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Clinical Study of Transcriptome-based Diagnostic Biomarker for Acute Febrile Illness

Transcriptome-based Diagnostic Biomarker for Acute Febrile Illness: a Cross-sectional Observational Study

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06552975
Enrollment
900
Registered
2024-08-14
Start date
2021-09-01
Completion date
2025-08-30
Last updated
2024-08-14

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Acute Febrile Illness

Keywords

Bacterial infection, Viral infection, noninfectious disease

Brief summary

Acute febrile illness is the main cause of outpatient visits,and bacterial and viral infections remains the most common cause. The diagnosis of infection is still based on symptoms and traditional techniques, resulting in overuse of antibacterial drugs or delay in treatment. The signature of host transcripts has a potential to reveal different modes of host-pathogen interaction and may serve as a biomarker for infection discrimination. Of note, transcriptome-microarray and RNA-seq methods need sophisticated techniques and expertise interpretation, hampering the universal implement of these platforms in low-tier hospitals and under- resourced countries. This study explores transcriptome-based diagnostic biomarker for acute febrile illness , hoping to achieve rapid, accurate and cost-effective distinction between bacterial and viral infection.

Detailed description

Acute fever is a common medical emergency worldwide, most often caused by bacterial or viral infections. Early and rapid differential diagnosis of infectious diseases is crucial for improving patient outcomes. While pathogen detection remains the gold standard for diagnosing infections, methods like culture are time-consuming and often lack sensitivity. Additionally, the presence of normal colonizing microorganisms, such as bacteria and viruses in the human body, can lead to false positives in pathogen detection. These limitations often compel physicians to rely on empirical antibacterial therapy based on clinical symptoms, inadvertently contributing to antibiotic overuse and the growing problem of bacterial resistance. Furthermore, the misuse of antibacterial drugs in patients with non-bacterial infections can lead to complications such as secondary infections with Clostridium difficile, liver dysfunction, kidney damage, cytopenia, and alterations in the body's microbiota. Diagnostic markers based on host inflammatory responses offer an alternative approach to infection diagnosis. However, protein biomarkers like procalcitonin, though widely used in clinical settings, are far from ideal for accurately diagnosing bacterial infections, as they are prone to false positives and negatives. A promising direction is the analysis of host-pathogen interactions at the transcriptome level, particularly the differential gene expression of the host in response to various pathogens. This area of research has gained significant attention recently. Transcriptomic markers derived from patients' peripheral blood have been successfully utilized in diagnosing and studying the pathogenesis of various infectious diseases. Despite these advances, studies relying on RNA sequencing or transcriptome chip technology require specialized equipment and bioinformatics expertise, making them expensive and challenging to implement in routine clinical practice. Additionally, the results from transcriptome analysis are not easily validated by reverse transcription polymerase chain reaction(RT-PCR), the gold standard for RNA quantification. Therefore, to make transcriptome-based diagnostic markers more clinically applicable, there is a need for real-time technologies, such as PCR, to enhance the accuracy of infection diagnosis and reduce the misuse of antibacterial drugs. Currently, research in this area remains limited.

Interventions

OTHERInfection

Pathogens such as bacteria and viruses invade the human body, grow, and proliferation, triggering an immune response.

Sponsors

Qilu Hospital of Shandong University
Lead SponsorOTHER

Study design

Observational model
CASE_CONTROL
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
ALL
Age
14 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* 1\. axillary temperature ≥38°C; 2. duration of fever shorter than 14 days; 3. subjects who are fully informed and agree to participate in this study.

Exclusion criteria

* 1.having comorbidities that may affect host gene expression, such as advanced malignancy, autoimmune diseases,immunodeficiency, or taking immune suppressors; 2.pregnancy; 3. mixed infection (viral combined with bacterial infection, autoimmune disease combined with bacterial infection); 4.incomplete clinical information; 5. For safety reasons or the interests of patients, clinicians believe that patients should not participate in any situation in this study.

Design outcomes

Primary

MeasureTime frameDescription
AUC for distinguishing bacterial infection from viral infectionThrough study completion, an average of 2 yearsThe AUC of the transcript biomarkers for distinguishing bacterial infection from viral infection reflects the diagnostic accuracy of the transcript biomarkers.

Secondary

MeasureTime frameDescription
AUC for distinguishing infectious disease from noninfectious diseaseThrough study completion, an average of 2 yearsThe AUC of the transcript biomarkers for distinguishing infectious disease from noninfectious disease reflects the diagnostic accuracy of the transcript biomarkers.

Countries

China

Contacts

Primary ContactGang Wang, professor
wangg1975@hotmail.com86-18560082130

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026