This systematic review and meta-analysis aims to investigate the effectiveness of left subclavian artery revascularization compared with non-revascularization in thoracic endovascular aortic repair, and to summarize the current evidence on its indications. A computerized search was conducted across multiple databases, including MEDLINE, SCOPUS, Cochrane Library, and Web of Science, for studies published up to November 2023. Study selection, data abstraction, and quality assessment (using the Newcastle-Ottawa Scale) were independently conducted by two reviewers, with a third author resolving discrepancies. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using random-effects models and publication bias was assessed using funnel plots. In the 76 included studies, left subclavian artery revascularization was associated with reduced risks of stroke (OR, 0.67; 95% CI, 0.45-0.98; n = 15,331), spinal cord ischemia (OR, 0.75; 95% CI, 0.56-0.99; n = 11,995), and arm ischemia (OR, 0.09; 95% CI, 0.01-0.59; n = 8438). No significant reduction in paraplegia (OR, 0.56; 95% CI, 0.21-1.47; n = 1802) or mortality (OR, 0.77; 95% CI, 0.53-1.12; n = 11,831) was observed. Moreover, the risk of endoleak was comparable in both groups (OR, 1.25; 95% CI, 0.55-2.84; P = .60; n = 793), whereas the risk of reintervention was significantly higher in the revascularization group (OR, 1.98; 95% CI, 1.03-3.83; P = .04; n = 272). Both groups had similar risks of major (OR, 0.45; 95% CI, 0.19-1.09; P = .08; n = 1113), minor (OR, 0.21; 95% CI, 0.01-3.45; P = .27; n = 183), renal (OR, 0.61; 95% CI, 0.12-3.06; P = .55; n = 310), and pulmonary (OR, 0.59; 95% CI, 0.16-2.15; P = .42; n = 8083) complications. The most frequent indications for left subclavian artery revascularization were primary prevention of spinal cord ischemia, augmentation of the landing zone, and primary stroke prevention. Left subclavian artery revascularization in thoracic endovascular aortic repair was associated with reduced neurological complications but was not found to impact mortality. The study highlights important indications for revascularization as well as significant predictors of complications, providing a basis for clinical decision-making and future research.

Background: Lower extremity endovascular revascularization for peripheral artery disease carries nonnegligible perioperative risks; however, outcome prediction tools remain limited. Using machine learning, we developed automated algorithms that predict 30‐day outcomes following lower extremity endovascular revascularization. Methods and Results: The National Surgical Quality Improvement Program targeted vascular database was used to identify patients who underwent lower extremity endovascular revascularization (angioplasty, stent, or atherectomy) for peripheral artery disease between 2011 and 2021. Input features included 38 preoperative demographic/clinical variables. The primary outcome was 30‐day postprocedural major adverse limb event (composite of major reintervention, untreated loss of patency, or major amputation) or death. Data were split into training (70%) and test (30%) sets. Using 10‐fold cross‐validation, 6 machine learning models were trained using preoperative features. The primary model evaluation metric was area under the receiver operating characteristic curve. Overall, 21 886 patients were included, and 30‐day major adverse limb event/death occurred in 1964 (9.0%) individuals. The best performing model for predicting 30‐day major adverse limb event/death was extreme gradient boosting, achieving an area under the receiver operating characteristic curve of 0.93 (95% CI, 0.92–0.94). In comparison, logistic regression had an area under the receiver operating characteristic curve of 0.72 (95% CI, 0.70–0.74). The calibration plot showed good agreement between predicted and observed event probabilities with a Brier score of 0.09. The top 3 predictive features in our algorithm were (1) chronic limb‐threatening ischemia, (2) tibial intervention, and (3) congestive heart failure. Conclusions: Our machine learning models accurately predict 30‐day outcomes following lower extremity endovascular revascularization using preoperative data with good discrimination and calibration. Prospective validation is warranted to assess for generalizability and external validity.

Background: Thoracic endovascular aortic repair (TEVAR) and complex endovascular aneurysm repair (EVAR) are complex procedures that carry a significant risk of complications. While risk prediction tools can aid in clinical decision making, they remain limited. We developed machine learning algorithms to predict outcomes following TEVAR and complex EVAR. Methods: The Vascular Quality Initiative database was used to identify patients who underwent elective TEVAR and complex EVAR for noninfrarenal aortic aneurysms between 2012 and 2023. We extracted 172 features from the index hospitalization, including 93 preoperative (demographic/clinical), 46 intraoperative (procedural), and 33 postoperative (in‐hospital course/complications) variables. The primary outcome was 1‐year thoracoabdominal aortic aneurysm life‐altering event, defined as new permanent dialysis, new permanent paralysis, stroke, or death. The data were split into training (70%) and test (30%) sets. We trained 6 machine learning models using preoperative features with 10‐fold cross‐validation. Model robustness was evaluated using calibration plots and Brier scores. Results: Overall, 10 738 patients underwent TEVAR or complex EVAR, with 1485 (13.8%) experiencing 1‐year thoracoabdominal aortic aneurysm life‐altering event. Extreme Gradient Boosting was the best preoperative prediction model, achieving an area under the receiver operating characteristic curve of 0.96 (95% CI, 0.95–0.97), compared with 0.70 (95% CI, 0.68–0.72) for logistic regression. The Extreme Gradient Boosting model maintained excellent performance at the intra‐ and postoperative stages, with areas under the receiver operating characteristic curves of 0.97 (95% CI, 0.96–0.98) and 0.98 (95% CI, 0.97–0.99), respectively. Calibration plots indicated good agreement between predicted/observed event probabilities, with Brier scores of 0.09 (preoperative), 0.08 (intraoperative), and 0.05 (postoperative). Conclusions: Machine learning models can accurately predict 1‐year outcomes following TEVAR and complex EVAR, performing better than logistic regression.

Aneurysms of the foot arteries are uncommon but can lead to devastating complications such as acute foot ischemia or arterial rupture if left untreated. In this case series, we present four cases of aneurysms of the foot: one true dorsalis pedis artery aneurysm and three cases of post-traumatic plantar artery pseudoaneurysms with arteriovenous fistulas. All four patients were successfully managed with surgical excision of the aneurysm with or without arteriovenous fistulas ligation. Our case series is followed by discussion on the etiology, clinical presentation and management strategy of patients with aneurysms of the foot arteries.

Background: This study aimed to compare the outcomes of the percutaneous femoral access and open surgical cutdown access approaches in patients undergoing thoracic/abdominal endovascular aortic repair. Methods: We retrospectively reviewed the medical records of 59 patients who underwent a thoracic/abdominal endovascular aortic repair at a single tertiary care hospital between 2015 and 2022. Based on their femoral access type, the patients were categorized into the “percutaneous” or “cutdown” groups. Using a computerized sheet, relevant patient data (including demographic information and patient risk factors) were collected. The operative duration, complication rates, mortality rates, intensive care unit admission and stay durations, and total hospital stay were compared between the two groups. The primary outcomes were differences in the postoperative morbidity and mortality associated with the two approaches. Results: The cutdown and percutaneous groups comprised 24 (41%) and 35 (59%) patients, respectively. The two groups displayed comparable demographic and clinical characteristics (p > 0.05). However, the vascular anatomy differed with the common femoral artery diameter being larger in the percutaneous group compared to the cutdown group (9.63 ± 1.81 mm vs. 8.49 ± 1.54 mm, p = 0.028). The ratio of the sheath diameter to the common femoral artery diameter was significantly lower in the percutaneous group than in the cutdown group (0.73 ± 0.16 vs. 0.85 ± 0.20, p = 0.027). A ratio of ≥0.74 was associated with a higher risk of complications (odds ratio, 12.0; 95% confidence interval, 1.4–102.2; p = 0.023) and mortality (odds ratio, 5.79; 95% confidence interval, 1.13–29.6; p = 0.035). Additionally, the operative duration was significantly shorter in the percutaneous group than in the cutdown group (141.43 ± 97.05 min vs. 218.46 ± 126.31 min, p = 0.001). Compared to the cutdown group, the percutaneous group experienced a shorter total hospital stay (21.54 ± 21.49 days vs. 11.60 ± 12.09 days, p = 0.022) and lower intensive care unit-admission rates (66.7% vs. 40%, p = 0.044). Conclusion: The percutaneous approach is a viable and more time-efficient alternative to the traditional cutdown method for delivering vascular endografts. It is associated with a significantly shorter operative duration and briefer hospital stays. Additionally, the ratio of the sheath diameter to the common femoral artery diameter can help surgeons preoperatively predict and anticipate the risks of complications and mortality. Future in-depth research is necessary to better understand the association between this ratio and postoperative outcomes and complications.

Carotid body tumors (CBTs) are rare and mostly benign. Research outcomes usually arise from single-center data. We conducted this study to present the characteristics and outcomes of patients who underwent surgical resection of CBT at our hospital over the past 20 years. In this retrospective review, the records of CBTs in our hospital were reviewed between 1998 and 2021. All patients who underwent CBT resection were included. The follow-up period was 12 months. A total of 44 CBTs were treated in our hospital. The male-to-female ratio was 1:2.4. Only 4.5% of patients had Shamblin I tumors. Patients with Shamblin II and III tumors were 56.8% and 38.6%, respectively. Duplex scan was used to diagnose CBT in all of the patients. The majority of our patients (97.7%) did not receive any preoperative embolization despite an average tumor size of 4.9 cm. Cranial nerve injuries were observed in 29.5% of cases. Meanwhile, stroke was reported in only two cases (4.5%). No deaths were encountered. Surgery is the definitive treatment for CBT. Size and local extension appear to be the main reasons for adverse events rather than surgical techniques. Our results are consistent with those of previously published studies. Good outcomes are expected in high-volume centers with appropriate preoperative imaging.