ABSTRACT
INTRODUCTION: This retrospective study investigated the effectiveness and safety of left distal transradial access (LDTRA) in patients with cardiovascular disease in Trinidad undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI). METHOD: Procedural parameters, including technical success and safety outcomes such as vascular complications and radial artery occlusion (RAO), were assessed in 111 consecutive patients undergoing CAG or PCI from January 2023 to June 2023 at the Eric Williams Medical Sciences Complex, Trinidad and Tobago. Eighty-eight patients underwent LDTRA, while 23 received left transradial access (LTRA). RESULTS: There was no difference in procedural success with LDTRA compared to LTRA, 90.9% vs. 100%, p-value 0.202, non-significant (ns). LDTRA was associated with shorter fluoroscopy times (8.4 ± 6.8 minutes vs. 12.4 ± 7.7 minutes, p-value = 0.02), procedural duration (26.7 ± 18 minutes vs. 35.8 ± 20 minutes, p-value = 0.04), and hemostasis time (142 ± 41 minutes vs. 186 ± 44 minutes, p-value < 0.05). There were no significant differences in procedural-related complications (8% for LDTRA vs. 4.3% for LTRA, p-value = 0.476, ns). There were no reported cases of RAO. In the subgroup of patients with prior coronary artery bypass grafting (CABG), the fluoroscopy and procedure times were similar for both access sites; however, LDTRA was associated with a shorter hemostasis time (128 ± 30 minutes vs. 194 ± 39 minutes, p-value = 0.01). CONCLUSIONS: LDTRA is effective and safe for coronary procedures and is associated with a shorter hemostasis time. This study may prove clinically pertinent in a limited-resource Caribbean setting.
ABSTRACT
In the evolution of modern medicine, artificial intelligence (AI) has been proven to provide an integral aspect of revolutionizing clinical diagnosis, drug discovery, and patient care. With the potential to scrutinize colossal amounts of medical data, radiological and histological images, and genomic data in healthcare institutions, AI-powered systems can recognize, determine, and associate patterns and provide impactful insights that would be strenuous and challenging for clinicians to detect during their daily clinical practice. The outcome of AI-mediated search offers more accurate, personalized patient diagnoses, guides in research for new drug therapies, and provides a more effective multidisciplinary treatment plan that can be implemented for patients with chronic diseases. Among the many promising applications of AI in modern medicine, medical imaging stands out distinctly as an area with tremendous potential. AI-powered algorithms can now accurately and sensitively identify cancer cells and other lesions in medical images with greater accuracy and sensitivity. This allows for earlier diagnosis and treatment, which can significantly impact patient outcomes. This review provides a comprehensive insight into diagnostic, therapeutic, and ethical issues with the advent of AI in modern medicine.
