Pre‐operative Eligibility for Minimally Invasive Coronary Artery Bypass Grafting Using the DaVinci Robot: An Examination of Anatomical Parameters using Computed Tomography
Notice bibliographique
Résumé
Introduction Minimally invasive coronary artery bypass procedures have been shown to reduce morbidity, 30‐day complication rates, and length of hospital stays, as well as increasing patient quality of life scores post‐operatively. The robotic‐assisted endoscopic single‐vessel small thoracotomy (endo‐SVST) bypass procedure is a minimally invasive procedure that confers similar benefits to the more invasive conventional full‐sternotomy revascularization approach. A limitation to the endo‐SVST procedure that still requires attention is the pre‐operative selection criteria. Inappropriate selection can result in intra‐operative conversions from the endo‐SVST to a conventional full‐sternotomy resulting in increased patient morbidity, and both operative and general anesthetic times along with increased costs. One of the primary intraoperative concerns, necessitating conversion to a conventional full‐sternotomy, is the inability of the endoscopic camera to visualize the left anterior descending (LAD) coronary artery, the target vessel, under the surrounding epicardial adipose tissue. The purpose of this study is to determine if anatomical and anthropometric parameters, examined using both patient data and pre‐operative computed tomography (CT) images, are able to predict and thus reduce the need for conversion based on effective pre‐operative exclusion criteria. Methods Retrospective analysis of patient pre‐operative CT angiography scans from both converted (N=13) and robotic‐assisted (N=13) procedures using the DaVinci Surgical Robot was performed. Patient scans were anonymized and measurements were made using 3D Slicer 4.4.0. Where possible, measurements of thoracic cavity dimensions and epicardial adipose depths were acquired from axial slices, at the most accessible segment of the LAD, in the fourth anterior intercostal space. An independent‐samples Student T Test (∝=0.05) and Pearson Correlation (∝=0.05) were performed using SPSS. Results Preliminary results indicate that patients who successfully underwent the endo‐SVST procedure had significantly less epicardial adipose tissue (p=0.03) overlying the LAD in the transverse measurement than those who were converted to the full‐sternotomy intra‐operatively. This data also suggests that there are no significant differences between the two groups with respect to the remaining epicardial adipose tissue and anthropometric measurements. A moderate, but non‐significant, positive correlation R=0.36 (p=0.07) appears to exist between body mass index (BMI) and the depth of epicardial adipose tissue within the anterior inter‐ventricular sulcus. Discussion These data suggest that a transverse depth measurement of epicardial adipose tissue overlying the LAD of 7.6±3.3mm may indicate a greater risk for conversion to the full‐sternotomy. Preliminary findings also indicate that the relationship between the depth of epicardial adipose tissue and conversion to full‐sternotomy may not be fully explained by a patient's BMI. However, future studies with a larger sample size need to be conducted in order to examine the relationship between these anatomical and anthropometric parameters and to also assess whether their combined use may further enhance the precision of pre‐operative exclusion criteria.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 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 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 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 ».