MX2020009705A - Metodos para la deteccion del riesgo de enfermedad renal cronica en un sujeto y metodo implementado por computadora. - Google Patents

Metodos para la deteccion del riesgo de enfermedad renal cronica en un sujeto y metodo implementado por computadora.

Info

Publication number
MX2020009705A
MX2020009705A MX2020009705A MX2020009705A MX2020009705A MX 2020009705 A MX2020009705 A MX 2020009705A MX 2020009705 A MX2020009705 A MX 2020009705A MX 2020009705 A MX2020009705 A MX 2020009705A MX 2020009705 A MX2020009705 A MX 2020009705A
Authority
MX
Mexico
Prior art keywords
subject
risk
screening
kidney disease
chronic kidney
Prior art date
Application number
MX2020009705A
Other languages
English (en)
Inventor
Alexander Buesser
Tony Huschto
Wolfgang Petrich
Stefan Ravizza
Bernd Schneidinger
Original Assignee
Hoffmann La Roche
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from EP18163573.1A external-priority patent/EP3543702B1/en
Application filed by Hoffmann La Roche filed Critical Hoffmann La Roche
Publication of MX2020009705A publication Critical patent/MX2020009705A/es

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Classifications

    • 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
    • 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
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
    • G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00—ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression
    • 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
    • G16H50/50—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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/34—Genitourinary disorders
    • G01N2800/347—Renal failures; Glomerular diseases; Tubulointerstitial diseases, e.g. nephritic syndrome, glomerulonephritis; Renovascular diseases, e.g. renal artery occlusion, nephropathy
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2800/00—Detection or diagnosis of diseases
    • G01N2800/54—Determining the risk of relapse
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Public Health (AREA)
  • Physics & Mathematics (AREA)
  • Molecular Biology (AREA)
  • Data Mining & Analysis (AREA)
  • Pathology (AREA)
  • Primary Health Care (AREA)
  • Epidemiology (AREA)
  • Hematology (AREA)
  • Chemical & Material Sciences (AREA)
  • Urology & Nephrology (AREA)
  • Immunology (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Biotechnology (AREA)
  • Biophysics (AREA)
  • Proteomics, Peptides & Aminoacids (AREA)
  • Cell Biology (AREA)
  • Biochemistry (AREA)
  • Analytical Chemistry (AREA)
  • Medicinal Chemistry (AREA)
  • Food Science & Technology (AREA)
  • Microbiology (AREA)
  • Artificial Intelligence (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • Software Systems (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Mathematical Physics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Genetics & Genomics (AREA)
  • Computational Linguistics (AREA)
  • General Engineering & Computer Science (AREA)
  • Computing Systems (AREA)

Abstract

La descripción se refiere a un método para cribar a un sujeto en cuanto al riesgo de enfermedad renal crónica (CKD), que comprende: recibir datos de marcadores indicativos de una pluralidad de parámetros de marcadores para un sujeto, indicando la pluralidad de parámetros de marcadores, para el sujeto para una medición período, un valor de la edad, un nivel de muestreo de la creatinina y un nivel de muestreo de la albúmina; y determinar un factor de riesgo indicativo del riesgo de padecer CKD para el sujeto a partir de la pluralidad de parámetros marcadores, en donde la determinación comprende: ponderar el valor de la edad por encima del nivel de albúmina de la muestra, y ponderar el nivel de creatinina de la muestra por encima de la muestra nivel de albúmina. Además, se proporciona un método implementado por ordenador para cribar un sujeto y un método para cribar un sujeto en cuanto al riesgo de enfermedad renal crónica (CKD).
MX2020009705A 2018-03-23 2019-03-22 Metodos para la deteccion del riesgo de enfermedad renal cronica en un sujeto y metodo implementado por computadora. MX2020009705A (es)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
EP18163573.1A EP3543702B1 (en) 2018-03-23 2018-03-23 Methods for screening a subject for the risk of chronic kidney disease and computer-implemented method
EP19150615 2019-01-07
PCT/EP2019/057297 WO2019180232A1 (en) 2018-03-23 2019-03-22 Methods for screening a subject for the risk of chronic kidney disease and computer-implemented method

Publications (1)

Publication Number Publication Date
MX2020009705A true MX2020009705A (es) 2020-10-07

Family

ID=65802112

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2020009705A MX2020009705A (es) 2018-03-23 2019-03-22 Metodos para la deteccion del riesgo de enfermedad renal cronica en un sujeto y metodo implementado por computadora.

Country Status (10)

Country Link
US (1) US20210118570A1 (es)
EP (1) EP3769086A1 (es)
KR (1) KR20200135444A (es)
CN (1) CN112105933A (es)
AU (1) AU2019238388A1 (es)
BR (1) BR112020019087A2 (es)
CA (1) CA3094294A1 (es)
MX (1) MX2020009705A (es)
RU (1) RU2020134037A (es)
WO (1) WO2019180232A1 (es)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP4060347A1 (en) * 2021-03-15 2022-09-21 F. Hoffmann-La Roche AG Method for screening a subject for the risk of chronic kidney disease and computer-implemented method
CN115148375B (zh) * 2022-08-31 2022-11-15 之江实验室 一种高通量真实世界药物有效性与安全性评价方法及系统
CN117711619A (zh) * 2023-12-15 2024-03-15 南方医科大学南方医院 一种糖尿病患者慢性肾脏病发生风险预测系统及存储介质

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB201214440D0 (en) * 2012-08-13 2012-09-26 Randox Lab Ltd Kidney disease biomarker
EP2746769A1 (en) * 2012-12-21 2014-06-25 Stembios Technologies, Inc. Method for evaluating effect of action on subject based on stem celldynamics
GB201404789D0 (en) * 2014-03-18 2014-04-30 Univ Dundee Biomarkers
RU2733471C2 (ru) * 2015-04-24 2020-10-01 Сфинготек Гмбх Способ прогнозирования риска развития хронического заболевания почек

Also Published As

Publication number Publication date
US20210118570A1 (en) 2021-04-22
RU2020134037A (ru) 2022-04-26
BR112020019087A2 (pt) 2020-12-29
EP3769086A1 (en) 2021-01-27
AU2019238388A1 (en) 2020-10-15
WO2019180232A1 (en) 2019-09-26
CN112105933A (zh) 2020-12-18
KR20200135444A (ko) 2020-12-02
CA3094294A1 (en) 2019-09-26

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