WO2016190723A1 - Procédé de détermination des indicateurs de risque cardiovasculaire élevé dans le cas d'obésité abdominale chez des patients de la région de la mer baltique - Google Patents

Procédé de détermination des indicateurs de risque cardiovasculaire élevé dans le cas d'obésité abdominale chez des patients de la région de la mer baltique Download PDF

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Publication number
WO2016190723A1
WO2016190723A1 PCT/LV2016/000002 LV2016000002W WO2016190723A1 WO 2016190723 A1 WO2016190723 A1 WO 2016190723A1 LV 2016000002 W LV2016000002 W LV 2016000002W WO 2016190723 A1 WO2016190723 A1 WO 2016190723A1
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WO
WIPO (PCT)
Prior art keywords
patients
cardiovascular risk
skin
central
patient
Prior art date
Application number
PCT/LV2016/000002
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English (en)
Inventor
Júlija VOICEHOVSKA
Jana JANOVSKA
Vladimirs VOICEHOVSKIS
Sergejs BABIKOVS
Olga ZUBOVA
Ludmila Ivanova
Jánis ĶÍSIS
Andrejs ŠĶESTERS
Alise SILOVA
Aivars LEJNIEKS
Original Assignee
Rígas Stradiņa Universitáte
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
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Application filed by Rígas Stradiņa Universitáte filed Critical Rígas Stradiņa Universitáte
Publication of WO2016190723A1 publication Critical patent/WO2016190723A1/fr

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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
    • A61B5/4842—Monitoring progression or stage of a disease
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/44—Detecting, measuring or recording for evaluating the integumentary system, e.g. skin, hair or nails
    • A61B5/441—Skin evaluation, e.g. for skin disorder diagnosis
    • A61B5/442—Evaluating skin mechanical properties, e.g. elasticity, hardness, texture, wrinkle assessment
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/44—Detecting, measuring or recording for evaluating the integumentary system, e.g. skin, hair or nails
    • A61B5/441—Skin evaluation, e.g. for skin disorder diagnosis
    • A61B5/444—Evaluating skin marks, e.g. mole, nevi, tumour, scar
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
    • 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
    • G16H50/80—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu

Definitions

  • the present invention relates to medicine, specifically to therapeutics, general practitioners, family doctors, cardiology, endocrinology, gerontology, dermatology.
  • Cardiovascular diseases is the main cause of death in Europe and the World [1]. Cardiovascular disease development risk factors (RF) identification and active, timely prophylaxis reduces mortality [2]. Methods for detecting cardiovascular risk parameters in patients without clinical signs is a problem in the Art.
  • Metabolic syndrome is a combination of the following clinical signs: increase in visceral fat deposition, insulin resistance, hyperinsulinemia, carbohydrate and fat metabolism disorders and arterial hypertension [3].
  • metabolic syndrome tissue inability to absorb insulin and inflammatory marker (cytokines etc.) level disorders.
  • cytokine activation FNOa, IL-6 etc.
  • endothelium dysfunction oxidative stress
  • cytokine inflammatory cascade oxidative stress
  • atherosclerosis development cytokine inflammatory cascade
  • Oxidative stress marker is malondialdehyde (MDA) and it is used to control ischemic heart diseases, metabolic syndrome and other disease treatment [6].
  • MDA malondialdehyde
  • Obesity is a disease of 21 s Century. A patient with central obesity features excessive body fat over the abdomen. A female is considered an obesity patient if her waist circumference to hip circumference ratio exceeds 0.8, when waist circumference is over 80 cm. A male is considered obese if the same ratio is over 0.99, with waist circumference over 94 cm [3]. Obesity is viewed as a chronic metabolic disease that develops in association with fatty tissue development. Endocrine pathologies, sedentary lifestyle, excessive food intake and psychotropic drug use stimulate obesity.
  • a detection of malondialdehyde allows for cardiovascular risk identification in patients with metabolic syndrome only when signs of cardiovascular damage are clinically observed. There currently is no cardiovascular risk estimation method for patients with metabolic syndrome without clinical signs.
  • SCORE scale is a method that allows for individual CVD risk estimation based on age, sex, physical activity and history of smoking. Unfortunately, this method also does not allow risk estimation in centrally obese patients without clinical signs of CVD.
  • the skin is the largest organ in human body and forms an outer shell with a surface of 1.5-2.0 m 2 and takes part in barrier, receptory, breathing, thermoregulation, metabolic and other functions of the organism.
  • the skin is also has a prominent part in maintaining immunity through keratinocytes, Langerhans cells (LCs), epidermal T- lymphocytes [8].
  • Skin keratinocytes produce a wide spectrum of regulatory molecules like keratinocytes and growth factors.
  • LCs are a specialized epidermal dendritic cells with monocyte-macrophage background and are capable of reacting with different types of T- cells and modulate immune responses.
  • the skin as an immune organ, possesses an excess of innate immunity over acquired immunity. Furthermore, innate immunity cell factors dominate over humoral regulation. Changes in cytokine production influence skin cell proliferation and differentiation and immune disorders of the skin take a pathogenetic part in numerous diseases.
  • Physicians, cardiologists, endocrinologists and gerontologists are aware of difficulties with finding an informative, noninvasive, easy-to-use method for a timely cardiovascular risk evaluation in patients with central obesity [10].
  • the method allows for detection of 2 or more skin surface appearance change combinations on the face, the neck, thorax and arms, and, if these combinations feature 6 or more papillomas, 2 or more keratosis and lentigo areas and/or 4 and more gravity wrinkles, a cardiovascular risk is measured.
  • Pigmentation disorders On inspection: lentigo-type pigmentation and/or dyschromia (light or dark patches). Lentigo (Lentigines, Naevispili) - brown, rounded pigmented patches that are slightly raised above the surface of the skin, several millimeters in diameter.
  • Papilloma is a relatively small, soft structure on a pedicle (with the colour of skin or hyperpigmented). Its size varies from 2 to 5 mm, but even bigger structures are documented.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Public Health (AREA)
  • Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Pathology (AREA)
  • Biomedical Technology (AREA)
  • Animal Behavior & Ethology (AREA)
  • Veterinary Medicine (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Biophysics (AREA)
  • Physics & Mathematics (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Databases & Information Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Dermatology (AREA)
  • Epidemiology (AREA)
  • Primary Health Care (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Physiology (AREA)
  • Psychiatry (AREA)
  • Signal Processing (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

L'invention se rapporte au domaine de la médecine, de la médecine interne, de la médecine générale, des praticiens généralistes, de la cardiologie, et de l'endocrinologie, de la gérontologie, de la dermatologie. L'invention se rapporte à un procédé non invasif valide pour l'évaluation du score de risque cardiovasculaire élevé chez des patients de la région baltique atteints d'obésité abdominale. Des modifications de 2 caractéristiques ou plus qui contribuent à l'aspect de la peau sont définies, de sorte que, si celles-ci incluent 6 à 8 ou plus papillomes, 2 ou 3 et plus de zones de kératose et de lentigo, et/ou 4 à 6 rides de gravitation, selon l'invention, il existe un risque cardiovasculaire élevé.
PCT/LV2016/000002 2015-05-27 2016-05-19 Procédé de détermination des indicateurs de risque cardiovasculaire élevé dans le cas d'obésité abdominale chez des patients de la région de la mer baltique WO2016190723A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
LVP-15-49 2015-05-27
LVP-15-49A LV15058B (lv) 2015-05-27 2015-05-27 Augsta kardiovaskulārā riska rādītāju noteikšanas paņēmiens centrālās aptaukošanās gadījumā Baltijas jūras reģiona pacientiem

Publications (1)

Publication Number Publication Date
WO2016190723A1 true WO2016190723A1 (fr) 2016-12-01

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PCT/LV2016/000002 WO2016190723A1 (fr) 2015-05-27 2016-05-19 Procédé de détermination des indicateurs de risque cardiovasculaire élevé dans le cas d'obésité abdominale chez des patients de la région de la mer baltique

Country Status (2)

Country Link
LV (1) LV15058B (fr)
WO (1) WO2016190723A1 (fr)

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140031411A1 (en) * 2010-12-01 2014-01-30 Max-Delbruck-Centrum Fur Molekulare Medizin Berlin-Buch Gpnmb/osteoactivin as a biomarker and drug target in cardiac diseases

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140031411A1 (en) * 2010-12-01 2014-01-30 Max-Delbruck-Centrum Fur Molekulare Medizin Berlin-Buch Gpnmb/osteoactivin as a biomarker and drug target in cardiac diseases

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
KUO HSU-KO ET AL.: "Human Papillomavirus and Cardiovascular Disease Among U.S. Women in the National Health and Nutrition Examination Survey, 2003 to 2006", JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY, vol. 58, no. 19, 2011, pages 2001 - 2006, XP028326505 *
LIU NAN ET AL.: "Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection.", BMC MEDICAL INFORMATICS & DECISION MAKING, vol. 14, no. 75, 2014, pages 1 - 9, XP021195892 *

Also Published As

Publication number Publication date
LV15058A (lv) 2015-10-20
LV15058B (lv) 2016-04-20

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