Artificial Intelligence for Rare Disease Diagnosis
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: AI-Assisted Diagnosis.
- Кому может быть актуально
- Состояния в реестре: Rare Disorders, Rare Diseases. Базовые параметры: от 18 лет · 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 →
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Официальное название
A Multicentre, Randomised Diagnostic Accuracy Study Evaluating AI Assisted Diagnosis of Rare Diseases
Обзор
A multicentre, randomised diagnostic accuracy study to evaluate whether the rare disease-specific AI can improve diagnostic accuracy and efficiency for physicians managing real-world clinical cases.
Подробное описание
Rare diseases collectively affect approximately 300 million individuals worldwide. This prolonged diagnostic delay is attributable in large part to the breadth of over 7,000 recognized rare conditions, which far exceeds the clinical exposure of any individual physician. A rare disease-specific diagnostic AI was developed by Peking Union Medical College Hospital (PUMCH), supporting differential diagnosis generation, clinical workup planning, and genomic variant interpretation. A balanced crossover design ensures that each enrolled physician serves as their own control, substantially reducing confounding from inter-reader variability in baseline diagnostic competency. Within each physician, cases are randomly assigned at the case level to either the AI-assisted or unassisted condition, such that each physician reads a subset of cases with AI assistance and the remaining cases without. This within-reader, case-level randomization eliminates the need for a washout period and directly controls for inter-reader differences in baseline diagnostic competency. All cases are collected from real-world clinical settings with independently confirmed gold-standard diagnoses and span a pre-specified spectrum of rare and non-rare disease categories, reflecting the differential diagnostic challenge encountered in routine clinical practice, to ensure diagnostic breadth and clinical representativeness. Physician seniority (junior vs. senior) is incorporated as a pre-specified stratification and subgroup analysis variable. Diagnostic outputs are evaluated by an independent Expert Adjudication Committee, blinded to the assistance condition, using standardized scoring criteria established prior to data collection.
Вмешательства
- Другое AI-Assisted Diagnosis
A rare disease-specific diagnostic AI model is used to accept free text input and assist in rare disease diagnoses. During the experimental condition, physicians may interact with the system freely alongside standard clinical resources to support their diagnostic reasoning.
Первичные конечные точки
- Top-3 Diagnostic Accuracy [Срок оценки: Up to 60 minutes per case (from case presentation to diagnostic report submission).]
Вторичные конечные точки (6)
- Diagnosis Time per Case [Срок оценки: Up to 60 minutes per case (from case presentation to diagnostic report submission).]
- Workup Plan Quality [Срок оценки: Up to 60 minutes per case (from case presentation to diagnostic report submission).]
- Physician Reported Usability of the AI-Assisted Diagnostic System [Срок оценки: Up to 60 minutes per case (upon completion of each case reading).]
- Physician Reported Workload [Срок оценки: Up to 60 minutes per case (upon completion of each case reading).]
- Physician Satisfaction [Срок оценки: Up to 60 minutes per case (upon completion of each case reading).]
- Physician Intention to Adopt AI-Assisted Diagnostic Support [Срок оценки: Up to 60 minutes per case (upon completion of each case reading).]
Критерии участия
Критерии включения
- 1\. Licensed physicians at the junior or senior level affiliated with internal medicine, neurology, pediatrics, and rare disease-related departments.
- 2\. Willingness to provide written informed consent, adhere to trial protocols, and complete all required pre-study training prior to enrollment.
Критерии исключения
- 1\. Prior exposure to any of the clinical cases included in the study case library.
- 2\. Direct participation in the design or development of the AI model.
Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.
Здоровые добровольцы: Да
Дизайн исследования
- Распределение
- Рандомизированное
- Модель
- Перекрёстный дизайн
- Маскирование
- Простое слепое
- Основная цель
- Диагностика
Центры проведения
Китай · 13 центров
- Peking Union Medical College Hospital — Пекин
- Cangzhou Central Hospital — Cangzhou
- Changchun Sacred Heart Hospital — Changchun
- Dongguan People's Hospital — Дунгуань
- First People's Hospital of Foshan — Foshan
- Guizhou Provincial People's Hospital — Guiyang
- Jilin Central General Hospital — Jilin City
- The First People's Hospital of Yunnan Province — Куньмин
- … и ещё 5 центров
Идентификаторы
NCT: NCT07625436 · PUMCH I-23PJ948