Changing the Future of Intestinal Failure in Intestinal Chronic Inflammation: Towards Innovative Predictive Factors and Therapeutic Targets.
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 入组人数
- 254
- 试验地点
- 1
- 主要终点
- Predictive Factors for FH in Crohn's Disease Using Gut Microbiota Composition
研究概览
简要总结
This is an interventional, prospective, no profit study that will be performed at CEMAD, from FONDAZIONE POLICLINICO GEMELLI IRCCS, Rome (UO1) and U.O.C. Internal Medicine and Gastroenterology from Ospedale Brotzu di Cagliari (UO4). Adult patients with Crohn Disease (CD) and chronic intestinal insufficiency (CF) and adult patients with CD at high and low risk of CF.
详细描述
The study involves an initial evaluation in which faecal samples will be collected, a blood sample will be taken and an ileocolonoscopy with biopsy (additional biopsy collection at the same time as clinical practice biopsy for study-specific analysis) will be performed.
Patients will then be re-evaluated nine months after the initial evaluation. In particular, faecal, blood and additional biopsy samples will be collected at the same time as the clinical practice biopsy and any changes in treatment will be recorded.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Sequential
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 75 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age ≥ 18 years-old and ≤ 75 years old
- •Capable of expressing informed consent;
- •An established diagnosis of Crohn's disease;
- •Antibiotics treatment free for at least 15 days.
排除标准
- •Age < 18 years-old and > 75 years old;
- •Not capable of expressing informed consent;
- •Pregnant or breastfeeding patients;
- •Comorbidities including: cancer pathology present or under active treatment; coagulopathies; chronic hepatopathy, heart failure, renal failure, respiratory failure.
研究组 & 干预措施
Investigation of predictive factors in patients with intestinal failure in crohn disease
- Typing of gut microbiota, metabolome and immunological signatures (IL 1b family and GLP-2 as starting point) in patients with CD and SBS/IF and in two cohorts of patients with CD, respectively at low and high risk of SBS /IF.
- Combining data from gut microbiota, metabolome and immunological analysis using tools based on Artificial Intelligence (AI) and Machine Learning (ML) technologies.
- Creation of a stool Biobank of categories of patients with Crohn's disease at high risk of SBS/IF and of patients with SBS with or without clinical symptoms of IF.
干预措施: analysis of predictive factors of IF in patients with Crohn's disease through the characterization of "multiomics" parameters (Other)
结局指标
主要结局
Predictive Factors for FH in Crohn's Disease Using Gut Microbiota Composition
时间窗: 24 month
This section focuses on characterizing the gut microbiota composition in patients with Crohn's disease at risk of SBS/IF. Advanced sequencing technologies and bioinformatics tools will be used to analyze the relative abundance of microbial species associated with SBS/IF risks. Unit of Measure: percentage or relative abundance of microbial taxa. Objective: To identify microbiota profiles predictive of dysbiosis and their association with SBS/IF risk factors.
Predictive Factors for FH in Crohn's Disease Using Metabolome Analysis
时间窗: 24 month
This section emphasizes the analysis of metabolic profiles. Key metabolites associated with SBS/IF risk will be quantified using mass spectrometry and other advanced chemical analysis techniques. Unit of Measure: metabolite concentration (e.g., µM, mM). Objective: To understand how metabolic variations influence the development of SBS/IF and support the design of targeted nutritional interventions.
Predictive Factors for FH in Crohn's Disease Using Immunological Signature Characterization
时间窗: 24 month
This section investigates the characterization of immunological biomarkers. Specific levels of the IL-1β family and GLP-2 will be measured as indicators of immune response and intestinal repair mechanisms. Unit of Measure: concentration (pg/mL). Objective: To identify immunological signatures associated with an increased risk of SBS/IF and optimize biomarker-based therapeutic strategies.
次要结局
未报告次要终点
研究者
Papa Alfredo
MD, Professor
Fondazione Policlinico Universitario Agostino Gemelli IRCCS