Pulmonary embolism (PE) remains a critical condition with significant mortality and morbidity, necessitating timely detection and intervention to improve patient outcomes. This review examines the evolving role of artificial intelligence (AI) in PE management. Two primary AI-driven models that are currently being explored are deep convolutional neural networks (DCNNs) for enhanced image-based detection and natural language processing (NLP) for improved risk stratification using electronic health records. A major advancement in this field was the FDA approval of the Aidoc© AI model, which has demonstrated high specificity and negative predictive value in PE diagnosis from imaging scans. Additionally, AI is being explored for optimizing anticoagulation strategies and predicting PE recurrence risk. While further large-scale studies are needed to fully establish AI’s role in clinical practice, its integration holds significant potential to enhance diagnostic accuracy and overall patient management.

Background: Large bore access procedures rely on vascular closure devices to minimize access site complications. Suture-based vascular closure devices (S-VCD) such as ProGlide and ProStar XL have been readily used, but recently, newer generation collagen-based vascular closure devices (C-VCD) such as MANTA have been introduced. Data on comparisons of these devices are limited. Methods: PubMed, Scopus and Cochrane were searched for articles on vascular closure devices using keywords, (“Vascular closure devices” OR “MANTA” OR “ProStar XL” OR “ProGlide”) AND (“outcomes”) that resulted in a total of 875 studies. Studies were included if bleeding or vascular complications as defined by Valve Academic Research Consortium-2 were compared between the two types of VCDs. The event level data were pooled across trials to calculate the Odds Ratio (OR) with 95% CI, and analysis was done with Review Manager 5.4 using random effects model. Results: Pooled analyses from these nine studies resulted in a total of 3410 patients, out of which 2855 were available for analysis. A total of 1229 received C-VCD and 1626 received S- VCD. Among the patients who received C-VCD, the bleeding complications (major and minor) were similar to patients who received S-VCD ((OR: 0.70 (0.35–1.39), p = 0.31, I² = 55%), OR: 0.92 (0.53–1.61), p = 0.77, I² = 65%)). The vascular complications (major and minor) in patients who received C-VCD were also similar to patients who received S-VCD ((OR: 1.01 (0.48–2.12), p = 0.98, I² = 52%), (OR: 0.90 (0.62–1.30), p = 0.56, I² = 35%)). Conclusions: Bleeding and vascular complications after large bore arteriotomy closure with collagen-based vascular closure devices are similar to suture-based vascular closure devices.

Aims: Intracardiac echocardiography-based electroanatomical mapping (EAM) improves procedural efficiency and safety in atrial fibrillation (AF) ablation and remains the standard of care. The CARTOSOUND FAM (AI FAM) module uses a deep-learning algorithm that automates left atrial reconstruction without manual contouring. This study aims to evaluate the 1-year outcomes of AI FAM compared to standard-of-care EAM in AF ablation. Methods and results: This study included 298 patients undergoing radiofrequency AF ablation between January 2021 and December 2023. Patients treated before January 2023 underwent standard-of-care EAM, while those in 2023 utilized AI FAM-based reconstruction. Baseline demographics, comorbidities, AF type, and medication use were recorded. Procedural characteristics, acute success, complications, and AF recurrence at 1-year follow-up were analysed. Of the 298 patients, 115 underwent mapping with AI FAM and 183 with EAM. Baseline characteristics were comparable. AI FAM reduced mean total procedure time (122.5 ± 23.5 vs. 129.0 ± 30.4 min, P = 0.040) and left atrial (LA) dwell time (78.3 ± 21.45 vs. 87.5 ± 28.2 min, P = 0.001). Acute procedural success was 98.3% in AI FAM vs. 98.9% in EAM with fewer complications observed in the AI FAM group (1 vs. 4). At 1 year, freedom from AF recurrence was comparable (80.0% AI FAM vs. 81.4% EAM at 1 year, LogRank P = 0.610). Conclusion: AI FAM was associated with incremental but significant procedural advantages over conventional contouring via reduced total procedure time and LA dwell time, without compromising acute and long-term safety and rhythm control efficacy. AI FAM integration with pulsed field ablation will mark another step towards making AF ablation more streamlined and accessible.

The purpose of this study is to evaluate whether early initiation of catheter-directed thrombolysis (CDT) in patients presenting with acute pulmonary embolism is associated with improved in-hospital outcomes. A retrospective cohort was extracted from the 2016–2019 National Inpatient Sample database, consisting of 21,730 weighted admissions undergoing CDT acute PE. From the time of admission, the sample was divided into early (48 h). Outcomes were measured using regression analysis and propensity score matching. No significant differences in mortality, cardiac arrest, cardiogenic shock, or intracranial hemorrhage (p > 0.05) were found between the early and late CDT groups. Late CDT patients had a higher likelihood of receiving systemic thrombolysis (3.21 [2.18–4.74], p < 0.01), blood transfusion (1.84 [1.41–2.40], p < 0.01), intubation (1.33 [1.05–1.70], p = 0.02), discharge disposition to care facilities (1.32 [1.14–1.53], p < 0.01). and having acute kidney injury (1.42 [1.25–1.61], p < 0.01). Predictors of late intervention were female sex, nonwhite race, and weekend admission (p < 0.01). This study represents a comprehensive evaluation of outcomes associated with the time interval for initiating CDT, revealing reduced morbidity with early intervention. Additionally, it identifies predictors associated with delayed CDT initiation. The broader ramifications of these findings, particularly in relation to hospital resource utilization and health disparities, warrant further exploration.