Rotational Atherectomy, Orbital Atherectomy, and Intravascular Lithotripsy Comparison for Calcified Coronary Lesions.
Kamila FlorekElżbieta BartoszewskaSzymon BiegałaOliwia KlimekBernadeta MalcharczykPiotr KublerPublished in: Journal of clinical medicine (2023)
In order to improve the percutaneous treatment of coronary artery calcifications (CAC) before stent implantation, methods such as rotational atherectomy (RA), orbital atherectomy (OA), and coronary intravascular lithotripsy (IVL) were invented. These techniques use different mechanisms of action and therefore have various short- and long-term outcomes. IVL employs sonic waves to modify CAC, whereas RA and OA use a rapidly rotating burr or crown. These methods have specific advantages and limitations, regarding their cost-efficiency, the movement of the device, their usefulness given the individual anatomy of both the lesion and the vessel, and the risk of specified complications. This study reviews the key findings of peer-reviewed articles available on Google Scholar with the keywords RA, OA, and IVL. Based on the collected data, successful stent delivery was assessed as 97.7% for OA, 92.4% for IVL, and 92.5% for RA, and 30-day prevalence of MACE (Major Adverse Cardiac Events) in OA-10.4%, IVL-7.2%, and RA-5%. There were no significant differences in the 1-year MACE. Compared to RA, OA and IVL are cost-effective approaches, but this is substantially dependent on the reimbursement system of the particular country. There is no standard method of CAC modification; therefore, a tailor-made approach is required.
Keyphrases
- coronary artery
- rheumatoid arthritis
- knee osteoarthritis
- disease activity
- pulmonary artery
- ankylosing spondylitis
- coronary artery disease
- risk factors
- interstitial lung disease
- systemic lupus erythematosus
- emergency department
- electronic health record
- heart failure
- minimally invasive
- systematic review
- big data
- left ventricular
- machine learning
- systemic sclerosis
- ultrasound guided
- atrial fibrillation
- deep learning
- radiofrequency ablation