UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000053009 |
|---|---|
| Receipt number | R000060470 |
| Scientific Title | Ambient mass spectrometry and machine learning-based diagnosis system for acute coronary syndrome |
| Date of disclosure of the study information | 2024/05/12 |
| Last modified on | 2023/12/08 12:03:05 |
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Basic information
Public title
Ambient mass spectrometry and machine learning-based diagnosis system for acute coronary syndrome
Acronym
Ambient mass spectrometry and machine learning-based diagnosis system for acute coronary syndrome
Scientific Title
Ambient mass spectrometry and machine learning-based diagnosis system for acute coronary syndrome
Scientific Title:Acronym
Ambient mass spectrometry and machine learning-based diagnosis system for acute coronary syndrome
Region
| Japan |
Condition
Condition
The acquired mass spectrum dataset was subsequently analyzed by partial least squares (PLS) regression to find the relationship between two groups. Support vector machine (SVM), a mehod of machine learning, was applied on the dataset to construct the diagnostic algorithm.
Classification by specialty
| Cardiology |
Classification by malignancy
Others
Genomic information
NO
Objectives
Narrative objectives1
The purpose of this study is to establish a novel diagnosis system in early acute coronary syndrome (ACS) using Probe Electrospray Ionization-Mass Spectrometry (PESI-MS) and machine learning (ML) and to validate the diagnostic accuracy.
Basic objectives2
Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
The PESI-MS and ML-based diagnosis system is likely an optimal solution to assist physicians in ACS diagnosis with its remarkably predictive accuracy
Key secondary outcomes
Base
Study type
Interventional
Study design
Basic design
Single arm
Randomization
Non-randomized
Randomization unit
Blinding
Open -no one is blinded
Control
Self control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment
Intervention
No. of arms
1
Purpose of intervention
Diagnosis
Type of intervention
| Other |
Interventions/Control_1
Myocardial infarction-diagnosed patients/ ACS patients with other diagnoses
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10
Eligibility
Age-lower limit
| 20 | years-old | <= |
Age-upper limit
| 90 | years-old | >= |
Gender
Male and Female
Key inclusion criteria
ACS patients
Key exclusion criteria
Not enough data
Target sample size
32
Research contact person
Name of lead principal investigator
| 1st name | Takeshi |
| Middle name | |
| Last name | Moriguchi |
Organization
University of Yamanashi
Division name
Emergency and Critical Care Unit
Zip code
4093898
Address
1110 shimokato
TEL
0552739812
tmoriguchi@yamanashi.ac.jp
Public contact
Name of contact person
| 1st name | Que |
| Middle name | N. N. |
| Last name | Tran |
Organization
University of Yamanashi
Division name
Emergency and Critical Care Unit
Zip code
4093898
Address
1110 shimokato
TEL
0552739812
Homepage URL
g19ddm19@yamanashi.ac.jp
Sponsor or person
Institute
University of Yamanashi
Institute
Department
Personal name
Que N. N. Tran
Funding Source
Organization
University of Yamanashi
Organization
Division
Category of Funding Organization
Other
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
University of Yamanashi
Address
1110 shimokato
Tel
0552739812
tmoriguchi@yamanashi.ac.jp
Secondary IDs
Secondary IDs
NO
Study ID_1
Org. issuing International ID_1
Study ID_2
Org. issuing International ID_2
IND to MHLW
Institutions
Institutions
University of Yamanashi (Yamanashi)
Other administrative information
Date of disclosure of the study information
| 2024 | Year | 05 | Month | 12 | Day |
Related information
URL releasing protocol
Publication of results
Partially published
Result
URL related to results and publications
Number of participants that the trial has enrolled
32
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description
Progress
Recruitment status
Completed
Date of protocol fixation
| 2023 | Year | 01 | Month | 01 | Day |
Date of IRB
| 2019 | Year | 07 | Month | 08 | Day |
Anticipated trial start date
| 2023 | Year | 01 | Month | 01 | Day |
Last follow-up date
| 2023 | Year | 12 | Month | 05 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
Management information
Registered date
| 2023 | Year | 12 | Month | 05 | Day |
Last modified on
| 2023 | Year | 12 | Month | 08 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000060470
