AI model predicts survival risk in critically ill children
AI Based Multi-modal Parameter of Peripheral Blood Cells (MMPBC) Predicts Survival Risk in Critically Ill Children: a Multicenter, Retrospective Cohort Study
This study is testing an AI tool that looks at blood cell data to see if it can help doctors predict survival chances for critically ill children in intensive care units.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 3 (estimated) |
| Ages | 1 Day to 18 Years |
| Sex | All |
| Sponsor | Zhujiang Hospital Academic / other |
| Locations | 1 site (Guangzhou, Guangdong) |
| Trial ID | NCT06034639 on ClinicalTrials.gov |
What this trial studies
This observational study investigates the effectiveness of an AI-based prediction model that analyzes multi-modal blood cell data to assess survival risk in critically ill children. The research focuses on children admitted to pediatric intensive care units (PICUs) and neonatal intensive care units (NICUs) who are facing severe health challenges. By utilizing advanced blood cell analysis technologies, the study aims to provide early warnings regarding patient survival, potentially improving clinical decision-making. The study will involve a large-scale cohort of critically ill children, leveraging comprehensive clinical data and blood test results.
Who should consider this trial
Good fit: Ideal candidates for this study are children under 18 years old who have been admitted to NICUs or PICUs and have undergone specific blood tests.
Not a fit: Patients with congenital immunodeficiency or specific blood diseases may not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could significantly enhance early detection of survival risks in critically ill children, leading to timely interventions.
How similar studies have performed: While the use of AI in medical predictions is gaining traction, this specific approach focusing on multi-modal blood cell data in critically ill children is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: 1. Children who were admitted to NICU and PICU from January 1, 2018, to March 31, 2023. 2. Age \<18 years, gender not limited. 3. Blood routine tests were performed using Mindray Medical's five-category blood cell analyzer (including BC6000, BC6000PLUS, BC6800PLUS, and BC7500 series), and the instrument or computer system retained relatively complete blood cell multi-modal data. 4. Detailed clinical medical records related to this study can be obtained. 5. Patients who were repeatedly admitted to NICU or PICU and had different conditions, causes, and outcomes each time were counted as new cases. Exclusion Criteria: 1. Children with congenital immunodeficiency. 2. Children with blood diseases, including iron-deficiency anemia, macrocytic anemia, hereditary spherocytosis, glucose-6-phosphate dehydrogenase deficiency, thalassemia, autoimmune hemolytic anemia, aplastic anemia, immune thrombocytopenia, acute lymphoblastic leukemia, acute non-lymphoblastic leukemia, multiple myeloma, allergic purpura, myelodysplastic syndrome, etc. 3. Children with genetic metabolic diseases, including galactosemia, mucopolysaccharidosis, glycogen storage disease, phenylketonuria, albinism, alkaptonuria, hypoxanthine-guanine phosphoribosyltransferase deficiency, chromhidrosis, Goucher disease, Tay-Sachs disease, etc. 4. Children with chromosomal diseases, including Down syndrome, trisomy 18, etc. 5. Children who received blood products within six months, including transfused blood components, human immunoglobulin, etc.
Where this trial is running
Guangzhou, Guangdong
- Zhujiang Hospital of Southern Medical University — Guangzhou, Guangdong, China (Recruiting)
Study contacts
- Study coordinator: Ruowen He
- Email: 1577576652@qq.com
- Phone: 13434240706
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.