Artificial Intelligence Cerebral Gray-white Matter Ratio Module Usage in Hsinchu District Hsinchu District Using an Artificial Intelligence Cerebral Gray-white Matter Ratio Module

NCT06856018 | Active Not Recruiting

• 1 other identifier: 202404018RINA
• Study Type: observational
• Target: 350
• Locations: 1 country
• Sites: 1

Brief Summary

This study aims to establish an electronic medical record and imaging database for out-of-hospital cardiac arrest (OHCA) patients at NTUH Hsinchu Branch. Leveraging an AI deep learning model and an automated brain gray-white matter analysis system developed at NTUH, the research seeks to validate these tools externally. By integrating electronic medical records and brain imaging data, the project strives to enhance the accuracy of prognostic assessments, supporting physicians and families in decision-making for post-cardiac arrest care. Validation at Hsinchu Branch will assess the model's reliability across diverse medical settings and patient populations, optimizing its applicability and accuracy.

Conditions

Out of Hospital Cardiac Arrest

Keywords

Out-of-hospital cardiac arrest patients; resuscitation,; artificial intelligence deep learning model

Outcome Measures

Primary Outcomes (1)

• Cerebral Performance Categories (CPC) Scale

  The Cerebral Performance Categories (CPC) scale is crucial for evaluating neurological outcomes in OHCA patients, providing a standardized framework to assess brain function and recovery after cardiac arrest. Ranging from CPC 1 (good recovery) to CPC 5 (brain death), it categorizes levels of neurological impairment, offering insights into the patient's prognosis. This scale is widely used in clinical and research settings to ensure consistent outcome measurement and facilitate comparison across studies. Additionally, it plays a vital role in guiding clinical decisions and discussions with families about post-resuscitation care and expectations, ultimately supporting better-informed decision-making.

  From the time of ROSC achievement until hospital discharge or death, assessed up to 700 days

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients with out-of-hospital cardiac arrest

You may qualify if:

• \- Patients at National Taiwan University Hospital Hsinchu Branch who experienced non-traumatic cardiac arrest between January 1, 2014, and December 31, 2020, and successfully achieved return of spontaneous circulation (ROSC) following resuscitation.

You may not qualify if:

• Under 18 years of age;
• Pregnant women;
• Individuals who did not achieve successful resuscitation
• Individuals without computed tomography (CT) imaging after resuscitation.

Sponsors & Collaborators

• National Taiwan University Hospital: lead

Study Sites (1)

National Taiwan University Hospital Hsin-Chu Branch

Hsinchu, 300, Taiwan

Location

Related Publications (5)

• Mutasa S, Sun S, Ha R. Understanding artificial intelligence based radiology studies: What is overfitting? Clin Imaging. 2020 Sep;65:96-99. doi: 10.1016/j.clinimag.2020.04.025. Epub 2020 Apr 23.

  PMID: 32387803 BACKGROUND

• Wang CH, Huang CH, Chang WT, Tsai MS, Yu PH, Wu YW, Chen WJ. Prognostic performance of simplified out-of-hospital cardiac arrest (OHCA) and cardiac arrest hospital prognosis (CAHP) scores in an East Asian population: A prospective cohort study. Resuscitation. 2019 Apr;137:133-139. doi: 10.1016/j.resuscitation.2019.02.015. Epub 2019 Feb 20.

  PMID: 30797049 BACKGROUND

• Adrie C, Cariou A, Mourvillier B, Laurent I, Dabbane H, Hantala F, Rhaoui A, Thuong M, Monchi M. Predicting survival with good neurological recovery at hospital admission after successful resuscitation of out-of-hospital cardiac arrest: the OHCA score. Eur Heart J. 2006 Dec;27(23):2840-5. doi: 10.1093/eurheartj/ehl335. Epub 2006 Nov 2.

  PMID: 17082207 BACKGROUND

• Chang HC, Tsai MS, Kuo LK, Hsu HH, Huang WC, Lai CH, Shih MC, Huang CH. Factors affecting outcomes in patients with cardiac arrest who receive target temperature management: The multi-center TIMECARD registry. J Formos Med Assoc. 2022 Jan;121(1 Pt 2):294-303. doi: 10.1016/j.jfma.2021.04.006. Epub 2021 Apr 29.

  PMID: 33934947 BACKGROUND

• Rea TD, Eisenberg MS, Sinibaldi G, White RD. Incidence of EMS-treated out-of-hospital cardiac arrest in the United States. Resuscitation. 2004 Oct;63(1):17-24. doi: 10.1016/j.resuscitation.2004.03.025.

  PMID: 15451582 BACKGROUND

MeSH Terms

Conditions

Out-of-Hospital Cardiac Arrest

Condition Hierarchy (Ancestors)

Heart Arrest; Heart Diseases; Cardiovascular Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 17, 2024
• First Posted: March 4, 2025
• Study Start: December 1, 2024
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: November 18, 2025

Record last verified: 2025-11

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)