Optimizing Femoral Access in Emergency EVAR with a Decision-Making Algorithm
Abstract
:1. Introduction
2. Materials and Methods
2.1. Technique—Surgical Approach
2.2. Technique—Percutaneous Approach
2.3. Algorithm
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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N (%) | ||
---|---|---|
Diabetes | 54 (73) | |
Hypertension | 70 (96) | |
Tobacco Use | 64 (86) | |
Renal Failure | 23 (31) | |
Obesity | ||
Obesity Grade I (BMI 30–34.9) | 5 (6.7) | |
Obesity Grade II (BMI 35–39.9) | 6 (8.1) | |
Obesity Grade III (BMI > 40) | 3 (4.1) |
Antiplatelet Therapy | N % | ||
---|---|---|---|
None | 25 (33.8) | ||
Single Agent | 45 (60.8) | ||
Acetylsalicylic, 100 mg | 31 | ||
Acetylsalicylic, 150 mg | 5 | ||
Acetylsalicylic, 300 mg | 3 | ||
Clopidogrel | 9 | ||
Ticlopidine | 1 | ||
Dual Therapy (Acetylsalicylic 100 mg + clopidogrel) | 0 | ||
Anticoagulation | |||
Warfarin | 3 (4.1) | ||
Direct Oral Anticoagulants | 1 (1.3) |
Group A: 46 Patients | Surgical Approach | Percutaneous Approach | Conversion | p |
---|---|---|---|---|
N. accesses | 40 | 52 | 10 | |
Severe atherosclerosis with calcifications of >50% of circumference | 8 | 26 | 3 | 0.5 |
Small CFA (<5 mm) | 8 | 2 | 0.4 | |
Obesity patients: BMI > 35 | 7 | 4 | 0.5 | |
Tortuosity of iliac–femoral axis: >1.6 | 11 | 1 | 0.6 | |
Group B: 28 patients | 1 | |||
N. accesses | 39 | 17 | ||
Severe atherosclerosis with calcifications of >50% of circumference | 19 | 0 | 0.5 | |
Small CFA (<5 mm) | 10 | 0 | 0.7 | |
Obesity patients: BMI > 35 | 2 | 0 | 0.5 | |
Tortuosity of iliac–femoral axis: >1.6 | 8 | 5 | 1 | 0.2 |
Variables | Surgical | Percutaneous | Conversion | p |
---|---|---|---|---|
Operative time, min [IQR] | 79 (68–85) | 66 (60–75) | 85 (78–122) | |
Rate of transfusion (21 patients—28.4%) | 12 (57%) | 9 (43%) | 11 (100%) | <0.04 |
Type of anesthesia | Local: 42, general: 3 | Local: 28, general: 1 | Local: 10, general: 1 | |
CFA approach time, min [IQR] | 7 (5–15) | 3 (1–5) | 12 (5–20) | <0.04 |
Mean contrast medium, mL [IQR] | 80 (75–91) | 81 (77–93) | ||
Fluoroscopy time, min [IQR] | 20 (11–21) | 21 (13–23) | ||
DAP, G * cm2 [IQR] | 30 (27.5–33) | 32 (28–36) | ||
Implanted Endoprostheses: 74 cases | ||||
Endurant (Medtronic) | 36 | 26 | 8 | |
Treo (Bolton) | 3 | 1 | 0 | |
AFX (Endologix) | 6 | 2 | 1 |
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Mirabella, D.; Bruno, S.; La Marca, M.A.; Dinoto, E.; Rodriquenz, E.; Miccichè, A.; Pecoraro, F. Optimizing Femoral Access in Emergency EVAR with a Decision-Making Algorithm. Life 2024, 14, 1113. https://doi.org/10.3390/life14091113
Mirabella D, Bruno S, La Marca MA, Dinoto E, Rodriquenz E, Miccichè A, Pecoraro F. Optimizing Femoral Access in Emergency EVAR with a Decision-Making Algorithm. Life. 2024; 14(9):1113. https://doi.org/10.3390/life14091113
Chicago/Turabian StyleMirabella, Domenico, Salvatore Bruno, Manfredi Agostino La Marca, Ettore Dinoto, Edoardo Rodriquenz, Andrea Miccichè, and Felice Pecoraro. 2024. "Optimizing Femoral Access in Emergency EVAR with a Decision-Making Algorithm" Life 14, no. 9: 1113. https://doi.org/10.3390/life14091113
APA StyleMirabella, D., Bruno, S., La Marca, M. A., Dinoto, E., Rodriquenz, E., Miccichè, A., & Pecoraro, F. (2024). Optimizing Femoral Access in Emergency EVAR with a Decision-Making Algorithm. Life, 14(9), 1113. https://doi.org/10.3390/life14091113