An Observational Clinical Study on the Construction of an Artificial Neural Network Model for ICU Pneumonia
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: establish an artificial neural network model.
- Who it may be relevant to
- Registry conditions: Pneumonia. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
An Observational Clinical Study on the Construction of an Artificial Neural Network Model for Rapid Intelligent Diagnosis of Microorganisms in ICU Pneumonia Based on Species-specific Rapid Detection of Pathogenic Bacteria
Overview
To achieve rapid, intelligent and accurate microbiological diagnosis and treatment for ICU pneumonia, an artificial neural network model for microbiological diagnosis is established, which depends on many clinical cases and machine deep learning from clinical experts' judgements according to species-specific rapid detection of pathogenic bacteria and other clinical parameter variables of patients.
Detailed description
This study is a prospective single-centre observational study, 600 ICU pneumonia patients are expected to be selected as the observation object, and the lower respiratory secretions of patients on d1, d3 and d7 after enrollment are collected for species-specific rapid detection and microbial culture, while the general information of the patients and the clinical information of the corresponding time points on d1, d3 and d7 are collected. Two experienced senior physicians were organized to determine whether the microbial results were colonized or infected, and an artificial neural network model for rapid and intelligent diagnosis of pathogenic microorganisms in ICU pneumonia will be established and validated through multi-dimensional machine learning.
Interventions
- Other establish an artificial neural network model
to establish an artificial neural network model for pathogen diagnosis in ICU pneumonia
Primary outcome measures
- clinical evaluation of each microbial detected whether in colonization or infection [Time frame: day1,day3 and day7 after enrollment]
Eligibility criteria
Inclusion criteria
- aged ≥18 years;
- agreed to obtain lower respiratory specimens for rapid testing of pathogenic bacteria;
- all were enrolled by an experienced physician who dynamically determined that the microorganisms were in a colonised or infected state;
- signed an informed consent form.
Exclusion criteria
- pregnant women;
- lactating women;
- patients who could not obtain lower respiratory specimens;
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Other
Study locations
China · 1 center
- Nanjing Drum Tower Hospital — Nanjing
Identifiers
NCT: NCT06661499 · 2024-607-01