Dynamic handgrip exercise for the detection of myocardial ischemia using fast Strain-ENCoded cardiovascular magnetic resonance
Notice bibliographique
Résumé
Previous data suggests dynamic handgrip exercise (DHE) as a potential physiological, needle-free stressor feasible for cardiovascular magnetic resonance (CMR) conditions. DHE-fast Strain-ENCoded imaging (fSENC) is potentially cost-saving, ultra-fast and avoids pharmacological side effects thereby targeting the drawbacks of conventional pharmacological stress CMR. To assess the diagnostic accuracy of DHE-fSENC for detecting ischemia-related wall motion abnormalities in suspected obstructive coronary artery disease (CAD). Patients with known or suspected obstructive CAD referred for CMR stress testing were prospectively enrolled. Diagnostic accuracy was assessed in comparison to pharmacological stress CMR and in a subgroup, compared to invasive coronary angiography (ICA). The CMR protocol was extended by both-handed DHE with 80 repetitions per minute over 2 minutes followed by fSENC short-axis acquisition before pharmacological stress testing. Stress-induced impairment of regional longitudinal strain was graded suspicious for obstructive CAD. Two-hundred sixty individuals with cardiovascular high-risk profile (64±13 years, 75% male) were enrolled. DHE-fSENC provided a sensitivity of 79% (95% CI: 64-89) and specificity of 87% (95% CI 82-91) compared to pharmacological stress CMR. In a subgroup of 105 patients with recent ICA, high diagnostic accuracy was found for the detection of obstructive CAD (sensitivity 82% (95% CI: 67-92), specificity 89% (95% CI: 78-95)). Exam duration of DHE-fSENC was significantly reduced compared to conventional CMR stress protocols (DHE-fSENC 207±69 sec vs. adenosine-perfusion 287±82 sec vs. dobutamine-cine 1132±294 sec, all p< 0.001). DHE-fSENC allows for a reliable and fast detection of obstructive CAD, thereby expanding the applicability of needle-free CMR stress testing. Dynamic handgrip exercise and fast Strain-ENCoded imaging. Schematic visualization of the both-sided, dynamic handgrip exercise at approx. 50% of MVC and a frequency of 80/min including fSENC acquisition at rest and during DHE. The comparison between fSENC at rest and after DHE of the apical slice in this example shows an impairment of LS after DHE of the inferior apical wall. DHE and fSENC acquisition was integrated into CMR routine protocol and was performed before pharmacological stress. DHE-fSENC: response of longitudinal strain. Comparison of LS at rest and during DHE. In ischemic segments, longitudinal strain was significantly impaired during DHE. In contrast, LS was more pronounced during DHE in non-ischemic segments. DHE-fSENC: test accuracy compared to pharmacological stress CMR. Test accuracy of DHE-fSENC compared to pharmacological stress CMR was excellent with a sensitivity of 79% (64-89) and a specificity of 87% (82-91). CMR = cardiac magnetic resonance imaging; DHE = dynamic handgrip exercise; fSENC = fast Strain-ENCoded imaging; LS = longitudinal strain; MVC = maximum voluntary contraction; NPV = negative predictive value; PPV = positive predictive value; SEM = standard error of the mean.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,005 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».