Меню
Идёт набор NCT06760845

Raman Spectroscopy Diagnosis of Kidney Diseases

Наблюдательное IgA Nephropathy (IgAN) Membranous Nephropathy Diabetic Nephropathy Focal Segmental Glomerulosclerosis (FSGS)

Ориентир для пациента и семьи

Простыми словами

Автоматическая сводка по структурированным данным реестра. Она помогает сориентироваться, но не заменяет официальный протокол или оценку врача.

Что изучают
В протоколе указаны: Imaging Time.
Кому может быть актуально
Состояния в реестре: IgA Nephropathy (IgAN), Membranous Nephropathy, Diabetic Nephropathy, Focal Segmental Glomerulosclerosis (FSGS). Базовые параметры: Без ограничений · Все.
Что важно проверить
Возраст, диагноз и пол — только базовые ориентиры. Предыдущее лечение, анализы и другие обязательные условия указаны ниже в критериях участия.
Где проводится
Китай
Следующий шаг
Сохраните исследование, покажите его лечащему врачу и уточните актуальный статус у исследовательского центра. Расходы, документы и поездка →
Официальное название

Research on Raman Spectroscopy Detection Technology in Kidney Disease Diagnosis

Обзор

This research plan, from January 2021 to December 2024, aims to collect serum and morning urine from patients diagnosed with IgA nephropathy, idiopathic membranous nephropathy, diabetic nephropathy, and focal segmental glomerulosclerosis the Nephrology Department of Qianfoshan Hospital in Shandong Province, through renal biopsy. These samples will be scanned using a Raman spect to obtain Raman spectral data. The scattering peaks in the Raman spectra will be analyzed using Origin software for Gaussian curve fitting. The position of the peaks will used to query relevant literature to identify the corresponding chemical bonds and confirm the presence of compounds. The intensity and area of the chemical substance peaks in the Raman will be calculated and used to plot calibration curves, thereby establishing a quantitative analysis equation. This equation will be used to accurately calculate the concentration of each analyte in serum and urine samples. Based on the average concentration data for each patient group, multivariate analysis methods, such as principal component analysis (PCA) and Mahalanis distance discriminant model, will be used to classify and predict the disease types. The preliminary data for this study comes from the Nephrology Department ofianfoshan Hospital, where different types of glomerular diseases have been pathologically classified using tools such as light microscopy, electron microscopy, and immunoforescence microscopy. By combining Raman spectroscopy technology and statistical analysis, this study aims to establish a non-invasive and efficient diagnostic tool to assist in the of kidney diseases and predict treatment outcomes.

Вмешательства

  • Диагностический тест Imaging Time
    Raman spectroscopy images of blood and urine

Первичные конечные точки

  • Raman spectroscopy images of blood and urine [Срок оценки: From the time of enrollment to the completion of blood and urine collection within 2 days]

Критерии участия

Критерии включения

  • Age 18 years or older;
  • Patients diagnosed with IgA nephropathy, idiopathic membranous nephrop, diabetic nephropathy, or focal segmental glomerulosclerosis confirmed by renal biopsy;
  • Patients who have not received hormone and/or immunosup therapy before the renal biopsy;

Критерии исключения

  • Presence of factors causing secondary membranous nephropathy: such as autoimmune diseases (systemic lupus erythematosus),/infections (viral hepatitis), drugs or toxins, etc.;
  • Severe infection: clinical manifestations such as fever, cough and sputum, throat, abdominal pain, diarrhea, boils and other skin and soft tissue infections, with white blood cell count in blood routine exceeding the normal range (10×09/L);
  • Severe cardiovascular disease: including chronic heart failure of grade 3 or above and various arrhythmias;
  • Infect diseases: active phase of various types of hepatitis, AIDS, syphilis, etc.;
  • Evidence of tumor: already diagnosed with a certain tumor or manifestations, tumor markers, etc. indicating the possibility of a tumor;
  • Patients with incomplete data or missed diagnosis.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Да

Дизайн исследования

Модель наблюдения
Другое

Центры проведения

Китай · 1 центр
  • Shandong Second Medical University. No.7166 Baotong West Street, Weifang, Shandong, 261053 — Цзинань

Публикации

  • Lima C, Muhamadali H, Goodacre R. The Role of Raman Spectroscopy Within Quantitative Metabolomics. Annu Rev Anal Chem (Palo Alto Calif). 2021 Jul 27;14(1):323-345. doi: 10.1146/annurev-anchem-091420-092323. PMID 33826853

Идентификаторы

NCT: NCT06760845 · SERS-2024

Первоисточники (государственные реестры)

Открыть это исследование на ClinicalTrials.gov ↗