ELECTROCARDIOGRAPHY AS A PART OF HEART DISEASES SCREENING DURING EPIDEMIOLOGICAL RESEARCH: CURRENT STATE, TECHNOLOGICAL TRENDS, UNRESOLVED ISSUES
Notice bibliographique
Résumé
The goal of this paper is to analyze modern views on the electrocardiography (ECG) for heart disease screening, to review the experience of using portable ECG devices, the amount and nature of information that can be obtained using ECG devices with different numbers of leads, their regulatory base, especially in the context of cardiovascular diseases (CVD) screening. The characteristics of various scales for determining serious cardiovascular events are given. It is concluded that there is a need to personalize the scale risk assessment, i.e. to supplement the traditional risk factors with individual physiologically important parameters recorded using instrumental methods. The most important of these instrumental methods is ECG. A detailed description of numerous studies using ECG predictors of cardiovascular events, both in the general population and in various cohorts, is given, with an indication of their evidentiary power. The evolution of views on the indications for ECG examination of clinically healthy individuals in the course of epidemiological studies is described. Miniature portable electrocardiographic devices that are used by the patient outside the doctor's office as part of a broader trend, point-of-care testing (POCT), i.e. a medical test performed directly at the patient's location, outside the doctor's office, are considered. These are mainly single-channel electrocardiographs with finger electrodes: AfibAlert (USA), AliveCor / Kardia (USA), DiCare (China), ECG Check (USA), HeartCheck Pen (Canada), InstantCheck (Taiwan), MD100E (China), PC -80 (China). REKA E 100 (Singapore), Zenicor (Sweden), Omron Heart Scan (Japan), MDK (Holland). The experience of AliveCor / Kardia in the context of successive obtaining of several FDA approvals is especially considered. The features of screening for cardiovascular diseases using ECG devices with a limited number of leads are analyzed. The original electrocardiographic hardware and software complexes created at the Glushkov Institute of Cybernetics of National Academy of Science of Ukraine are described. The uniqueness of the software of these complexes is based on the analysis of subtle ECG changes that are invisible during the usual visual and/or automatic interpretation of the ECG signal. The idea of the analysis method consists, firstly, in measuring the maximum number of ECG parameters and heart rate variability, and secondly, in positioning each parameter on a scale between the absolute norm and extreme pathology. The software for these devices is structured according to a hierarchical principle. It consists of four levels – from individual particular indicators to the general integral indicator of the functional state of the cardiovascular system. When moving to higher levels of analysis, the information obtained at the previous level is generalized and aggregated. This is expressed in the averaging of all point values of all parameters of indicators of the previous level. indicators of the first level are averaged at the second level, the second – at the third, the third – at the fourth. The complex index, available in the software, is formed on the basis of assessments of generally accepted and original indicators of heart rate variability, characteristics of QRS complexes.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,020 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,001 | 0,006 |
| Communication savante | 0,005 | 0,008 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».