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Study on a Machine Learning-Based Identification Model for Streptococcus pneumoniae Bloodstream Infection in Children

Development and Validation of Machine Learning for Discriminating Pneumococcus Pneumonia Bloodstream infection: A Case-Matched Study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600128099
Enrollment
Unknown
Registered
2026-07-14
Start date
2026-08-01
Completion date
Unknown
Last updated
2026-07-20

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

Conditions

Streptococcus pneumoniae pneumonia complicated with bloodstream infection

Interventions

Bloodstream infection group:None
Non-bloodstream infection group:None

Sponsors

The Second Affiliated Hospital of Wenzhou Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
No minimum to 16 Years

Inclusion criteria

Inclusion criteria: 1.Age >=1 month and < < 16 years old; 2.A hospitalized child was diagnosed with Streptococcus pneumoniae pneumonia, meeting the standards of the "Guidelines for the Management of Community-Acquired Pneumonia in Children". The etiological diagnosis was confirmed (Streptococcus pneumoniae was detected in sputum or alveolar lavage fluid culture, or the nucleic acid test of Streptococcus pneumoniae was positive), and the clinical diagnosis was confirmed (typical clinical manifestations of pneumonia + lung imaging evidence). 3.The clinical data are complete.

Exclusion criteria

Exclusion criteria: 1.Pneumonia complicated with other bacteria such as Staphylococcus aureus and Haemophilus influenzae, or non-viral pathogens such as Mycoplasma pneumoniae, chlamydia, and fungi; 2.Antibiotics were used before admission; 3.Abnormal immune function, including congenital immune deficiency diseases, AIDS, long-term use of glucocorticoids/immunosuppressants, after hematopoietic stem cell transplantation, chemotherapy period for malignant tumors, etc; 4.Combined with underlying severe diseases, including complex congenital heart disease, bronchopulmonary dysplasia, end-stage renal disease, liver cirrhosis, neuromuscular diseases, genetic metabolic diseases and other diseases that significantly affect the prognosis of infection; 5.Non-infectious lung diseases, such as atelectasis, bronchial foreign bodies, allergic pneumonia and other cases misdiagnosed as pneumonia; 6.Infection caused by iatrogenic factors, secondary infection after admission due to central venous catheterization, tracheal intubation and other operations, rather than bloodstream infection directly progressing from Streptococcus pneumoniae pneumonia.

Design outcomes

Primary

MeasureTime frame
Laboratory indicators: blood routine, blood biochemistry, procalcitonin, and pathogen results of blood culture;Chest imaging indicators;

Countries

China

Contacts

Public ContactXia Xiaojiao

The Second Affiliated Hospital of Wenzhou Medical University

xiaxi37@163.com+86 577 88002726

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jul 23, 2026