AI-Driven Accurate Diagnosis of Pathogens in Severe Pneumonia (AI-PneumoDx)

March 10, 2026 updated by: Zhenhui Zhang, Guangzhou Medical University

Study on Accurate Diagnosis of Pathogens in Severe Pneumonia Based on Artificial Intelligence-Driven Technology

Severe pneumonia (SP) is a critical illness characterized by complex etiology, rapid progression, and high mortality. Its precision diagnosis and treatment face two core challenges. First, traditional etiological diagnostic methods (such as culture, serology, PCR) suffer from low detection rates, long turnaround times, and limited pathogen spectrum coverage, making it difficult to meet the clinical need for early, rapid, and precise diagnosis. Even with the application of next-generation sequencing, challenges remain in result interpretation and distinguishing colonization, contamination, and true infection. Second, host immune responses are highly heterogeneous, and there is currently a lack of a subtyping system that can systematically reveal its dynamic evolution and guide precise immunomodulatory therapy. Research on viral severe pneumonia (VSP) indicates that patients exhibit a complex immune imbalance characterized by coexisting hyperactivation of innate immune cells and exhaustion/suppression of adaptive immune cells. Furthermore, this immune heterogeneity may transcend the traditional binary framework, with at least three potential immune subtypes showing significant differences in mortality rates. Therefore, the investigators propose that: By constructing a severe pneumonia cohort and developing an artificial intelligence model that integrates multimodal clinical data (clinical, imaging, microbiological), host multidimensional etiological data (e.g., metagenomic sequencing), and immunomics data (T/B cell immune repertoire, transcriptomics, etc.), it can, on one hand, achieve more accurate and faster etiological diagnosis of severe pneumonia compared to traditional methods; on the other hand, it can identify immune endotypes with distinct immune features, different clinical outcomes, and varied responses to immunomodulatory therapies (e.g., targeting hyperinflammatory or immunosuppressed subtypes). Ultimately, this integrated model system is expected to provide a scientific tool for the individualized treatment and clinical decision-making in severe pneumonia, guiding precise immune intervention to improve patient prognosis.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Active, not recruiting

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Observational

Enrollment (Estimated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
1000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Guangdong
      • Guangzhou, Guangdong, China, 510000
        • Guangzhou First People's Hospital
      • Guangzhou, Guangdong, China, 510000
        • The second Affiliated Hospital of Guangzhou Medical University
      • Guangzhou, Guangdong, China, 510000
        • The Third Affiliated Hospital of Guangzhou Medical University
      • Guangzhou, Guangdong, China, 510000
        • The Affiliated Panyu Central Hospital of Guangzhou Medical University
      • Guangzhou, Guangdong, China, 510000
        • The Fourth Affiliated Hospital of Guangzhou Medical University
      • Guangzhou, Guangdong, China, 510000
        • the Guangzhou Red Cross Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Adult patients admitted to the ICU with a diagnosis of severe pneumonia who meet the specified inclusion and exclusion criteria.

Description

Inclusion Criteria:

  • Age ≥ 18 years;
  • Admitted to the ICU, meeting the diagnostic criteria for severe pneumonia;
  • ICU stay > 72 hours;
  • The patient or legal representative provides informed consent.

Exclusion Criteria:

  • Age < 18 years;
  • Expected survival time < 1 day;
  • Already hospitalized in a general ward for ≥4 weeks or already treated in the ICU for ≥2 weeks;
  • Pregnant or lactating women;
  • Presence of contraindications to bronchoalveolar lavage;
  • Participation in another clinical study or deemed unsuitable by the investigator.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort

Group / Cohort

A group or subgroup of participants in an observational study that is assessed for biomedical or health outcomes.
Severe pneumonia cohort
Plans to enroll approximately 1000 adult patients meeting the diagnostic criteria for severe pneumonia.

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
Accuracy of the AI model for the etiological diagnosis of severe pneumonia
Time Frame: From baseline (Day 0) to Day 7 after enrollment.
The primary outcome is the accuracy of the constructed artificial intelligence model in diagnosing the etiology of severe pneumonia. Accuracy is defined as the proportion of correct predictions made by the model out of the total number of samples. It is calculated using the formula: Accuracy = (Number of Correct Predictions) / (Total Number of Samples). The AI model will integrate multimodal data including clinical, imaging, and microbiological features. The diagnostic performance of the model will be compared against a gold standard.
From baseline (Day 0) to Day 7 after enrollment.
Identification and characterization of immune subtypes in severe pneumonia
Time Frame: From baseline (Day 0) to Day 28 after enrollment.
The primary outcome is the identification of distinct immune subtypes in patients with severe pneumonia using an artificial intelligence model that integrates multimodal data, including clinical parameters, imaging, and immunomics. The study aims to reveal the dynamic evolution of host immune responses. The model will identify at least 3 potential immune subtypes (such as immune hyperactivation, immunosuppression, and mixed types) with significant differences in clinical outcomes like mortality .
From baseline (Day 0) to Day 28 after enrollment.

Secondary Outcome Measures

Secondary Outcome Measures

In a clinical study's protocol, a planned outcome measure that is not as important as the primary outcome measure for evaluating the effect of an intervention but is still of interest. Most clinical studies have more than one secondary outcome measure.
Outcome Measure
Measure Description
Time Frame
Clinical and etiological differences between community-acquired pneumonia (CAP) and hospital-acquired pneumonia (HAP)
Time Frame: From baseline (Day 0) through Day 7 after enrollment
Through the multicenter cohort, the study aims to systematically compare the differences in clinical outcomes, pathogen spectrum, and immune response characteristics between CAP and HAP patients. This comparison will help clarify the distinct clinical features and etiological backgrounds of these two types of pneumonia.
From baseline (Day 0) through Day 7 after enrollment
Exploration of triggering conditions for HAP and development of a predictive model
Time Frame: From baseline (Day 0) to Day 28 after enrollment.
The study aims to explore the triggering conditions for hospital-acquired pneumonia (HAP), specifically identifying key predictive indicators for nosocomial and secondary infections, and to establish a predictive model for HAP. This will involve analyzing clinical, microbiological, and host immune data from the multicenter cohort to identify risk factors and early warning signs.
From baseline (Day 0) to Day 28 after enrollment.
Association between pathogen spectrum characteristics and host immune microenvironment in severe pneumonia.
Time Frame: From baseline (Day 0) to Day 28 after enrollment.
The study will systematically collect serological tests, microbial culture, PCR, and metagenomic sequencing data to comprehensively characterize the pathogen spectrum of severe pneumonia. By integrating this with host immune indicators (such as lymphocyte subsets, cytokines) and clinical outcomes, the study aims to investigate how different pathogens (e.g., bacteria, viruses, fungi, and mixed infections) specifically drive host immune responses. This outcome seeks to reveal the dynamic association between "pathogen-host immunity-clinical outcome", providing a basis for targeted therapy.
From baseline (Day 0) to Day 28 after enrollment.
Association between dynamic evolution of immune subtypes and prognosis
Time Frame: From baseline (Day 0) through Day 28 after enrollment.
This outcome explores the association between the dynamic evolution trajectory of immune subtypes and patient prognosis. Cox proportional hazards models will be used to analyze the independent relationship between subtypes and prognosis.
From baseline (Day 0) through Day 28 after enrollment.
Development of a 28-day mortality prediction model based on multimodal AI fusion.
Time Frame: 28 days after enrollment.
The study aims to build an intelligent prognostic prediction model for severe pneumonia by integrating multimodal data, including clinical baseline information, scoring systems (APACHE II, SOFA), imaging features (CT/X-ray), laboratory indicators, and dynamic immune data. This is an exploratory research endpoint to determine if the AI model can predict 28-day all-cause mortality in patients with severe pneumonia.
28 days after enrollment.

Other Outcome Measures

Other Outcome Measures

For clinical trials, a planned measurement described in the protocol that is used to determine the effect of an intervention/treatment on participants. For observational studies, a measurement or observation that is used to describe patterns of diseases or traits, or associations with exposures, risk factors, or treatment. Types of outcome measures include primary outcome measure and secondary outcome measure.
Outcome Measure
Measure Description
Time Frame
Exploration of immune subtype-specific biomarkers and their diagnostic efficacy
Time Frame: From baseline (Day 0) through Day 7 after enrollment.
The study aims to explore and identify specific biomarkers for different immune subtypes of severe pneumonia, particularly viral severe pneumonia (VSP), and evaluate their diagnostic efficacy. This involves using SHAP and other interpretability techniques to screen for key biomarker combinations from complex multi-omics features. The diagnostic performance of these subtype-specific biomarkers will be validated, aiming for an Area Under the Curve (AUC) greater than 0.75. This exploration is part of developing a simplified clinical diagnostic panel based on key immune markers and clinical data.
From baseline (Day 0) through Day 7 after enrollment.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
Guangzhou Medical University

Investigators

Investigators

A researcher involved in a clinical study. Related terms include site principal investigator, site sub-investigator, study chair, study director, and study principal investigator.
  • Principal Investigator: Zhen-hui Zhang, PhD, Second Affiliated Hospital of Guangzhou Medical University
  • Study Chair: Zi-feng Yang, State Key Laboratory of Respiratory Disease

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
September 18, 2025

Primary Completion (Estimated)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
December 31, 2026

Study Completion (Estimated)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
December 31, 2027

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
March 5, 2026

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
March 5, 2026

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
March 10, 2026

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
March 12, 2026

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
March 10, 2026

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
March 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • ICU-2025-001
  • GZNL2024B01008 (Other Grant/Funding Number: Guangzhou Laboratory and State Key Laboratory of Respiratory Disease)

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

IPD Plan Description

A final decision regarding IPD sharing has not been made. Any future data sharing will comply with ethical guidelines, participant privacy protection, and relevant regulatory requirements.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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