MétaCan
Menu
Retour à la cohorte
Enregistrement W2256311774 · doi:10.1111/jch.12782

A Call to Regulate Manufacture and Marketing of Blood Pressure Devices and Cuffs: A Position Statement From the World Hypertension League, International Society of Hypertension and Supporting Hypertension Organizations

2016· article· en· W2256311774 sur OpenAlexaff
Norm R.C. Campbell, Mark Gelfer, George S. Stergiou, Bruce S. Alpert, Martin G. Myers, Michael Rakotz, Raj Padwal, Aletta E. Schutte, Eoin OʼBrien, Daniel T. Lackland, Mark L. Niebylski, Peter M Nilsson, Kimbree A. Redburn, Xinhua Zhang, Louise M. Burrell, Masatsugu Horiuchi, Neil R Poulter, Dorairaj Prabhakaran, Agustín J. Ramiréz, Ernesto L. Schiffrin, Rhian M. Touyz, Ji‐Guang Wang, Michael A. Weber

Notice bibliographique

RevueJournal of Clinical Hypertension · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueBlood Pressure and Hypertension Studies
Établissements canadiensUniversity of AlbertaSunnybrook Health Science CentreHealth Sciences CentreUniversity of British ColumbiaLibin Cardiovascular Institute of AlbertaUniversity of Calgary
Organismes subventionnairesBritish Heart FoundationAVITA MedicalOMRON Corporation
Mots-clésAuscultationMedicineMicrophoneBlood pressurePulse wave velocityCuffPosition statementCardiologyInternal medicineSound pressureComputer scienceSurgeryTelecommunications

Résumé

récupéré en direct d'OpenAlex

Nearly all automated blood pressure (BP) measurement devices assess BP by the oscillometric technique.1, 2 Oscillometric BP readings are derived by measuring the maximal oscillations of the composite pulse wave in the BP cuff, which corresponds to the mean arterial pressure. Systolic and diastolic BP are then estimated by points along the composite pulse wave, using an algorithm that is proprietary to each manufacturer and device. Hence, there is a need to ensure that the estimated BP by automated oscillometric devices reflects BP measured by auscultation. A few automated devices use auscultation to assess Korotkoff sounds by using a microphone.2 Microphones may capture different sound wave lengths and sound intensity than the human ear and there is a potential for sound artifacts to be recorded by automated devices as Korotkoff sounds. Therefore, automated devices that operate using microphones to assess Korotkoff sounds also require an assessment of their ability to estimate BP accurately. An international validation standard and several protocols have been developed to test the ability of automated devices to assess BP accurately in the general public, as well as in special populations, such as children or pregnant women, and special conditions such as arrhythmias.1,3-7 Factors that need to be considered for validation include microphone sensitivity, cuff size, appropriate algorithms, and the reliability and reproducibility of BP readings. Many manufacturers have developed devices that have been rigorously tested by independent investigators by using one or more of these test procedures. Scientists, clinicians, and the public can be reassured that these devices are likely to be accurate in the populations tested. Other devices have been tested independently but the test results were not published. Many government approval agencies do not require independent validation of accuracy according to established validation standards/protocols as mentioned above; rather, they rely only on the manufacturers to show that they have done accuracy tests internally. Furthermore, some validation testing may not include enough people with a wide range of arm sizes to ensure accurate readings in people with small or large arm sizes.8 Thus, many devices currently available on the market for self-monitoring of BP at home or for professional use in the office or hospital have: (1) not been tested independently according to the international standard or a national protocol; (2) have failed independent validation studies; or (3) may not produce accurate readings in those with small or large arms but are still marketed.2 The accuracy of these devices is not assured, and, for devices that fail validation standards, inaccurate BP readings and thereby incorrect treatment decisions are likely. The manufacture and sale of BP measurement cuffs are also problematic. The issues apply not only to automated but also manual auscultatory devices. With the exception of cuffs that automatically adjust for a wide range of arm sizes,9, 10 an accurate BP assessment requires the selection of an appropriate cuff size according to the individual's arm circumference.11 In general, this requires cuffs to be marked with the range of arm circumferences on which the cuff will be able to be used to assess BP accurately. However, some cuffs are not marked, and some may be inaccurately marked. Further, claims that “one size cuff fits all” may not have been validated in studies that had patients with a wide range of arm sizes. Clinicians can manually mark cuffs for the range of arm sizes on which they are likely to be accurate and can also manually assess individual arm circumferences to see what cuff would be proper. Unfortunately, these procedures are time-consuming and rarely done in clinical practice. Ensuring that all BP cuffs, when manufactured, are accurately marked for the range of arm sizes to be used for accurate BP assessment is a crucial and simple step for resolving this problem. Ensuring that the devices have a wide range of cuff sizes and that the devices are validated with the range of cuffs sizes available is also important. Notwithstanding the relevant issues regarding arm sizes, the use of wrist devices to assess BP is becoming more popular. This is likely attributable to ease of use (eg, namely, no need to measure arm circumferences), cost, and usability in obese individuals with cone-shaped upper arms. There are, however, several challenges when using these devices, including that the wrist be held at heart level—an aspect that is not adhered to in many instances. Furthermore, a large proportion of these low-cost devices are not validated according to the described procedures, and, as a rule, are generally not advised to be used as a first option because of overestimation or underestimation of BP. Dr Mark Niebylski and Kimbree Redburn are paid WHL consultants but report no other conflicts. Dr Ji-Guang Wang reports receiving research grants and consulting fees from several BP measuring device companies including A&D, AVITA, Honsun, Omron, and Rossmax but reports no other conflicts. Dr Michael Weber is a consultant for and received travel support from Omron but reports no other conflicts. All other primary authors including those from WHL and the ISH report no conflicts of interest.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,031
score de la tête « metaresearch » (Gemma)0,045
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,073
Score d'incertitude au seuil0,164

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0310,045
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,004
Bibliométrie0,0020,001
Études des sciences et des technologies0,0050,005
Communication savante0,0090,008
Science ouverte0,0060,005
Intégrité de la recherche0,0730,040
Charge utile insuffisante (le modèle a refusé de juger)0,0280,033

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.

Tête enseignante Opus0,048
Tête enseignante GPT0,327
Écart entre enseignants0,280 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations44
Publié2016
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueJournal of Clinical HypertensionMême sujetBlood Pressure and Hypertension StudiesTravaux en français237 207