scholarly journals Characteristics that define high risk in carotid endarterectomy from the Vascular Study Group of New England

2015 ◽  
Vol 62 (4) ◽  
pp. 929-936 ◽  
Author(s):  
Lindsay Gates ◽  
Robert Botta ◽  
Felix Schlosser ◽  
Philip Goodney ◽  
Margriet Fokkema ◽  
...  
Keyword(s):  
High Risk ◽  
New England ◽  
Carotid Endarterectomy ◽  
Study Group

scholarly journals Shared Quality Data Results in Increased Protamine Use and Reduced Bleeding Complications After Carotid Endarterectomy in the Vascular Study Group of New England

2012 ◽  
Vol 56 (5) ◽  
pp. 1476
Author(s):  
Reshma B. Patel ◽  
Peter Beaulieu ◽  
Philip P. Goodney ◽  
Andrew C. Stanley ◽  
Jack L. Cronenwett ◽  
...  
Keyword(s):  
New England ◽  
Carotid Endarterectomy ◽  
Quality Data ◽  
Bleeding Complications ◽  
Study Group

External validation of the Vascular Study Group of New England carotid endarterectomy risk predictive model using an independent U.S. national surgical database

2020 ◽  
Vol 71 (6) ◽  
pp. 1954-1963
Author(s):  
Mohammad H. Eslami ◽  
Zein Saadeddin ◽  
Alik Farber ◽  
Larry Fish ◽  
Efthymios D. Avgerinos ◽  
...  
Keyword(s):  
New England ◽  
Carotid Endarterectomy ◽  
Predictive Model ◽  
External Validation ◽  
Study Group

scholarly journals Completion imaging after carotid endarterectomy in the Vascular Study Group of New England

2011 ◽  
Vol 54 (2) ◽  
pp. 376-385.e3 ◽  
Author(s):  
Jessica B. Wallaert ◽  
Philip P. Goodney ◽  
John J. Vignati ◽  
David H. Stone ◽  
Brian W. Nolan ◽  
...  
Keyword(s):  
New England ◽  
Carotid Endarterectomy ◽  
Study Group

scholarly journals Shared quality data are associated with increased protamine use and reduced bleeding complications after carotid endarterectomy in the Vascular Study Group of New England

2013 ◽  
Vol 58 (6) ◽  
pp. 1518-1524.e1 ◽  
Author(s):  
Reshma B. Patel ◽  
Peter Beaulieu ◽  
Karen Homa ◽  
Philip P. Goodney ◽  
Andrew C. Stanley ◽  
...  
Keyword(s):  
New England ◽  
Carotid Endarterectomy ◽  
Quality Data ◽  
Bleeding Complications ◽  
Study Group

Outcome of carotid endarterectomy under local anaesthesia with respect to the patients’ risk profile

VASA ◽  
2009 ◽  
Vol 38 (3) ◽  
pp. 225-233 ◽  
Author(s):  
Aleksic ◽  
Luebke ◽  
Brunkwall
Keyword(s):  
Myocardial Infarction ◽  
High Risk ◽  
Carotid Endarterectomy ◽  
Complication Rate ◽  
Local Anaesthesia ◽  
High Risk Group ◽  
High Risk Patients ◽  
Hostile Neck ◽  
Risk Patients ◽  
Angioplasty And Stenting

Background: In the present study the perioperative complication rate is compared between high- and low-risk patients when carotid endarterectomy (CEA) is routinely performed under local anaesthesia (LA). Patients and methods: From January 2000 through June 2008 1220 consecutive patients underwent CEA under LA. High-risk patients fulfilled at least one of the following characteristics: ASA 4 classification, “hostile neck”, recurrent ICA stenosis, contralateral ICA occlusion, age ≥ 80 years. The combined complication rate comprised any new neurological deficit (TIA or stroke), myocardial infarction or death within 30 days after CEA, which was compared between patient groups. Results: Overall 309 patients (25%) were attributed to the high-risk group, which differed significantly regarding sex distribution (more males: 70% vs. 63%, p = 0,011), neurological presentation (more asymptomatic: 72% vs. 62%, p = 0,001) and shunt necessity (33% vs. 14%, p < 0,001). In 32 patients 17 TIAs and 15 strokes were observed. In 3 patients a myocardial infarction occurred. Death occurred in one patient following a stroke and in another patient following myocardial infarction, leading to a combined complication rate of 2,9% (35/1220). In the multivariate analysis only previous neurological symptomatology (OR 2,85, 95% CI 1,38-5,91) and intraoperative shunting (OR 5,57, 95% CI 2,69-11,55) were identified as independent risk factors for an increased combined complication rate. Conclusions: With the routine use of LA, CEA was not associated with worse outcome in high-risk patients. Considering the data reported in the literature, it does not appear justified to refer high-risk patients principally to carotid angioplasty and stenting (CAS) when LA can be chosen to perform CEA.

Aortic arch calcification is strongly associated with coronary artery calcification

VASA ◽  
2015 ◽  
Vol 44 (2) ◽  
pp. 106-114 ◽  
Author(s):  
Adem Adar ◽  
Hakan Erkan ◽  
Tayyar Gokdeniz ◽  
Aysegul Karadeniz ◽  
Ismail G. Cavusoglu ◽  
...  
Keyword(s):  
Coronary Artery ◽  
High Risk ◽  
Aortic Arch ◽  
Chest Radiography ◽  
Coronary Artery Calcification ◽  
Independent Predictor ◽  
Study Group ◽  
Discriminative Performance ◽  
Sensitivity Specificity ◽  
Aortic Arch Calcification

Background: We aimed to investigate the association between aortic arch and coronary artery calcification (CAC). We postulated that low‐ and high‐risk CAC scores could be predicted with the evaluation of standard chest radiography for aortic arch calcification (AAC). Patients and methods: Consecutive patients who were referred for a multidetector computerized tomography (MDCT) examination were enrolled prospectively. All patients were scanned using a commercially available 64‐slice MDCT scanner for the evaluation of CAC score. A four‐point grading scale (0, 1, 2 and 3) was used to evaluate AAC on the standard posterior‐anterior chest radiography images. Results: The study group consisted of 248 patients. Median age of the study group was 52 (IQR: 10) years, and 165 (67 %) were male. AAC grades (r = 0.676, p < 0.0001) and age (r = 0.518, p < 0.0001) were significantly and positively correlated with CAC score. Presence of AAC was independently associated with the presence of CAC (OR: 11.20, 95 % CI 4.25 to 29.52). An AAC grade of ≥ 2 was the strongest independent predictor of a high‐risk CAC score (OR: 27.42, 95 % CI 6.09 to 123.52). Receiver operating characteristics curve analysis yielded a strong predictive ability of AAC grades for a CAC score of ≥ 100 (AUC = 0.892, P < 0.0001), and ≥ 400 (AUC = 0.894, P < 0.0001). Absence of AAC had a sensitivity, specificity and accuracy of 90 %, 84 % and 89 %, respectively, for a CAC score of < 100. An AAC grade of ≥ 2 predicted a CAC score of ≥400 with a sensitivity, specificity and accuracy of 68 %, 98 % and 95 %, respectively. Conclusions: AAC is a strong and independent predictor of CAC. The discriminative performance of AAC is high in detecting patients with low‐ and high‐risk CAC scores.

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