Clinical Research Directory

FSL2 Post Approval Study for Pediatric and Young Adults Patients

This is a prospective, multi-center, non-randomized, single-arm study intended to characterize the safety of the FreeStyle Libre 2 Flash Glucose Monitoring System when used to manage diabetes in pediatric and young adult patient populations.

The Effect Of Color Rotation Technique Training On İnsülin Self-management İn Diabetic Patients.

Diabetes mellitus (DM) is a chronic disease characterized by impaired carbohydrate, protein, and lipid metabolism, resulting from a deficiency of insulin hormone secreted by the pancreas and/or the body's inability to utilize it even when sufficient insulin is secreted. As a frequently observed chronic disease, diabetes is a significant public health problem; if left uncontrolled, it can lead to serious complications and negatively impact quality of life.Individual management of treatment is crucial for successful treatment and glycemic control in diabetes. Due to the complexity of diabetes management related to insulin use, diabetics require greater self-care skills. Nurses play a crucial role in developing desired self-management behaviors in individuals with diabetes, supporting them, and meeting their needs.

Impact of Pilates Exercises on Diabetic Erectile Dysfunction.

Erectile dysfunction (ED) has a prevalence of 52.5% in diabetic male patients, as described in a meta-analysis of 145 studies, including 88,577 men with type 1 and type 2 diabetes. In men, ED can cause sexual dissatisfaction and distress, unsatisfactory relationships, and marital tension

Efficacy of Linaclotide in Type II Diabetics With Chronic Constipation

Study includes 5 visits, when all basic clinical information, vital signs, symptoms, and side effects are going to be assessed at each appointment. Patients are going to be assigned by the computer, to receive an active or non-active drug for 14 days in a first phase. The order will be change during the second phase. The 2 weeks break without our medication will separate these phases. A very close observation regarding safety of our subjects will be implemented by study personnel and clinical investigators.

Effect of Tributyrin Supplementation on Glycemic Control, Inflammation, and Cardiovascular Risk in Patients With Type 2 Diabetes

This study evaluates the effectiveness and safety of tributyrin supplementation in patients with type 2 diabetes mellitus (T2DM) who are at increased risk of cardiovascular disease. Type 2 diabetes is commonly associated with poor blood sugar control, chronic inflammation, oxidative stress, and an increased risk of heart disease. Tributyrin is a dietary supplement that acts as a precursor to butyrate, a compound known for its anti-inflammatory and metabolic benefits. It may help improve blood sugar levels, reduce inflammation, and lower cardiovascular risk. In this randomized, double-blind, controlled clinical trial, participants will receive either tributyrin in addition to their standard diabetes treatment or standard therapy alone. The study will assess whether tributyrin improves glycemic control, inflammation, oxidative stress, lipid profile, and overall cardiovascular risk while maintaining safety and tolerability.

Total Intravenous and Balanced Anesthesia in Diabetic Patients Undergoing Video-Assisted Thoracoscopy

Video-assisted thoracoscopy is a minimally invasive surgical technique used to diagnose and treat problems in chest. Diabetics are more prone to infections, slower wound healing and other complications during and after surgery. Studies suggests that Total Intravenous Anesthesia (TIVA) can lead to a lower increase in blood glucose levels and a better suppression of the stress response compared to balanced anesthesia using inhalational agents like Isoflurane. In the present study we are aiming to compare the effects of Total Intravenous Anesthesia (TIVA) Versus Balanced Anesthesia on blood glucose level in Diabetic Patients undergoing Video-assisted thoracoscopy.

The Impact of Social Worker Referrals on Diabetes and Loneliness

The goal of this clinical trial is to learn if referral to a social worker (social prescribing) can help reduce loneliness and improve blood sugar control (A1C) in older adults with diabetes. It will also help us understand how this approach can support overall well-being in seniors. The main questions it aims to answer are: * Does referral to a social worker reduce feelings of loneliness in older adults with diabetes? * Does this support improve blood sugar control (A1C)? Researchers will compare social worker referral to usual diabetes care to see if this approach improves both social well-being and diabetes outcomes. Participants will: * Be assigned (like flipping a coin) to either meet with a social worker or continue their usual care * Complete a short 3-question loneliness survey at the start and again after 6 months * Have their A1C levels reviewed from their routine medical records

Detection of Diabetic Foot Skin Damage Using Plantar Mechanical Parameters

Diabetes represents one of the major chronic diseases, with diabetic ulcers being a significant adverse prognosis. Approximately 80% of lower limb amputations are attributed to diabetic foot ulcers, which constitute a primary cause of patient disability and mortality, while also imposing a substantial burden on healthcare systems. Although standardized Western medical protocols for diabetic foot management exist, clinical outcomes remain suboptimal. The amputation rate due to diabetic foot ulcers continues to rise annually, underscoring the urgent need for novel and effective interventions to address this condition. Quantitative assessment of cutaneous biomechanical parameters may indirectly reflect the cumulative damage inflicted by diabetes on foot tissues. Such evaluation provides critical guidance for predicting susceptibility to recurrent ulceration and determining the necessity of enhanced offloading strategies to prevent ulcer development. By applying specific mechanical loads to the skin and measuring deformation, rebound characteristics, and displacement dynamics under pressure, it becomes possible to quantitatively evaluate parameters such as elastic modulus and viscoelastic properties. This case-control study aims to investigate the feasibility of utilizing plantar skin quantitative mechanical parameters as objective biomarkers for biomechanical impairment in diabetic foot. Furthermore, it seeks to establish a standardized operating procedure (SOP) for quantitative measurements tailored to diabetic foot scenarios. The study is designed to bridge critical evidence gaps between theoretical consensus and clinically applicable quantitative tools, demonstrating clear innovation and potential clinical value.

AI-Based Diabetic Foot Recurrence Cohort

Diabetic foot ulcer (DFU) is a major adverse outcome of diabetes, which itself is one of the most significant chronic diseases. The recurrence of DFU involves multiple risk factors, including altered foot loading patterns, patient compliance, family care capacity, blood glucose monitoring, degree of ischemia, and systemic disease control. Early identification of recurrence signs and timely follow-up interventions are crucial for improving prognosis, reducing disability rates, and lowering healthcare costs. However, traditional follow-up systems lack individualized strategies-such as risk stratification, inflexible follow-up intervals, and insufficient compliance management-often resulting in suboptimal outcomes. High-risk patients prone to recurrence may not be followed up frequently enough for early detection, while low-risk patients may undergo unnecessary visits, increasing burdens on both patients and healthcare providers. This inefficiency contributes significantly to the persistently high rates of disability and mortality among recurrent DFU patients. Establishing an individualized follow-up strategy for DFU, supported by advanced technology to address core bottlenecks such as delayed recurrence warnings and inadequate home-based management, represents an effective technical pathway to tackle these issues. Our center proposes to develop a dedicated DFU cohort with comprehensive active follow-up and a multimodal database encompassing well-defined indicators. We aim to explore a high-risk foot grading system for preventing DFU recurrence and design targeted follow-up protocols. By leveraging AI technology, we intend to build a wound warning system capable of identifying DFU recurrence. Furthermore, we seek to establish a telemedicine and AI-assisted, patient-centered home-based self-management framework for early warning and prevention of DFU recurrence.

"Erectile Function After PCI in MI and Non-MI Patients"

The goal of this observational study is to assess changes in patients' erectile function after percutaneous coronary intervention (PCI) using a standard IIEF (International Index of Erectile Function) questionnaire at 1, 3, and 6 months post-PCI. By doing this, we try to compare patients' responses to PCI after having a heart attack and stable angina to see the real effect of myocardial infarction on erectile function status in the long term by comparing it with a very similar group.

Assessing the Effectiveness of Large Language Model (LLM)-Enabled Nurse Treatment Planning in 2 Indian Districts

The goal of this clinical trial is to learn whether AI-enabled, nurse-led treatment planning can improve the quality of clinical reasoning and management compared with standard physician-led care in adult primary care patients (≥18 years) presenting with hypertension, diabetes mellitus, fever, breathlessness, or musculoskeletal pain in rural and semi-urban India. The main questions it aims to answer are: * Does a nurse + large language model (LLM) consultation achieve non-inferior clinical quality scores compared with a standard doctor consultation? * Is AI-assisted nurse-led care acceptable and satisfactory to patients in primary healthcare settings? Researchers will compare nurse + LLM-led consultations with physician-led standard-of-care consultations within the same participant to see if the AI-enabled nurse model delivers comparable or improved clinical reasoning and treatment planning. Participants will: * Receive two sequential consultations for the same visit (one with a nurse using an AI tool and one with a physician, order randomized). * Have both consultations audio recorded for blinded clinical quality assessment. * Complete a brief exit survey on communication, trust, and satisfaction after the AI-assisted nurse consultation.

Telemedicine-Based Behavioral Intervention to Improve Outcomes Among Diabetic Patients

The goal of this quasi-experimental clinical study is to learn whether a telemedicine-based behavioral intervention can improve health outcomes among adult patients with diabetes receiving care at tertiary hospitals in Northwest Amhara, Ethiopia. The main questions it aims to answer are: * Does a telemedicine-based behavioral intervention improve glycemic control (HbA1c) among diabetic patients? * Does the intervention improve medication adherence among diabetic patients? * Does the intervention improve diabetes self-care practices? * Does the intervention increase patients' knowledge about diabetes? * Does the intervention reduce hospital admissions among diabetic patients? We will compare patients who receive telemedicine-based counseling with patients who receive usual care to see if the intervention improves glycemic control, medication adherence, self-care practices, diabetes knowledge, and reduces hospital admissions. Participants will: * Receive structured telephone-based education every two weeks for three months (intervention group only) * Participate in 30-50-minute counseling sessions during the first call and 15-30 Minutes sessions during subsequent calls (intervention group only) * Receive education on diabetes basics, nutrition and meal planning, physical activity, medication management, blood glucose monitoring, complication prevention, and psychosocial support (intervention group only) * Engage in interactive discussions and receive individualized guidance from trained nurses (intervention group only) * Continue routine diabetes care at the hospital (both groups)

Clinical Efficacy of Implementing an AI-SaMD for Funduscopy Analysis in Patients With Diabetes

The objective of this study is to investigate the efficacy of implementing the AI-SaMD(VUNO Med®-Fundus AI™) alongside routine clinical practice for the detection of diabetic retinopathy.

Gemini Study: A Prospective, Multicenter Evaluation of Performance and Safety of the Eversense Gemini System With Flash Glucose Measurement Feature

A prospective, multicenter evaluation of performance and safety of the Eversense Gemini System with flash glucose measurement feature. The purpose of this clinical investigation is to evaluate the accuracy of the Gemini System with new technological flash glucose monitoring (FGM) feature enhancements compared to reference glucose measurements and the Eversense 365 CGM System. The investigation will also evaluate safety of the Gemini System usage.

Effects of Selected Statins on Blood Glucose Levels in Healthy Volunteers

This Phase I randomized clinical trial aims to investigate the short-term effects of three commonly prescribed statins (atorvastatin, rosuvastatin, and simvastatin) at different dose levels on blood glucose homeostasis in healthy volunteers. The study will assess changes in fasting blood glucose, insulin, and C-peptide levels following two days of statin administration under controlled conditions. The research seeks to provide comparative data on the potential diabetogenic effects of these medications.

Duodenal ReCET as an Early Treatment for Type 2 DM

This study is designed to evaluate the efficacy and safety of endoscopic duodenal re-cellularization therapy in individuals with in patients with a recent diagnosis of type 2 diabetes mellitus (T2DM).

The Role of Inflammatory Biomarkers in Preventing Deep Sternal Wound Infections After Sternotomy

The goal of this observational study is to reveal blood biomarkers that will have prognostic significance in terms of the development of deep wound infection following sternotomy. As for the practical significance of the study, blood biomarkers correlated with deep wound infections can be used to prevent the development of wound infections in the postoperative period. Based on this, it is possible to formulate an algorithm for preventive measures.

Assessment of Antithyroglobulin Antibody Levels Among Diabetic Patients

Assessment of antithyroglobulin antibody (anti Tg) level among diabetic patients explores the intersection between autoimmune thyroid disease and diabetes mellitus. Autoimmune thyroiditis and diabetes frequently coexist, and anti Tg is one of the main markers used to document thyroid autoimmunity.(1,2) Thyroglobulin is a large iodinated glycoprotein produced by thyroid and serves as the precursor for thyroid hormone synthesis. Damage to thyroid tissue in autoimmune thyroiditis leads to production of autoantibodies against thyroglobulin (Tg)(1,3). Anti Tg is therefore considered serologic hallmarks of autoimmune thyroiditis. The presence of this antibody may also be used to monitor thyroid damage progression and predict the development of overt hypothyroidism in at risk populations(1,3). Type 1 diabetes mellitus (T1DM) is an organ specific autoimmune. Because of shared genetic susceptibility and overlapping immune mechanisms, patients with T1DM have a markedly increased prevalence of autoimmune thyroiditis compared with the general population. International guidelines support routine screening for thyroid autoantibodies and thyroid function in T1DM to enable early detection of subclinical thyroid dysfunction(2,4). . A study reported that, among 60 T1DM patients without known thyroid disease, 16.7% were positive for anti Tg, and subclinical or overt hypothyroidism was present in a substantial fraction of this antibody positive individuals. Other series similarly show that thyroid autoantibodies are common in T1DM and that their presence predicts later thyroid dysfunction. (5,6). Increasing evidence indicates that type 2 diabetes mellitus (T2DM) is also associated with a higher prevalence of thyroid autoantibodies than nondiabetic controls in many studies(1,7). In a study including 72 T2DM patients, 20.8% had either anti TPO or anti Tg positivity, and 8.3% had isolated anti Tg antibodies, with rates comparable to or higher than those reported in regional control populations. A study of female T2DM patients found anti Tg in 61.3% of cases compared with no positives in the control group, and more than half of hypothyroid diabetic patients had anti Tg positivity, suggesting a significant autoimmune contribution to thyroid dysfunction in some T2DM cohorts. (2,8). Autoimmune clustering means that diabetic patients, are predisposed to additional organ specific autoimmune diseases, including autoimmune thyroiditis. Screening for anti Tg provides a more complete picture of thyroid autoimmunity. (2,8)

Targeting Neurovascular Coupling in Cognitive Decline Via Nitrate-Based Supplementation

Diet is established among the most relevant adjustable variables of human health in modern societies. The recognition by the World Health Organization of cognitive impairment and dementia associated with aging as one of the major public health challenges of our time, highlights the imperative need for a more comprehensive understanding of how different aspects of lifestyle, in particular diet, affect neural function and consequent cognitive performance throughout lifespan. The brain is endowed with fine mechanisms for a precise spatial and temporal control of cerebral blood flow (CBF) according to neural activity, the neurovascular coupling (NVC). Mounting evidence from preclinical and human studies demonstrate that NVC dysfunction is a key early factor contributing to the pathogenesis of cognitive decline and vascular cognitive impairment (VCI) in aging and conditions associated with accelerated microvascular aging, such as cerebral small vessel disease (cSVD). Failure at any part of the NVC pathway disrupts CBF resulting in catastrophic depletion of oxygenation and energy supply to brain cells, and, in the long run, to neuronal dysfunction and cognitive impairment. The investigators have shown that nitric oxide (NO) synthesized by neuronal nitric oxide synthase (nNOS) is a direct mediator of NVC and that decreased bioavailability of NO along aging compromised NVC and reduced local CBF. Shortly after the identification of nNOS as a source of NO for vasodilation in the brain, an alternative pathway for NO production independent of nNOS, relying on the sequential reduction of nitrate, the nitrate:nitrite:NO pathway, was unveiled. Nitrate consumed in green leafy vegetables as part of a normal diet is bioactivated to nitrite and both compounds are permanent constituents of blood/tissues in animal species, influencing CBF and resulting in improvements in learning and memory in rodents and VCI patients. However, a critical question remains on whether NO produced from nitrite is functionally linked to neuronal activation. This is key to understanding whether dietary nitrate can be linked to neuronal-dependent CBF increases and cognitive performance. The investigators and others have shown that upon excitatory stimulation, ascorbate is released from neurons being available for nitrite reduction and our preliminary data supports that NO bioavailability and CBF might be maintained independently of nNOS by the reduction of nitrite to NO in the brain extracellular space upon neuronal activation (unpublish data). This innovative mechanism functionally links the production of NO from nitrite to neuronal activation, triggering CBF increases and maintaining an operative NVC. A further facet is that, bridging diet and cognitive performance, this mechanism incorporates modulatory elements which is open to adjustment by diet via nitrate. Thus, in this pilot trial a proof of concept study will be conducted to investigate the clinical impact of a dietary nitrate supplementation intervention in a clinical population with VCI due to small vessel disease, as measured by changes on NVC and cognitive performance. The investigators hypothesise that functional NVC is maintained operative in VCI patients by increasing NO bioavailability in the extracellular space of the brain through a nitrate -rich diet that, in turn, supports an adequate CBF in response to neuronal activation, modulating the molecular mechanisms and cognitive performance of disease-related physiological and cognitive markers.

Efficacy of Placental Membrane Dressings in Accelerating Diabetic Foot Healing

Evaluation of Efficacy of Placental Membrane Dressings in Accelerating Diabetic Foot Healing

Multicenter Study on Cardiovascular and Metabolic Complications in Patients With Biochemically Silent Pheochromocytomas and Paragangliomas

The aim of the study is to characterise the cardiovascular and metabolic complications pre- and post-surgery of patients with biochemically negative PPGL and to compare them with normal individuals and patients with secreting PPGLs age and sex matched.

Prediction Model for the Risk of Developing Foot Ulcers in Diabetes

Introduction Foot ulcers in diabetes mellitus (DM) are a common and serious complication that can lead to infection, amputation, and increased mortality. Early identification of patients at high risk is crucial in order to implement preventive measures at an early stage. The number of people with DM is increasing globally, from 540 million in 2021 to an estimated 780 million by 2045. Foot ulcers cause considerable suffering for the individual and entail substantial costs for the healthcare system. Despite national guidelines recommending regular, structured foot examinations and risk classification to assess the risk of developing foot ulcers, current risk models do not take into account the complex interactions between risk factors and socioeconomic factors such as marital status, level of education, and place of residence. Data-driven advances and artificial intelligence (AI) offer new opportunities to refine risk identification, but their use in predicting the risk of diabetic foot ulcers remains limited. The need for foot screening is considerable. In Sweden, there are approximately 600,000 patients with DM, and half of them live with an increased risk due to nerve damage in the feet. This means that, based on risk level, around 300,000 patients in Sweden may require preventive interventions, including medical foot care, customised footwear, and access to specialist care for those with foot ulcers. Improved preventive efforts are emphasised in the person-centred and integrated care pathway for people with diabetes at high risk of foot ulcers. However, accurate identification of foot ulcer risk is currently lacking. Prevention leads not only to good quality of life for the individual but also to reduced healthcare costs. Estimates by Ragnarsson Tennvall show that a hard-to-heal ulcer costs approximately SEK 100,000 per year, while an amputation costs around SEK 300,000-500,000. Given a prevalence of foot ulcers of 5% among patients with diabetes, the annual cost of ulcer care amounts to SEK 3 billion. In addition, there are costs of approximately SEK 750 million for amputations, according to data from the quality register SwedAmp. The aim of the study is to develop, test, and validate prediction models (statistical and AI-based) to identify patients with DM who are at risk of developing foot ulcers. The models will be based on retrospective electronic health record data from primary care in the Västra Götaland Region (VGR), as well as data from Statistics Sweden (SCB) concerning demographic factors such as marital status, level of education, occupation, and place of residence. Methods The study has two methodological approaches: AI-based modelling and statistical modelling. AI-based approach Machine learning models will be developed to predict patients at risk of developing diabetic foot ulcers. The models will be trained using cross-validation on a large dataset in which variables will be iteratively excluded. Conformal prediction will be used to quantify uncertainty in patient-level predictions. The resulting models will be analysed to identify the strongest predictors and will be compared with classical statistical modelling and findings from the literature. Steps in AI modelling: Data extraction: Electronic health record data from primary care in VGR, supplemented with sociodemographic data from SCB. Data processing: Use of, among other variables, diagnostic codes (ICD-10), healthcare interventions (KVÅ codes), visit types, visit frequency, ECG parameters, and free-text data to construct predictors. Model development: Prediction models will be developed and trained using cross-validation. Measures of uncertainty will be generated using conformal prediction. Validation: A separate cohort will be used to test model performance (sensitivity, specificity, positive predictive value \[PPV\]). Interpretation: The models will be reviewed for transparency and clinical interpretability in collaboration with patient representatives, clinicians, and researchers. The results of the statistical and AI-based models will be compared with regard to their respective strengths and weaknesses. Statistical modelling Two populations will be analysed: patients with diabetes without foot ulcers and patients with diabetes with foot ulcers. Co-variation and causal relationships between risk factors and foot ulcers will be identified. A model describing causal pathways leading to ulcer development will be developed, and its certainty and uncertainty will be analysed.

Neurophysiological, Autonomic, and Sonographic Assessment of Diabetic Peripheral Neuropathy

Diabetic peripheral neuropathy causes pain, sensory loss, and foot risk; multimodal assessment enables earlier diagnosis and improved patient management.

"Smart Family Doctor" Assisted Comprehensive Management of Secondary Prevention Among Post Revascularization Patients

This study aims to evaluate the effect of an AI-assisted "Smart family doctor" digital health management tool on improving the control rates of hypertension, diabetes, and dyslipidemia in post-revascularization patients. A randomized controlled trial design will be used, involving approximately 10-20 hospitals and 951 participants. Eligible participants are adults aged between 18 and 80 years, post-CABG or post-PCI patients with hypertension, diabetes, and dyslipidemia.