跳至主要内容
临床试验/NCT05787405
NCT05787405已完成不适用

CORONABED.BOT: an Automation Project Using Artificial Intelligence for Early Diagnosis of Clinical Evolution From SARS-CoV-2"

Fondazione Policlinico Universitario Agostino Gemelli IRCCS1 个研究点 分布在 1 个国家目标入组 8,000 人开始时间: 2020年12月1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
8,000
试验地点
1
主要终点
the implementation of prediction models

研究概览

简要总结

The aim of the CORONA.BOT project is to exploit the Artificial Intelligence methods of Generator Real World Data Facility to automatically extract structured and unstructured data from hospital databases and to implement an early risk assessment (warning system) regarding the negative outcome for patients infected with SARS-CoV-2.

The objective of CORONABED.BOT is to analyze the care pathways of patients from the same cohort as CORONA.BOT, in order to identify the total length of stay, intensive care occupations and flows between departments, based on variables demographics and first entry clinics Early identification of patients with symptoms compatible with SARS-CoV-2 infection will enable more rapid activation of isolation procedures, contact monitoring/contact history and decisions on the most appropriate clinical pathway in terms of type of treatment and unit. Similarly, the identification of factors correlated with worse outcomes will allow more effective planning for the use of critical resources (such as intensive care and others).

研究设计

研究类型
Observational
观察模型
Cohort
时间视角
Prospective

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

  • adult patients (18 years of age or older)
  • admitted to the Gemelli and Columbus Polyclinic
  • diagnosis of SARS-CoV-2 infection (suspected cases will also be included).

排除标准

  • 未提供

结局指标

主要结局

the implementation of prediction models

时间窗: 24 months

tThe DataMart built will allow the creation of predictive models both for diagnosis of SARS-coV-2 pneumonia as well as death

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Sponsor

研究点 (1)

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