The Predictive Value of Sidestream Dark Field Imaging in Diabetic Nephropathy: a Observational Clinical Trial Evaluating the Predictive Value of SDF in DN
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 入组人数
- 143
- 试验地点
- 1
- 主要终点
- the comparison of the density of total length of the small perfusd vessels(PDV) in the acquisition window between the 3 groups
研究概览
简要总结
Diabetic microangiopathy refers to the pathological changes of arterioles, capillaries and venules in diabetic patients. Due to the impacts including glycol-metabolism disorder, disturbance of lipid metabolism, cytokine, oxidative stress and hemodynamic changes, the structure and function of microvessels are damaged accordingly. Diabetic nephropathy (DN) is one of the most common and serious chronic microvascular complications of diabetes, and becomes a leading cause of end-stage renal failure(ESRF). Presently, urinary albumin/creatinine ratio (UACR) is a widely accepted and relatively reliable indicator for early diagnosis of DN, however, there are 2/3 DN patients with normal albuminuria have decreased glomerular filtration rate (glomerular filtration rate, GFR) and abnormal structure of the kidney, one the other hand, the presence of albuminuria is associated with other vascular dysfunction and kidney disease other than DN, therefore its accuracy is increasingly being challenged.
Sidestream dark field(SDF) imagining technology, as an emerging way to visualize blood vessels, is evaluated in a semi-quantitative manner and provides an effective means to study structure and function of microcirculation. Different from biochemical markers like albuminuria, SDF provides a visual information about vessel structure, density, and quality of diffusion. At present the research of sublingual microcirculation by SDF technique is mainly applied to microcirculation monitoring in patients in the intensive care unit or laboratory animal models with acute hemorrhagic shock to assess the potential of being a tool of diagnosis and treatment prognostic indicator, no relevant research has been carried out to evaluate the predictive value of diabetic microangiopathy in literature so far.
Herein, the investigators designed the study based on SDF imaging to collect scientific data, thus providing strong support for the early assessment and diagnosis of diabetic nephropathy and possibly guiding individual therapy in the future.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Cross Sectional
入排标准
- 年龄范围
- 18 Years 至 70 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •age ranges from 18 to 70 years old
- •signed informed consent
排除标准
- •Younger than 18 years old or older than 70 years old
- •Shock patients who have low blood pressure under 90/60mmHg
- •Patients with mental abnormality who are uncooperative with this study
- •Having difficulty in mouth opening
- •Patients with Ketoacidosis
- •Oral mucosal inflammation or injury, which could locally influence the sublingual microvasculature
- •Pregnant or lactating women
- •Refuse to sign informed consent
结局指标
主要结局
the comparison of the density of total length of the small perfusd vessels(PDV) in the acquisition window between the 3 groups
时间窗: 21 months
We use dark-field microcirculation microscopic observation System (Chinese Advanced Vessel Analyse Contrast System 4.0, C - AVA - C version 4.0) developed by Li Hua company to compare interesting parameters of vessels between the three groups. PVD is one of the parameters indicated of the perfused vessel density, calculated by the ratio of the length of small perfusion vessels to the visual field area (unit: mm/mm2)
次要结局
- the comparison of Proportion of De Backer density score between the 3 groups(21 months)
- the comparison of The density of the total length of small vessels(TVD) in the area of the acquisition window between the 3 groups(21 months)
- Correlation comparison: The correlation between SDF vascular parameters and the clinical data of the subjects was compared(21 months)
研究者
Zhiming Zhu
Director of the department of Hypertension & Endocrinology, Daping Hospital
Third Military Medical University