Casanegra, Ana I.

Abstract Background Published data on the risk of venous thromboembolism (VTE) with coronavirus disease 2019 (COVID-19) vaccines are scarce and inconclusive, leading to an unmet need for further studies. Methods A retrospective, multicentered study of adult patients vaccinated for one of the three approved COVID-19 vaccines in the United States of America and a pre-COVID-19 cohort of patients vaccinated for influenza at two institutions: Mayo Clinic Enterprise sites and the Medical College of Wisconsin, looking at rate of VTE over 90 days. VTE was identified by applying validated natural language processing algorithms to relevant imaging studies. Kaplan–Meier curves were used to evaluate rate of VTE and Cox proportional hazard models for incident VTE after vaccinations. Sensitivity analyses were performed for age, sex, outpatient versus inpatient status, and type of COVID-19 vaccine. Results A total of 911,381 study subjects received COVID-19 vaccine (mean age: 56.8 [standard deviation, SD: 18.3] years, 55.3% females) and 442,612 received influenza vaccine (mean age: 56.5 [SD: 18.3] years, 58.7% females). VTE occurred within 90 days in 1,498 (0.11%) of the total 1,353,993 vaccinations: 882 (0.10%) in the COVID-19 and 616 (0.14%) in the influenza vaccination cohort. After adjusting for confounding variables, there was no difference in VTE event rate after COVID-19 vaccination compared with influenza vaccination (adjusted hazard ratio: 0.95 [95% confidence interval: 0.85–1.05]). No significant difference in VTE rates was observed between the two cohorts on sensitivity analyses. Conclusion In this large cohort of COVID-19-vaccinated patients, risk of VTE at 90 days was low and no different than a pre-COVID-19 cohort of influenza-vaccinated patients.

Background The formation of dissecting pseudoaneurysms (dPSAs) is a common sequela of cervical artery dissection, which has been suggested to increase thrombotic risk in previous studies. This study reported clinical features and long‐term outcomes of cervical internal carotid (cICA) and vertebral artery (cVA) dPSAs. Methods We performed a retrospective chart review over a 10‐year period (January 2012–December 2021). Baseline demographics and clinical characteristics, medical and endovascular treatments, and long‐term outcomes were reported for cICA and cVA dPSA groups separately. Nonparametric tests were used to compare group differences. Results In our cohort, 120 (12%) of 999 cervical artery dissection patients had dPSA, with 85% occurring in the cICA and 15% in the cVA. Most dPSAs occurred spontaneously or in association with minor trauma. Compared with cICA dPSA, patients with cVA dPSA were younger (median age [range]=34.5 [24–70] versus 52 [30–77]; P <0.01), had a smaller dPSA size (median size [range]=4.5 mm [2–17] versus 8 mm [1.2–32]; P <0.01), and were more likely to reduce in size at follow‐up (median size change [range]=−2.8 mm [−17;0] versus 0 [−24;10.8]). Antithrombotic therapy was predominately aspirin monotherapy. No patients with cVA dPSA experienced recurrent strokes and only 3% of patients with cICA dPSA developed new/recurrent stroke in the territory of dPSA while on an antithrombotic regimen requiring endovascular intervention, and none of the dPSAs ruptured. A total of 98% of the patients had an excellent outcome (modified Rankin scale 0–2 at final follow‐up). Conclusion Most cICA and cVA dPSAs have a benign prognosis with medical therapy alone. Further prospective randomized clinical trials are needed to provide high quality evidence on the necessity of additional endovascular therapy at diagnosis in addition to medical therapy alone.

AbstractPatients with thrombophilia remain concerned about venous thromboembolism (VTE) risk with COVID‐19 vaccinations. The aim of this study was to examine VTE outcomes in patients with inherited or acquired thrombophilia who were vaccinated for COVID‐19. Vaccinated patients ≥18 years between November 1, 2020 and November 1, 2021 were analyzed using electronic medical records across the Mayo Clinic enterprise. The primary outcome was imaging confirmed acute VTE occurring 90 days before and after the date of the first vaccine dose. Thrombophilia patients were identified through laboratory testing results and ICD‐10 codes. A total of 792 010 patients with at least one COVID‐19 vaccination were identified. Six thousand sixty‐seven of these patients were found to have a thrombophilia, among whom there was a total of 39 VTE events after compared to 51 VTE events before vaccination (0.64% vs. 0.84%, p = .20). In patients with Factor V Leiden or prothrombin gene mutation, VTE occurred in 27 patients before and in 29 patients after vaccination (0.61 vs. 0.65%, p = .79). In patients with antiphospholipid syndrome, VTE occurred in six patients before and four patients after vaccination (0.59% vs. 0.39%, p = .40). No difference was observed in the overall VTE rate when comparing the postvaccination 90 days to the prevaccination 90 days, adjusted hazard ratio 0.81 (95% confidence interval: 0.53–1.23). In this subgroup of COVID‐19 vaccinated patients with thrombophilia, there was no increased risk for acute VTE postvaccination compared to the prevaccination timeframe. These results are consistent with prior studies and should offer additional reassurance to patients with inherited or acquired thrombophilia.

Background Study aims were to analyze prospectively collected data from patients with cancer-associated venous thromboembolism (VTE) to determine the impact of VTE recurrence and anticoagulant-related bleeding on all-cause mortality. Patients/Methods Consecutive cancer patients with acute VTE treated with anticoagulants (March 1, 2013–November 30, 2021) were included in this analysis. Anticoagulant therapy-associated VTE recurrences, major bleeding, and clinically relevant nonmajor bleeding (CRNMB) were assessed for their impact on all-cause mortality outcomes. Results This study included 1,812 cancer patients with VTE. Of these, there were 97 (5.4%) with recurrent VTE, 98 (5.4%) with major, and 104 (5.7%) with CRNMB while receiving anticoagulants. Recurrent VTE (hazard ratio [HR]: 1.52; 95% confidence interval [CI]: 1.16–2.00; p = 0.0028), major bleeding (HR: 1.82; 95% CI: 1.41–2.31; p = 0.006), and CRNMB (HR; 1.38; 95% CI: 1.05–1.81; p = 0.018) each adversely influenced mortality outcomes. Deep vein thrombosis as the incident thrombotic event type was associated with VTE recurrence (HR: 1.78; 95% CI: 1.08–2.89; p = 0.02). Neither cancer type nor stage, chemotherapy, or Ottawa risk category influenced VTE recurrence. Higher body weights (HR: 1.01; 95% CI: 1.00–1.01; p = 0.005) were associated with increased major bleeding, while high Ottawa scores (HR: 0.66; 95% CI: 0.46–0.96; p = 0.03) and apixaban treatment (HR: 0.62; 95% CI: 0.45–0.84; p = 0.002) were associated with fewer major bleeding outcomes. Conclusion Among cancer patients receiving anticoagulant therapy for VTE, adverse outcomes such as VTE recurrence, major bleeding, or CRNMB increase mortality risk by 40 to 80%. Identifying variables predicting these outcomes may help risk-stratify patients with poor prognosis.

AbstractBackgroundClinical picture and outcome of incidental pulmonary embolism (iPE) compared to symptomatic pulmonary embolism (sPE) remain unclear.MethodsDemographics, recurrent venous thromboembolism (VTE), mortality, major bleeding, and clinically relevant nonmajor bleeding (CRNMB) were compared between iPE and sPE patients who were followed prospectively at Mayo Thrombophilia Clinic (March 1, 2013 to August 1, 2020).ResultsOut of 3576 VTE patients, 1417 (39.6%) had PE: 562 (39.7%) iPE and 855 sPE. Patients with cancer were more likely to have iPE (400 iPE vs. 314 sPE) compared to those without cancer (162 iPE vs. 541 sPE). VTE recurrence rate (all per 100 person‐years) was similar in all iPE and sPE patients (3.34 vs. 3.68, p = .50), with cancer (4.16 vs. 4.89, p = .370), and without cancer patients (0.89 vs. 2.80, p = .25). Higher mortality observed in all patients with iPE compared to sPE (46.45 vs. 23.47, p < .001) and with cancer (56.41 vs. 45.77, p = .03) became not significant after adjustment for age, antiplatelet therapy, metastases, and cancer location. Noncancer iPE patients had higher mortality (15.95 vs. 7.18, p = .006) even after adjustment (p = .05). The major bleeding rate was also higher in all patients iPE compared to sPE (7.10 vs. 3.68, p = .03), but not after adjustment (p = .974); higher major bleeding rate in noncancer patients (6.49 vs. 1.25, p = .007) remained significant after adjustment (.02). CRNMB rate was similar to iPE and sPE patients.ConclusioniPE represents a more serious clinical condition compared to sPE as indicated by the higher mortality and major bleeding but these differences reflect underlying comorbidities rather than the seriousness of the embolic event.

Background: Patients with peripheral artery disease (PAD) are at increased risk for major adverse limb and cardiac events including mortality. Developing screening tools capable of accurate PAD identification is a necessary first step for strategies of adverse outcome prevention. This study aimed to determine whether machine analysis of a resting Doppler waveform using deep neural networks can accurately identify patients with PAD. Methods: Consecutive patients (4/8/2015 – 12/31/2020) undergoing rest and postexercise ankle–brachial index (ABI) testing were included. Patients were randomly allocated to training, validation, and testing subsets (70%/15%/15%). Deep neural networks were trained on resting posterior tibial arterial Doppler waveforms to predict normal (> 0.9) or PAD (⩽ 0.9) using rest and postexercise ABI. A separate dataset of 151 patients who underwent testing during a period after the model had been created and validated (1/1/2021 – 3/31/2021) was used for secondary validation. Area under the receiver operating characteristic curves (AUC) were constructed to evaluate test performance. Results: Among 11,748 total patients, 3432 patients met study criteria: 1941 with PAD (mean age 69 ± 12 years) and 1491 without PAD (64 ± 14 years). The predictive model with highest performance identified PAD with an AUC 0.94 (CI = 0.92–0.96), sensitivity 0.83, specificity 0.88, accuracy 0.85, and positive predictive value (PPV) 0.90. Results were similar for the validation dataset: AUC 0.94 (CI = 0.91–0.98), sensitivity 0.91, specificity 0.85, accuracy 0.89, and PPV 0.89 (postexercise ABI comparison). Conclusion: An artificial intelligence-enabled analysis of a resting Doppler arterial waveform permits identification of PAD at a clinically relevant performance level.