Henkin, Stanislav

Post-pulmonary embolism syndrome (PPES) encompasses a diverse spectrum of long-term complications that are associated with persistent dyspnea, exercise intolerance, and a decrease in quality of life. The PPES constellation ranges from life-threatening conditions such as chronic thromboembolic pulmonary hypertension (CTEPH) to nonlife-threatening but still debilitating conditions such as chronic thromboembolic pulmonary disease (CTED) or post-PE deconditioning. The safety and efficacy of exercise and cardiopulmonary rehabilitation programs to prevent and manage these symptoms in PPES has not been well established. Herein, we review contributors to PPES and synthesize the evidence for exercise training after PE to treat and prevent PPES.

Background: Whether oral anticoagulation (OAC) can be discontinued after the resolution of left ventricular thrombus (LVT) remains controversial, particularly in patients without risk factors such as left ventricular aneurysms. This study aimed to identify patients who may safely discontinue OAC. Methods: We conducted a retrospective cohort study of patients with LVT resolution who completed their anticoagulation course and excluded patients with left ventricular (LV) aneurysm. Clinical and echocardiographic factors were compared between patients who experienced LVT recurrence (n = 22) and those without recurrence during follow-up (n = 94). Results: The cohort had a mean age of 64.5 ± 15.0 years, and half (50%) were male. Most had an ischemic cardiomyopathy (64.6%). LVT recurred in 19% (22/116) of patients following initial resolution. Patients with recurrence were older (mean age 71.3 ± 11.9 vs. 63.4 ± 15.7 years, p = 0.03) and were more likely to have prior ischemic stroke and arterial thromboembolism (18.2% vs. 4.3%, p = 0.02 for both). At the time of thrombus resolution, LVEF was significantly lower among patients who had recurrence (33.4 ± 13.6% vs. 42.5 ± 15.5%, p = 0.012). Stroke, systemic embolism, and mortality rates were similar regardless of recurrence status. Recurrence risk by presence or absence of stroke and LEVF >50% on the LVT resolution echocardiogram is shown in Figure 1. Notably, no recurrences were observed among patients with both LVEF > 50% and no history of stroke (0/32), which was statistically significant compared to each other category. Conclusion: Among patients without left ventricular aneurysm who discontinued oral anticoagulation after LVT resolution, those with preserved LVEF (>50%) and no prior history of stroke had a very low risk of recurrence, with no events observed in this subgroup. These findings suggest that some patients may safely discontinue anticoagulation after LVT resolution.

ImportanceAcute pulmonary embolism (PE) is a major cause of morbidity and mortality in patients with cancer in the US and worldwide.ObjectivesTo assess the trends in PE-related mortality from 2011 to 2020 among US patients with cancer across age, sex, ethnic and racial groups, urbanicity, and regionality.Design, Setting, and ParticipantsThis cohort study used the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research data system to determine national trends in age-adjusted mortality rates (AAMRs) due to acute PE among US patients with cancer aged 15 years or older from January 2011 to December 2020. Concomitant trends in cancer mortality and incidence that may have contributed to PE-related mortality were obtained from US Cancer Statistics. Data were analyzed from September to November 2024.ExposurePE-related mortality.Main Outcomes and MeasuresThe primary outcome was PE-related deaths among individuals with cancer. AAMRs and cancer incidence were assessed using joinpoint regression modeling, expressed as an average annual percentage change (AAPC) with relative 95% CIs.ResultsFrom 2011 to 2020, a total of 27 280 194 individuals aged 15 years or older (13 897 519 male [50.9%]; 13 382 675 female [49.1%]) died in the US. The AAMR for PE-related mortality in patients with cancer increased during this time period (AAPC, 2.5%; 95% CI, 1.4% to 3.6%; P = .001), without differences between sexes (P for parallelism = .38). The AAMR increased among those aged 15 to 64 years (AAPC, 3.2%; 95% CI, 1.9% to 4.6%; P = .001), non-Hispanic and non-Latinx White individuals (AAPC, 2.7%; 95% CI, 1.52% to 3.94%; P = .001), non-Hispanic and non-Latinx Black or African American individuals (AAPC, 2.2%; 95% CI, 0.7% to 3.7%; P = .001), Hispanic and Latinx individuals (AAPC, 2.6%; 95% CI, 0.7% to 4.5%; P = .006), and among individuals residing in the Southern US (AAPC, 3.7%; 95% CI, 1.3% to 6.2%; P = .003). During the same period, age-adjusted cancer incidence and cancer-related mortality decreased while the absolute number of new cancer diagnoses and cancer-related deaths increased.Conclusions and RelevanceThis cohort study found that despite decreases in cancer-related mortality rates, age-adjusted PE-related mortality in US patients with cancer increased over the last decade; concerning trends included rising PE-related mortality in younger individuals aged 15 to 64 years, particular ethnic and racial groups, and the Southern region of the US. Recognition of such patterns may inform further research into thromboprophylaxis and treatment of PE as a complication of cancer and cancer-directed therapy.

Background: Risk stratification for suspected pulmonary emboli (PE) remains an area of active research. Current risk stratification algorithms have moderate discriminatory capabilities and are guideline-recommended, but they are poorly utilized in practice, with most clinicians relying predominantly on their clinical training and personal “gestalt.” Our group recently derived an Artificial Intelligence (AI) algorithm using electrocardiograms (ECG) to predict the presence of PE (AUC 0.69) on computed tomography scans of the pulmonary arteries (CTPA) in a cohort of 79K patients. Aim: Validate the AI-ECG algorithm in a contemporary dataset of patients with suspected PE. Methods: Emergency Department (ED) visits between 9/1/2022 and 12/31/2023 across the Mayo Clinic Enterprise were searched using a unified data platform. ED visits in patients over 18 years of age with a discretely documented Wells' PE or PERC Rule, a D-dimer result, or a CTPA were included. Only CTPA imaging and D-dimers performed within 48 hours of ED admission were eligible to be included. Patients were included in the final cohort if an ECG was performed within 6 hours of ED admission, D-dimer testing, or CTPA. Patients were considered negative for PE if CTPA was negative, and when this wasn't performed, a negative D-dimer (high sensitivity) or PERC rule of 0 was considered negative. A previously derived Artificial Neural Network algorithm to analyze the ECG to predict PE was applied to the dataset for validation. Results: A total of 27,028 ED visits in 24,288 unique patients meet inclusion criteria. Among this group, the first ED visit with a CTPA and an ECG within 6 hours was included, leaving 18,936 patients for the final validation cohort. The mean age of the cohort was 54.7 (SD 18.7), and 57% were male. Among the entire cohort, 13,573 underwent D-dimer testing for which 4,895 (36%) were positive at standard thresholds. A total of 10,486 patients underwent CTPA (55% of patients evaluated), of which 455 were positive for PE (4.3%). Using the AI-ECG model from the derivation cohort applied to this validation cohort resulted in an AUC of 0.69, identical to the derivation cohort. Using ECG model estimates alone, low (0.74%, n=2447, NPV 99.3%), elevated (2.27%, n=15404, NPV, 97.72%), and high-risk (8.02%, n=1085, NPV 91.98%) categories for PE can be created. A negative D-dimer in the elevated risk group increased the negative predictive value (NPV) to >99.9% and could be used to reduce imaging in this group further. Using the proposed ECG to D-dimer cascade risk stratification could further reduce the need for PE imaging for an overall NPV of 99.9% and sensitivity of 95.2%. We then used additional clinical parameters to train a new algorithm with additional clinical data and the AI-ECG algorithm estimates. Multiple machine learning algorithms were then evaluated in a dataset divided into training (2/3) and testing (1/3) datasets, after downsampling (to address class imbalance). The best results were obtained with AI-ECG results and D-dimer: Ada Boost (AUC 0.93, F1 score 0.895) compared to standard logistic regression (AUC 0.79, F1 score 0.746). The addition of age, sex, and oxygen saturation did not improve model performance. Conclusion: We have now validated the previously derived AI-ANN ECG algorithm for PE in a contemporary and independent cohort and demonstrate potential for integration into clinical PE assessment algorithms. Unlike prior risk stratification processes, ECGs are invariably performed in patients with cardiopulmonary symptoms and have the potential to prevent missed or delayed PE diagnosis by proactively identifying high-risk patients. Additionally, we demonstrate that the results of this algorithm can be combined with D-dimer values, resulting in a simple, powerful, predictive algorithm (AUC 0.93) that pairs cardiovascular electrophysiology with laboratory biomarkers and could lead to a new paradigm in clinical risk stratification for PE.