Response to Letter by Bladin et al
Notice bibliographique
Résumé
Measurement of Carotid Arteries to Quantify Carotid Stenosis" 1 and our related works.[2][3][4] We agree that the optimal method to quantify carotid stenosis remains somewhat controversial.All methods of carotid stenosis quantification are relatively flawed, despite the imaging modality or the statistical technique.Nonetheless, the attempts to improve this quantification have all played an important role in our understanding of carotid disease and measurement methodology.Bladen et al correctly state our message that carotid stenosis should be directly measured and individualized.We agree that we could have measured the widest portion of the carotid bulb, instead of at the level of tightest luminal stenosis.Yet, the carotid stenosis index (CSI) 5 does not involve measurement of the carotid bulb at all.Instead the CSI method relied on a presumed "fixed anatomic relationship" 5 between the common carotid artery (CCA) and the carotid bulb to provide an estimation of the widest point of the carotid bulb.This "fixed anatomic relationship" is far from fixed, with other authors reporting standard deviations ranging from Ϯ0.09 to Ϯ0.19.6 The CSI authors also report that estimations of the carotid bulb via measurement of the CCA is more accurate, because the CCA is easier to measure, is disease free and has less anatomic variation.5 With the high quality data from CTA, all vessels can be viewed and measured with the same ease, atherosclerotic disease can be identified (with qualification of plaque content), and anatomic variation is easier to identify because one CTA examination provides data for the entire neck vasculature.CTA gives high resolution imaging of all arteries as well as the soft tissue details of the arterial wall.4 The outside arterial wall can be identified consistently, despite claims to the otherwise.The wall is well demarcated from surrounding peri-arterial fat, and from different densities of intraluminal plaque.There are technical choices that need to be considered to properly evaluate the arteries as we have described.[1][2][3][4] Specifically, this involves the rewindowing of images using a digital PACS system, rather than interpretation from filmed images.For now, carotid quantification methods will most likely remain individualized by regional and individual healthcare centers and physicians, depending on the mix of available technologies, resources and local expertise.One of the goals of our work was to introduce CTA as yet another method to quantify carotid stenosis.CTA has become the preferred angiographic modality at our center, and many others, because of its lack of stroke risk, ability to directly measure in millimeters, ease of standardization of CTA, the quickness of the examination (seconds to acquire images from the aortic arch to vertex), low demand of labor-intensive resources, and the high quality data produced.Catheter angiography is no longer the "gold standard" in identifying carotid stenosis.Current CTA techniques allow for direct quantification and visualization of the neck vasculature from the arch through vertex in only a few seconds.CTA technology is readily available, can be performed by a single qualified technologist, and provides high quality data that was previously only available through catheter angiography, however, without risk of stroke.
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 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 | 0,004 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,005 | 0,003 |
| Communication savante | 0,005 | 0,003 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,085 | 0,045 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,016 |
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 ».