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Набор скоро начнётся NCT07650799

AI-assisted Rare Disease Diagnosis

Без фазы С лечением Rare Disorders Rare Diseases

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 system.
Кому может быть актуально
Состояния в реестре: Rare Disorders, Rare Diseases. Базовые параметры: от 0 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 →
Официальное название

A Multicentre Randomised Controlled Trial of LLM-Assisted Diagnostic Support in Patients With Suspected Rare or Diagnostically Unresolved Disease

Обзор

A multicentre randomised controlled trial evaluating whether a rare-disease diagnostic large language model can improve diagnostic quality, efficiency, and health-economic outcomes for physicians managing patients with suspected rare or diagnostically unresolved disease.

Подробное описание

Rare disease patients commonly experience prolonged diagnostic odysseys rooted in limited rare disease recognition, phenotypic heterogeneity, and dispersed diagnostic clues. Diagnostic decision-support large language models may improve first-visit consultations by integrating prior records, generating structured analyses, and proposing candidate diagnoses, thereby shortening diagnostic pathways and improving appropriate genetic testing referral.

Participating physicians will provide care under both AI-assisted and standard diagnostic workflows. Eligible patients will be individually randomised to receive either AI-assisted diagnostic support or standard clinical practice.

In the intervention arm, physicians will have diagnostic support from AI when seeing patients. In the control arm, patients are seen under standard hospital workflow without any generative AI tools. Outcomes adjudicated by an independent Expert Committee blinded to arm assignment; adjudicators access no AI-generated materials.

A prospective within-trial economic evaluation will be conducted alongside the randomized trial. Healthcare resource use and costs associated with the diagnostic pathway will be collected.

Вмешательства

  • Другое AI system
    The study AI system will be used to provide diagnostic support during the clinical encounter, including structuring relevant clinical information, generating a clinical analysis, and suggesting candidate diagnoses for review by the treating physician.

Первичные конечные точки

  • Overall Correct Diagnostic Yield [Срок оценки: From the first visit to final reference diagnosis adjudication, an average of 8 weeks.]
Вторичные конечные точки (7)
  • Candidate Diagnostic Accuracy [Срок оценки: From the first visit to final reference diagnosis adjudication, an average of 8 weeks.]
  • Molecular Diagnostic Yield [Срок оценки: From the first visit to final reference diagnosis adjudication, an average of 8 weeks.]
  • Time to a Correct Diagnosis [Срок оценки: From enrollment to the end of follow-up, up to 8 weeks.]
  • Appropriate Genetic Testing Recommendation Rate [Срок оценки: From the initial consultation to genetic testing indication adjudication, approximately 8 weeks]
  • Duration of the Initial Physician Consultation [Срок оценки: Assessed at each consultation (day 1), within 1 day.]
  • Physician-Reported Experience [Срок оценки: Assessed at each consultation (day 1), within 1 day.]
  • Patient-Reported Experience [Срок оценки: Assessed at each consultation (day 1), within 1 day.]

Критерии участия

Patient Inclusion Criteria:

  • Any age. Legal guardian co-signs consent for minors or individuals lacking legal capacity.
  • Diagnostically unresolved or suspected rare disease, with at least one prior complete clinical evaluation at a secondary-level or higher institution yielding no confirmed explanatory diagnosis.
  • First presentation to the enrolling institution for the current condition, with no prior records in the institutional HIS or outpatient system.
  • No prior genetic testing related to the current condition; no results or reports available.
  • Written informed consent provided voluntarily by patient or legal guardian, with commitment and ability to complete structured follow-up.

Patient Exclusion Criteria:

  • Confirmed diagnosis (clinical, pathological, or molecular) explaining the primary symptoms.
  • Emergency presentation, critical illness, or any condition incompatible with trial participation.
  • Neither patient nor legally authorised proxy able to complete follow-up.
  • Concurrent enrollment in another interventional study with diagnostic accuracy or genetic testing yield as a primary endpoint.
  • Prior use of another AI system has already yielded a confirmed diagnosis for the current condition.

Physician Inclusion Criteria

  • Licensed physician in internal medicine, neurology, pediatrics, general medicine, rare disease, or a related specialty.
  • ≥2 years of clinical practice; competent to manage rare disease patients; stratified into junior or senior tier.
  • Voluntary participation with written informed consent.

Physician Exclusion Criteria

  • No longer in clinical practice, or unable to fulfill required outpatient duties during the study period.
  • Unwilling to provide informed consent or to permit protocol-required collection of consultation and questionnaire data.
  • Currently enrolled in another AI-assisted clinical workflow, or expected to be unable to comply with the procedures.

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

Здоровые добровольцы: Нет

Дизайн исследования

Распределение
Рандомизированное
Модель
Параллельные группы
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: NCT07650799 · PUMCH I-26PJ0002

Первоисточники (государственные реестры)

Открыть это исследование на ClinicalTrials.gov ↗