WO2022173201A3 - Procédé de pronostic du diabète sucré de type 2 après une chirurgie du cancer de l'estomac - Google Patents
Procédé de pronostic du diabète sucré de type 2 après une chirurgie du cancer de l'estomac Download PDFInfo
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- 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
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- WIPO (PCT)
- Prior art keywords
- stomach cancer
- diabetes mellitus
- cancer surgery
- diabetes
- prognosis
- Prior art date
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- 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
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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
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
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- 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
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- 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
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- 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
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- 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
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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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
- 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
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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
- G16H50/20—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
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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
- G16H50/30—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
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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
- G16H50/70—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)
- Heart & Thoracic Surgery (AREA)
- Molecular Biology (AREA)
- Surgery (AREA)
- Veterinary Medicine (AREA)
- Animal Behavior & Ethology (AREA)
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- Databases & Information Systems (AREA)
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- Physiology (AREA)
- Software Systems (AREA)
- Cardiology (AREA)
- Theoretical Computer Science (AREA)
- Neurosurgery (AREA)
- Psychology (AREA)
- Optics & Photonics (AREA)
- Artificial Intelligence (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Vascular Medicine (AREA)
- Mathematical Physics (AREA)
- Computing Systems (AREA)
- General Physics & Mathematics (AREA)
- Developmental Disabilities (AREA)
- Psychiatry (AREA)
- Hospice & Palliative Care (AREA)
- Child & Adolescent Psychology (AREA)
- Emergency Medicine (AREA)
Abstract
La présente invention divulgue un procédé de pronostic du diabète sucré de type 2 après une chirurgie du cancer de l'estomac. Le procédé comprend les étapes dans lesquelles : (a) une partie de classification de cible classifie une population de patients cibles en un groupe de base et un groupe de vérification selon la période de chirurgie du cancer de l'estomac; (b) une partie de sélection de variables sélectionne une variable préopératoire pour effectuer un pronostic du diabète sucré pendant une certaine période de temps après une chirurgie du cancer de l'estomac dans les groupes de patients cibles classifiés; (c) une partie de calcul de score reçoit les variables préopératoires sélectionnées et calcule un score de prédiction de diabète pour évaluer des symptômes progressifs du diabète en fonction de la valeur de référence de chaque variable; et (d) une partie de vérification de capacité de prédiction reçoit le score de prédiction de diabète calculé et calcule la zone sous la courbe caractéristique d'opération de récepteur pour le groupe de base et le groupe de vérification pour vérifier l'utilité du système de score. Selon la présente invention, diverses procédures de progression du diabète sucré de type 2 qui peuvent se produire après une chirurgie du cancer de l'estomac peuvent être efficacement prédites, ce qui permet d'améliorer considérablement la gestion pertinente des taux de glycémie et d'empêcher les effets secondaires attribués à des prescriptions répétées de médicaments pour le diabète sucré après une chirurgie.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
KR1020210018747A KR102510347B1 (ko) | 2021-02-10 | 2021-02-10 | 위암 수술 이후 제2형 당뇨병 예후의 예측 방법 |
KR10-2021-0018747 | 2021-02-10 |
Publications (2)
Publication Number | Publication Date |
---|---|
WO2022173201A2 WO2022173201A2 (fr) | 2022-08-18 |
WO2022173201A3 true WO2022173201A3 (fr) | 2022-10-06 |
Family
ID=82837800
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Application Number | Title | Priority Date | Filing Date |
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PCT/KR2022/001945 WO2022173201A2 (fr) | 2021-02-10 | 2022-02-09 | Procédé de pronostic du diabète sucré de type 2 après une chirurgie du cancer de l'estomac |
Country Status (2)
Country | Link |
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KR (1) | KR102510347B1 (fr) |
WO (1) | WO2022173201A2 (fr) |
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 (ko) * | 2016-12-30 | 2018-07-10 | 서울대학교산학협력단 | 대사이상 질환의 질병 위험도를 예측하는 장치 및 방법 |
KR20190062461A (ko) * | 2016-09-28 | 2019-06-05 | 미디얼 리서치 리미티드 | 의료 데이터 마이닝을 위한 시스템 및 방법 |
KR20210001959A (ko) * | 2019-06-27 | 2021-01-06 | 서울대학교산학협력단 | 위암의 다층 다요인 패널과 Computational biological network modeling을 통한 위암 발암에 대한 에티옴 모형 |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2011528117A (ja) | 2008-07-15 | 2011-11-10 | メタノミクス ヘルス ゲーエムベーハー | 胃バイパス及びそれに関連する状態を診断する手段及び方法 |
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2021
- 2021-02-10 KR KR1020210018747A patent/KR102510347B1/ko active IP Right Grant
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2022
- 2022-02-09 WO PCT/KR2022/001945 patent/WO2022173201A2/fr 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 (ko) * | 2016-09-28 | 2019-06-05 | 미디얼 리서치 리미티드 | 의료 데이터 마이닝을 위한 시스템 및 방법 |
KR20180079208A (ko) * | 2016-12-30 | 2018-07-10 | 서울대학교산학협력단 | 대사이상 질환의 질병 위험도를 예측하는 장치 및 방법 |
KR20210001959A (ko) * | 2019-06-27 | 2021-01-06 | 서울대학교산학협력단 | 위암의 다층 다요인 패널과 Computational biological network modeling을 통한 위암 발암에 대한 에티옴 모형 |
Non-Patent Citations (1)
Title |
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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 |
---|---|
KR20220115723A (ko) | 2022-08-18 |
WO2022173201A2 (fr) | 2022-08-18 |
KR102510347B1 (ko) | 2023-03-20 |
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