WO2022173201A3 - Method for prognosis of type 2 diabetes mellitus after stomach cancer surgery - Google Patents
Method for prognosis of type 2 diabetes mellitus after stomach cancer surgery Download PDFInfo
- Publication number
- WO2022173201A3 WO2022173201A3 PCT/KR2022/001945 KR2022001945W WO2022173201A3 WO 2022173201 A3 WO2022173201 A3 WO 2022173201A3 KR 2022001945 W KR2022001945 W KR 2022001945W WO 2022173201 A3 WO2022173201 A3 WO 2022173201A3
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- stomach cancer
- diabetes mellitus
- cancer surgery
- diabetes
- prognosis
- Prior art date
Links
- 238000001356 surgical procedure Methods 0.000 title abstract 6
- 208000005718 Stomach Neoplasms Diseases 0.000 title abstract 5
- 206010017758 gastric cancer Diseases 0.000 title abstract 5
- 201000011549 stomach cancer Diseases 0.000 title abstract 5
- 238000000034 method Methods 0.000 title abstract 4
- 238000004393 prognosis Methods 0.000 title abstract 3
- 208000001072 type 2 diabetes mellitus Diseases 0.000 title abstract 3
- 206010012601 diabetes mellitus Diseases 0.000 abstract 5
- 238000012795 verification Methods 0.000 abstract 3
- 239000008280 blood Substances 0.000 abstract 1
- 210000004369 blood Anatomy 0.000 abstract 1
- 239000003814 drug Substances 0.000 abstract 1
- 229940079593 drug Drugs 0.000 abstract 1
- 230000000694 effects Effects 0.000 abstract 1
- 230000000750 progressive effect Effects 0.000 abstract 1
- 208000024891 symptom Diseases 0.000 abstract 1
Classifications
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/021—Measuring pressure in heart or blood vessels
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4058—Detecting, measuring or recording for evaluating the nervous system for evaluating the central nervous system
- A61B5/4064—Evaluating the brain
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4076—Diagnosing or monitoring particular conditions of the nervous system
- A61B5/4088—Diagnosing of monitoring cognitive diseases, e.g. Alzheimer, prion diseases or dementia
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4869—Determining body composition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
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- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Pathology (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- Biophysics (AREA)
- Veterinary Medicine (AREA)
- Animal Behavior & Ethology (AREA)
- Heart & Thoracic Surgery (AREA)
- Surgery (AREA)
- Molecular Biology (AREA)
- Databases & Information Systems (AREA)
- Neurology (AREA)
- Physiology (AREA)
- Theoretical Computer Science (AREA)
- Software Systems (AREA)
- Cardiology (AREA)
- Psychology (AREA)
- Neurosurgery (AREA)
- Optics & Photonics (AREA)
- Computing Systems (AREA)
- Vascular Medicine (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Mathematical Physics (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Emergency Medicine (AREA)
- Developmental Disabilities (AREA)
- Hospice & Palliative Care (AREA)
- Psychiatry (AREA)
- Child & Adolescent Psychology (AREA)
Abstract
The present invention discloses a method for prognosis of type 2 diabetes mellitus after stomach cancer surgery. The method comprises the steps in which: (a) a target classification part classifies a target patient population into a basic group and a verification group according to the period of stomach cancer surgery; (b) a variable selection part selects a preoperative variable to make a prognosis of diabetes mellitus for a certain period of time after stomach cancer surgery in the classified target patient groups; (c) a score calculation part is provided with the selected preoperative variables and calculates a diabetes prediction score to evaluate progressive symptoms of diabetes according to the reference value of each variable; and (d) a prediction ability verification part is provided with the calculated diabetes prediction score and calculates the area under receiver operation characteristic curve for the basic group and the verification group to verify usefulness of the score system. According to the present invention, various progression procedures of type 2 diabetes mellitus which may occur after stomach cancer surgery can be effectively predicted, whereby pertinent management of blood sugar levels can be remarkably improved and the side effects attributed to repeated prescriptions of drugs for diabetes mellitus after surgery can be prevented.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
KR1020210018747A KR102510347B1 (en) | 2021-02-10 | 2021-02-10 | A method for predicting the prognosis of type 2 diabetes after gastric cancer surgery |
KR10-2021-0018747 | 2021-02-10 |
Publications (2)
Publication Number | Publication Date |
---|---|
WO2022173201A2 WO2022173201A2 (en) | 2022-08-18 |
WO2022173201A3 true WO2022173201A3 (en) | 2022-10-06 |
Family
ID=82837800
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/KR2022/001945 WO2022173201A2 (en) | 2021-02-10 | 2022-02-09 | Method for prognosis of type 2 diabetes mellitus after stomach cancer surgery |
Country Status (2)
Country | Link |
---|---|
KR (1) | KR102510347B1 (en) |
WO (1) | WO2022173201A2 (en) |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20150332020A1 (en) * | 2014-05-16 | 2015-11-19 | Corcept Therapeutics, Inc. | Systems and methods of managing treatment of a chronic condition by symptom tracking |
KR20180079208A (en) * | 2016-12-30 | 2018-07-10 | 서울대학교산학협력단 | Apparatus and method for predicting disease risk of metabolic disease |
KR20190062461A (en) * | 2016-09-28 | 2019-06-05 | 미디얼 리서치 리미티드 | System and method for medical data mining |
KR20210001959A (en) * | 2019-06-27 | 2021-01-06 | 서울대학교산학협력단 | Etiome model for gastric cancer development based on multi-layer ad multi-factor panel and computational biological network modeling |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP2313773A1 (en) | 2008-07-15 | 2011-04-27 | Metanomics Health GmbH | Means and methods diagnosing gastric bypass and conditions related thereto |
-
2021
- 2021-02-10 KR KR1020210018747A patent/KR102510347B1/en active IP Right Grant
-
2022
- 2022-02-09 WO PCT/KR2022/001945 patent/WO2022173201A2/en active Application Filing
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20150332020A1 (en) * | 2014-05-16 | 2015-11-19 | Corcept Therapeutics, Inc. | Systems and methods of managing treatment of a chronic condition by symptom tracking |
KR20190062461A (en) * | 2016-09-28 | 2019-06-05 | 미디얼 리서치 리미티드 | System and method for medical data mining |
KR20180079208A (en) * | 2016-12-30 | 2018-07-10 | 서울대학교산학협력단 | Apparatus and method for predicting disease risk of metabolic disease |
KR20210001959A (en) * | 2019-06-27 | 2021-01-06 | 서울대학교산학협력단 | Etiome model for gastric cancer development based on multi-layer ad multi-factor panel and computational biological network modeling |
Non-Patent Citations (1)
Title |
---|
KIM JONG WON, CHEONG JAE-HO, HYUNG WOO JIN, CHOI SEUNG-HO, HOON SUNG, JONG NOH, KIM WON, JW KIM, JH CHEONG, WJ HYUNG, SH CHOI, NOH: "Outcome after gastrectomy in gastric cancer patients with type 2 diabetes", WORLD JOURNAL OF GASTROENTEROLOGY, WJG PRESS, CN, vol. 18, no. 1, 1 January 2012 (2012-01-01), CN , pages 49, XP055972779, ISSN: 1007-9327, DOI: 10.3748/wjg.v18.i1.49 * |
Also Published As
Publication number | Publication date |
---|---|
KR102510347B1 (en) | 2023-03-20 |
WO2022173201A2 (en) | 2022-08-18 |
KR20220115723A (en) | 2022-08-18 |
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