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临床试验/NCT07485465
NCT07485465尚未招募不适用

The Role of Chat GPT in the Diagnosis and Treatment of Lymphedema

Fatih Sultan Mehmet Training and Research Hospital1 个研究点 分布在 1 个国家目标入组 25 人开始时间: 2026年3月15日最近更新:

试验速览

阶段
不适用
状态
尚未招募
发起方
入组人数
25
试验地点
1
主要终点
Diagnostic accuracy rate

研究概览

简要总结

A domain-specific, custom-trained large language model for the differential diagnosis and treatment planning of lymphedema, lipedema, and venous insufficiency.

详细描述

The differential diagnosis of lower limb swelling remains problematic in clinical practice, as lymphedema, lipedema, and peripheral venous disease often present with similar features. Therefore, we developed LymphedemaGPT, a GPT-5-based clinical assistant designed to help practitioners navigate these diagnostic complexities.

LymphedemaGPT was designed to analyze structured patient data to extract clinical summaries, present possible diagnoses with percentage probabilities, create differential diagnosis tables, suggest additional diagnostic tests, and generate evidence-based treatment plans.

LymphedemaGPT's responses are based on seven scientific publications uploaded to the system, in addition to the Sleigh BC & Manna B (2023) and Rockson approaches. Owing to this resource integration, the model can provide more reliable and consistent recommendations aligned with evidence-based medicine principles based on current guidelines and scientific publications.

Extensive prompt engineering techniques were applied to optimize the diagnostic and therapeutic accuracy of LymphedemaGPT.

The model is programmed to prioritize the questioning phase until a diagnosis is confirmed. In the initial responses, only structured anamnesis questions were asked, and after sufficient information was collected, systematic analysis and treatment planning were initiated. The response flow was designed as follows: (1) history collection, (2) preliminary assessment, (3) additional questioning (if necessary), and (4) systematic analysis and treatment planning when sufficient data were obtained.

研究设计

研究类型
Observational
观察模型
Case Only
时间视角
Cross Sectional

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • Patients over the age of 18
  • Clinical diagnosis of lymphoedema
  • Clinical diagnosis of lipoedema
  • Clinical diagnosis of venous insufficiency

排除标准

  • Lack of medical history
  • Lack of demographic data
  • Lack of clinical data and
  • Lack of imaging methods

结局指标

主要结局

Diagnostic accuracy rate

时间窗: 1 hour

Percentage of cases where the primary diagnosis (most likely diagnosis) was correctly determined. The maximum percentage for each case was 100, and the minimum percentage was 0. Higher percentages mean a better outcome.

Treatment adequacy rate

时间窗: 1 hour

Percentage of treatment recommendations consistent with current guidelines. The maximum percentage for each case was 100, and the minimum percentage was 0. Higher percentages mean a better outcome.

Average criterion score

时间窗: 1 hour

Average Likert score of two evaluators for each criterion. The maximum score for each case was 40, and the minimum score was 8. higher scores mean a better outcome.

次要结局

  • Overall performance score(1 hour)

研究者

发起方
Fatih Sultan Mehmet Training and Research Hospital
申办方类型
Other
责任方
Sponsor

研究点 (1)

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