There are about 21062 clinical studies being (or have been) conducted in Italy. The country of the clinical trial is determined by the location of where the clinical research is being studied. Most studies are often held in multiple locations & countries.
This clinical trial aims to assess the efficacy of Optical Coherence Tomography (OCT) in the early diagnosis of oral cancer. It focuses on Oral Potentially Malignant Disorders (OPMDs) as precursors to Oral Squamous Cell Carcinoma (OSCC). Despite the availability of oral screening, diagnostic delays persist, underscoring the importance of exploring non-invasive methodologies. The OCT technology provides cross-sectional analysis of biological tissues, enabling a detailed evaluation of ultrastructural oral mucosal features. The trial aims to compare OCT preliminary evaluation with traditional histology, considered the gold standard in oral lesion diagnosing. It seeks to create a database of pathological OCT data, facilitating the non invasive identification of carcinogenic processes. The goal is to develop a diagnostic algorithm based on OCT, enhancing its ability to detect characteristic patterns such as the keratinized layer, squamous epithelium, basement membrane, and lamina propria in oral tissues affected by OPMDs and OSCC. Furthermore, the trial aims to implement Artificial Intelligence (AI) in OCT image analysis. The use of machine learning algorithms could contribute to a faster and more accurate assessment of images, aiding in early diagnosis. The trial aims to standardize the comparison between in vivo OCT images and histological analysis, adopting a site-specific approach in biopsies to improve correspondence between data collected by both methods. In summary, the trial not only evaluates OCT as a diagnostic tool but also aims to integrate AI to develop a standardized approach that enhances the accuracy of oral cancer diagnosis, providing a significant contribution to clinical practice.
This is a pre-marketing, single-centre, prospective clinical trial with the aim of comparison the effectiveness and safety of the SOUNDI medical device compared to polysomnography in detecting parameters for the diagnosis of obstructive sleep apnea (OSA) syndrome in subjects with suspected diagnosis of sleep disorders.
The aim of the present study was to evaluate the efficacy of preoperative low-residue diet on postoperative ileus in women undergoing elective cesarean section. It is a surgeon-blind, randomized controlled trial enrolling pregnant women at ≥39 weeks of gestation undergoing elective cesarean section. Patients were preoperatively randomized to receive either low-residue diet (arm A) or free diet (arm B) starting from three days before surgery. The primary outcome was the postoperative ileus at 24 hours after surgery. The secondary outcomes were the postoperative pain (assessed through VAS scale), the quality of the surgical field (scored using a 5-point scale, from poor to excellent), postoperative complications, and the length of hospital stay. Perioperative data were collected and compared between groups.
Low-dose computed tomography (LDCT) lung cancer (LC) screening can reduce mortality among heavy smokers, but there is a critical need to better identify people at higher risk and to reduce harms related to management of benign nodules. The most promising strategy is to combine novel tools to optimize clinical decisions and increase the benefit of screening. In this respect, the investigators already demonstrated that the combination of baseline LDCT features with a minimal invasive microRNA blood test was able to more precisely estimate the individual risk of developing LC. The investigators posit that additional immune-related and radiologic features can be integrated with the help of artificial intelligence (AI) to further implement LDCT screening strategies. The project will answer whether the combination of (bio)markers of different origin can predict LC development at baseline and over time, indicate which screen-detected lung nodules are likely to be malignant and ultimately reduce LC and all cause mortality.
Ageing is characterised by a change in body composition with a parallel decrease in muscle mass and an increase and central redistribution of fat. When drastically exacerbated, these two processes culminate in a condition known as sarcopenic obesity (SO). SO is characterised by the coexistence of obesity and sarcopenia (i.e. reduced muscle mass and function) and is a growing public health problem in the elderly. The health risks of obesity and sarcopenia act synergistically, maximising the risk of disability of OS. The molecular mechanisms underlying OS are largely unknown. Increased fat mass induces chronic systemic inflammation and alters the profiles of adipokines and hormones, promoting the development of sarcopenia. On the other hand, the reduction in muscle tissue (SM) typical of sarcopenia is characterised by an alteration in the metabolic properties of skeletal muscle with an increase in insulin resistance and a reduction in energy expenditure that favours the accumulation and dysfunction of adipose tissue (AT). The cellular alterations that would seem to underlie OS are: altered autophagy, cellular senescence, epigenetic and mitochondrial alterations and maladaptive activation of intra- and intercellular inflammatory circuits (e.g. cytokines, extracellular vesicles, dysfunctional circulating leukocytes). However, the interconnections between these mechanisms are still unclear. The impact of OS can be dramatic on the health and quality of life of those affected. Therefore, the identification of early biomarkers that can recognise overweight and obese individuals at risk of developing SO is of paramount importance. This would shed light on the heterogeneity of an otherwise homogeneous clinical condition, opening new horizons towards the conscious design of more personalised therapeutic strategies, allowing a more rational use of the limited resources available for the growing elderly population. The study design designed to achieve this aim is a cross-sectional observational study with an additional multicentre procedure lasting two years.
The goal of this observational study is to train a machine learning system based on data from patients affected by spontaneous Intracranial Hemorrage. The main question it aims to answer is whether there is a correlation between actual clinical pratice, reached outcomes and favorable or unfavorable predictive factors, and anamnesis. Participants will be treated as per standard clinical practice.
To optimize the effectiveness of asthma therapy there is a need to identify and address individual patient goals. Considering the self-management discussion as central for the achievement of health outcomes, Healthcare Providers may help patients make specific actions to obtain their desired goals. The current evidence suggest that Healthcare Professionals need to develop a more patient-centered and partnership-based approach based on the development and review of action plans, including the experiential asthma knowledge of patients and caregivers. From a practical perspective, the specialist (i.e. pulmunologists, allergologists, etc) has clear therapeutic targets to be reached in asthmatic patients: for example, improving the disease control, the spirometric values and asthma control test (ACT) score vs. pre-treatment evaluations represent the standard outcomes to reach (GINA 2019). However, as previously described, patients are more likely to achieve an improved clinical outcome when the treatment is driven by a personalized goal. This builds on the same principle as shared decision making between the physician and patient, recognizing both the personal motivation and the accountability on behalf of the patient (Hoskins et al. 2016). This study aims to evaluate if the identification of a personalized outcome allows patients to achieve a better control of asthma in terms of asthma control test (ACT) and asthma quality of life questionnaire (AQLQ). In addition, a set of clinical outcomes (i.e. forced expiratory volume in one second - FEV1, use of rescue therapy, night awakeness) will also be assessed.
Spatial navigation skills are very important in everyday activities and quality of life but spatial navigation abilities are not part of the standard process of assessment and rehabilitation of patients. Furthermore, it is known that children with cerebral palsy have impaired visuo-spatial competences. The main objective of this study is to evaluate and compare the spatial navigation abilities of typically developing children and of children with cerebral palsy using the "StarMaze" application delivered by means of a Head Mounted Display (HMD). The second aim is to investigate the user experience during the session. A similar application was already developed and tested in a virtual reality large scale platform whose size and cost limit the accessibility. Therefore, the assessment (and future training) of navigation abilities with affordable and easy-to-use technology such as HMD open new perspectives.
The study will investigate the effects of an inovative intervention based on the use of music on 45 professionals in the field of dementia, 45 elderly people with dementia.
The goal of this observational study is to understand the clinical variability in a population of ALS patients using multidimensional biomarkers. The main questions it aims to answer are: - Which set of biomarkers explain genotypic-phenotypic correlations in ALS? - Which set of biomarkers can be used to subdivide the ALS population in homogeneous subgroups? Participants will undergo: - neurological evaluation - neurophysiological evaluation - neuropsychological evaluation - whole exome sequencing - biomarker measurement in CSF and plasma