dose deviation) offering HCPs a comprehensive assessment approach. RESULTS: We used data from a connected insulin pen to exemplify the use of the three-step model to evaluate overall, adherence, adherence distribution, and dose deviation using patient cases. CONCLUSION: The methodology provides HCPs with detailed access to previously limited clinical data on insulin administration, making it possible to identify specific nonadherence behavior which will guide patient-HCP discussions and potentially provide valuable insights for tailoring the most appropriate forms of support.