Bacterial Infections Clinical Trial
Official title:
Development and Accuracy Evaluation of Gram Staining Analysis AI
NCT number | NCT06377592 |
Other study ID # | G22396 |
Secondary ID | |
Status | Recruiting |
Phase | |
First received | |
Last updated | |
Start date | May 10, 2023 |
Est. completion date | March 31, 2027 |
The investigators use Gram-stained specimens provided from clinical settings to develop and evaluate the accuracy of Gram staining analysis AI
Status | Recruiting |
Enrollment | 18000 |
Est. completion date | March 31, 2027 |
Est. primary completion date | March 31, 2027 |
Accepts healthy volunteers | No |
Gender | All |
Age group | N/A and older |
Eligibility | Inclusion Criteria: - Patients in whom a Gram stain test was ordered Exclusion Criteria: - No exclusion criteria |
Country | Name | City | State |
---|---|---|---|
Japan | Osaka University Hospital | Suita | Osaka |
Lead Sponsor | Collaborator |
---|---|
GramEye |
Japan,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Advanced level of blood culture Gram stain analysis AI accuracy | Analyzing Gram-stained microscopic images of blood culture-positive specimens using AI and evaluating the accuracy of bacterial species estimation For example, classify GPC clusters as S. aureus or CNS. | Day1 | |
Primary | Ordinary level of blood culture Gram stain analysis AI accuracy | Gram-stained microscopic images of blood culture-positive specimens are analyzed using AI, and bacteria are classified based on morphological classification.
For example, gram-positive cocci (GPC) are classified into gram-positive staphylococci (GCP clusters) and gram-positive streptococci (GPC chains). |
Day1 |
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