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AI-Driven Accurate Diagnosis of Pathogens in Severe Pneumonia

NCT07461714 · Status: ACTIVE_NOT_RECRUITING · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2026-03-12

No results posted yet for this study

Summary

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.

Conditions

  • Severe Pneumonia

Sponsors & Collaborators

  • Guangzhou Medical University

    lead OTHER

Principal Investigators

  • Zhen-hui Zhang, PhD · Second Affiliated Hospital of Guangzhou Medical University

  • Zi-feng Yang · State Key Laboratory of Respiratory Disease

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-09-18
Primary Completion
2026-12-31
Completion
2027-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07461714 on ClinicalTrials.gov