Skip to content

Testing a new AI tool to quickly identify MRSA and detect PVL genes to help improve treatment decisions

Development and validation of an AI-CDSS using MALDI-TOF MS for rapid SCCmec typing and PVL detection in MRSA and its impact on clinical decision-making: a randomized controlled trial

Status
Recruiting
Phases
Unknown
Study type
Interventional
Source
ISRCTN
Registry ID
ISRCTN48917589
Enrollment
400
Registered
2025-09-15
Start date
2025-10-01
Completion date
Unknown
Last updated
2025-09-29

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

Conditions

Antibiotic resistance Infections and Infestations

Interventions

Randomized comparison of artificial intelligence–clinical decision support system (AI-CDSS) use with standard diagnostic and prescribing practices for MRSA. This randomized controlled trial compares

Sponsors

Tri-Service General Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Medical Licensure Requirements: Participants must be licensed healthcare providers authorized to prescribe antibiotics, including residents, fellows, and attending physicians. 2. Clinical Experience: Participants must have at least one year of clinical experience to ensure they are familiar with antibiotic prescribing practices. 3. Technology Access: Participants must have regular access to computers or tablets with internet connectivity to use the AI clinical decision support system. 4. Training Commitment: Participants must be willing to complete a brief training session to learn how to properly use the AI system.

Exclusion criteria

Exclusion criteria: 1. Limited Prescribing Authority: Healthcare practitioners without medication prescribing privileges, such as nurses, medical interns, and medical students. 2. Insufficient Clinical Experience: Healthcare providers with less than one year of clinical practice experience.

Design outcomes

Primary

MeasureTime frame
Physicians' confidence in diagnosing and managing MRSA infections, including the identification of PVL-positive strains, will be rated by physicians for each case. Confidence will be measured using a structured questionnaire on days 3, 5, 7, and 14 after antibiotic treatment initiation.

Secondary

MeasureTime frame
The following secondary outcome measures will be measured using a questionnaire on days 3, 5, 7, and 14 after antibiotic treatment initiation: 1. Satisfaction with the diagnostic and prescribing process, including factors influencing satisfaction, decision-making efficiency (time required and ease of accessing molecular information), and reliance on technological tools for MRSA management, are all rated and reported by physicians. 2. The effectiveness of diagnostic-guided treatment choices in mitigating public health concerns related to antibiotic resistance and PVL-associated virulence will be assessed by physicians.

Countries

Taiwan

Contacts

Public ContactHung-Sheng Shang
iamkeith@mail.ndmctsgh.edu.tw+886 920713130

Outcome results

None listed

Source: ISRCTN (via WHO ICTRP) · Data processed: Feb 4, 2026