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临床试验/NCT06410547
NCT06410547已完成不适用

Using Large Language Models Such As GPT-4 to Assess Guideline Adherence in Patients With Chronic Obstructive Pulmonary Disease

Charite University, Berlin, Germany1 个研究点 分布在 1 个国家目标入组 78 人开始时间: 2024年5月15日最近更新:
适应症

试验速览

阶段
不适用
状态
已完成
入组人数
78
试验地点
1
主要终点
Percentage of patients treated in concordance with treatment guidelines at the time of hospital discharge

研究概览

简要总结

According to studies in the US and the Netherlands, 33-40% of patients with chronic conditions receive care that does not follow guideline recommendations. These findings have also been demonstrated in the management of COPD. This leads to under- or over-treatment of patients and, in the case of COPD, to exacerbations and hospitalisations. These exacerbations are a significant clinical problem, affecting patient's lung function, quality of life and mortality. They are also a burden on the healthcare system. Technological advances in artificial intelligence offer the opportunity to address these issues in COPD management. In the past year, there have been remarkable innovations in the field of natural language processing, especially through large language models such as GPT-4 from OpenAI and Bard or Gemini from Google. These models offer an opportunity to improve the implementation of evidence-based care in clinical practice.

This study is a prospective, randomised trial that will compare therapy on discharge for patients with COPD. One arm will receive no intervention, while the other arm will receive a treatment recommendation from an LLM. The study will compare the percentage of patients treated according to the guideline.

研究设计

研究类型
Interventional
分配方式
Randomized
干预模型
Parallel
主要目的
Treatment
盲法
Triple (Participant, Care Provider, Outcomes Assessor)

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

  • Diagnosis of COPD
  • Discharge after hospitalization

排除标准

  • Lack of Consent

结局指标

主要结局

Percentage of patients treated in concordance with treatment guidelines at the time of hospital discharge

时间窗: From date of admission (which is enrollment) to the date of discharge, assessed up to one month

This primary endpoint will assess the percentage of guideline-concordant treatments in each study arm.

Adherence to treatment guidelines at the time of hospital discharge

时间窗: From date of admission (which is enrollment) to the date of discharge, assessed up to one month

The primary endpoint will assess whether the treatment at the time of discharge is consistent with the guidelines' recommendations. This is a binary outcome measure of yes or no.

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Matthias Gröschel

Principal Investigator

Charite University, Berlin, Germany

研究点 (1)

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