Casanegra, Ana I.

Background Patients with peripheral artery disease are at increased risk for major adverse cardiac events, major adverse limb events, and all‐cause death. Developing tools capable of identifying those patients with peripheral artery disease at greatest risk for major adverse events is the first step for outcome prevention. This study aimed to determine whether computer‐assisted analysis of a resting Doppler waveform using deep neural networks can accurately identify patients with peripheral artery disease at greatest risk for adverse outcome events. Methods and Results Consecutive patients (April 1, 2015, to December 31, 2020) undergoing ankle–brachial index testing were included. Patients were randomly allocated to training, validation, and testing subsets (60%/20%/20%). Deep neural networks were trained on resting posterior tibial arterial Doppler waveforms to predict major adverse cardiac events, major adverse limb events, and all‐cause death at 5 years. Patients were then analyzed in groups based on the quartiles of each prediction score in the training set. Among 11 384 total patients, 10 437 patients met study inclusion criteria (mean age, 65.8±14.8 years; 40.6% women). The test subset included 2084 patients. During 5 years of follow‐up, there were 447 deaths, 585 major adverse cardiac events, and 161 MALE events. After adjusting for age, sex, and Charlson comorbidity index, deep neural network analysis of the posterior tibial artery waveform provided independent prediction of death (hazard ratio [HR], 2.44 [95% CI, 1.78–3.34]), major adverse cardiac events (HR, 1.97 [95% CI, 1.49–2.61]), and major adverse limb events (HR, 11.03 [95% CI, 5.43–22.39]) at 5 years. Conclusions An artificial intelligence–enabled analysis of Doppler arterial waveforms enables identification of major adverse outcomes among patients with peripheral artery disease, which may promote early adoption and adherence of risk factor modification.

Pulmonary embolism (PE) is the third most common cause of cardiovascular death and necessitates prompt, accurate risk assessment at initial diagnosis to guide treatment and reduce associated mortality. Intermediate-risk PE, defined as the presence of right ventricular (RV) dysfunction in the absence of hemodynamic compromise, carries a significant risk for adverse clinical outcomes and represents a unique diagnostic challenge. While small clinical trials have evaluated advanced treatment strategies beyond standard anticoagulation, such as thrombolytic or endovascular therapy, there remains continued debate on the optimal care for this patient population. Here, we review the most recent risk stratification models, highlighting differences between prediction scores and their limitations, and discuss the utility of serologic biomarkers and imaging modalities to detect right ventricular dysfunction. Additionally, we examine current treatment recommendations including anticoagulation strategies, use of thrombolytics at full and reduced doses, and utilization of invasive treatment options. Current knowledge gaps and ongoing studies are highlighted.

Introduction: Predictive algorithms using multiple clinical variables can identify patients at higher risk for abdominal aortic aneurysms (AAA), however they are cumbersome and cannot used directly by patients. A simple, cheap, noninvasive, and readily available (virtual) screening tool for identification of AAA could aid in screening algorithms. Aims: We sought to determine if a machine learning algorithm could predict the presence of an AAA by using a image of the face Methods: Diagnostic imaging studies were extracted from the electronic health record (EHR) from 5/7/2018 through 1/1/2023 and analyzed by a natural language processing algorithm previously validated to identify abdominal aortic aneurysms. Patient EHR profile pictures were extracted and matched to imaging studies. Various deep neural network (DNN) architectures were explored, all trained as classifiers on the face images along with clinical variables to predict clinical outcomes. All models used were CNNs with an EfficientNet architecture. Model performance was evaluated by standard metrics such as the area under the curve (AUC), specificities (Sp), and sensitivities (Sn). All performance metrics reported results from the test subset of the primary dataset and did not contain any observations considered during training. Results: A total of 5522 patients with facial images and AAA diagnostic studies were analyzed, among whom 1314 (23.8%) had a AAA. The optimal model had an AUC of 0.72 (Sn 0.44, Sp 0.83) for predicting AAA and remained similar in women (AUC 0.7), men (AUC 0.65), age >65 (AUC 0.63), and age <=65 (AUC 0.72) (Table). Conclusions: Using only an image of a patients face, the presence of an AAA could be identified with moderate performance in men, women, and in those less than 65. The model’s performance in demographics not typically screened for AAA may allow for targeted screening programs in these groups.

Introduction: Warfarin is a commonly prescribed anticoagulant for treating atrial fibrillation, mechanical valves, and venous thromboembolism. Warfarin dose management remains challenging due to dosing variability between patients and warfarin’s narrow therapeutic window. Time in therapeutic range (TTR) is critical to warfarin’s safety and efficacy, but TTR typically remains low (40-50%) in community practices. Specialized anticoagulation clinics and protocolized approaches can increase TTR but have great administrative burdens and health care costs. Aim: To develop standardized optimal warfarin dose decision support using a machine learning model based on time series anticoagulation data and patient demographic characteristics Methods: The dataset included 12,497 warfarin patients monitored in the anticoagulation tracker of electronic medical records across the Mayo Clinic Enterprise. The dataset contained time series anticoagulation data (warfarin dose, INR, INR target range) and patient demographic characteristics. We implemented an offline deep reinforcement learning model (DRL) to predict the cumulative warfarin dose for the days until the next INR test based on a patient’s historical anticoagulation data. Prior approaches utilized traditional supervised learning methods such as regression or Long Short Term Memory (LSTM) neural networks to approximate a function mimicking the behavior of the training data. On the other hand, DRL learned an optimal dosing policy through continuous interaction and feedback from the training data. The key advantage of DRL is the model can learn to behave differently (and potentially better) for suboptimal clinical states in the data such as overdosing or underdosing. To evaluate the DRL model we compared the predicted warfarin doses with the physician-prescribed doses Results: DRL model’s prediction accuracy was 96.96%, outperforming our implementation of a baseline LSTM model with a prediction accuracy of 70.58%. Further evaluation of the DRL model indicated that the model correctly adjusted the warfarin dose at time steps when patients had out-of-range INRs. Conclusions: Offline deep reinforcement learning demonstrates potential in supporting warfarin dose management to maximize TTR.

Intro: Venous thromboembolism (VTE) is a common cause of death among cancer patients, second only to cancer progression. Identifying factors predicting worse outcomes among cancer patients with VTE would be useful clinically. For cancer patients with pulmonary emboli (PE), it remains unclear whether concomitant leg deep vein thrombosis (DVT) as a source for further embolization adversely impacts this risk. The aim of this project was to determine the impact of residual DVT on adverse outcomes among cancer patients suffering acute PE. Methods: Consecutive patients with confirmed acute PE (March 1, 2013 - June 30, 2021) underwent ultrasound (US) imaging and were divided into two groups depending on the presence or absence of leg DVT. PE severity was classified based on AHA criteria. Patients were followed prospectively for VTE recurrence, major and clinically relevant non-major bleeding (CRNMB) and all-cause mortality. Results: Over the study interval, 1,035 cancer patients with PE were enrolled (Table 1). Of these, 375 (36.2%) had leg DVT confirmed by US. Patients with leg DVT were older (64.2 vs 61.4 years, p = 0.01), heavier (90.2 vs 85.1 kg, p &lt;0.001), with lower metastatic disease prevalence (49.1% vs 57.1%, p = 0.01) compared to those without leg DVT. Cancer type distribution also differed between groups. PE patients with DVT more often had prostate, genitourinary, and hematologic cancers while those without DVT more often had pancreatic and breast cancers. Patients with DVT more often had symptomatic PE (48.2% vs. 35.9%, p &lt; 0.001), massive (2.9% vs 0.5%, p &lt; 0.001), and submassive (22.0% vs 7.6%, p &lt; 0.001). Patients with DVT more often received unfractionated heparin (39.5% vs 18.7%, p &lt; 0.001) whereas those without DVT were more frequently treated with low molecular weight heparin (57.5% vs. 44.3%, p &lt;0.001), and apixaban (16.4% vs. 11.7%, p &lt; 0.05). Anticoagulant duration, VTE recurrence, major bleeding and CRNMB were similar between groups (Table 2). Conclusion: Among a large cohort of cancer patients with pulmonary emboli, significant clinical and cancer specific differences exist comparing those with and without leg DVT.While theoretically increasing the risk of recurrent embolization, the presence of residual DVT does not appear to adversely impact important outcomes among cancer patients adequately treated with anticoagulation.

Purpose/Introduction: Patients with cancer and venous thromboembolism (VTE) have higher complication rates including thrombosis recurrence and bleeding. Real world prospective clinical outcome estimates of VTE management comparing cancer and non-cancer patients are limited. To assess VTE recurrence, major bleeding, and clinically relevant non-major bleeding (CRNMB) in patients with cancer and without cancer, the prospective Mayo Clinic Thrombophilia Clinic Registry was analyzed. Methods: Upon recruitment, consecutive patients with confirmed acute VTE (03/01/2013 - 04/30/2023) were treated in a standardized, guideline-sanctioned, protocol driven strategy incorporating shared patient-decision making. Patients were divided into groups based on cancer status. After enrollment, patients were actively followed at 3 month intervals, in person whenever feasible, by mailed questionnaire or scripted phone interview to assess vital status, medication compliance, VTE recurrence, major bleeding and CRNMB. Results: Over the study time-frame, 2,064 patients (53.8% male, 46.2% female) with a cancer and 2,647 patients (54.9% male, 45.1% female) without cancer were enrolled. The most common cancers were gastrointestinal (n=423, 20.5%), pancreatic (n=287, 13.9%), genitourinary (n=198, 9.6%), hematologic (n=171, 8.3%), and lung cancer (n=170, 8.2%). Patients with cancer were older, had lower weight and lower platelet counts compared to non-cancer patients (Table1). Pulmonary embolism (PE, 52.6% vs 43.7%, p&lt;0.001), upper extremity DVT (9.1% vs 6.0%, p&lt;0.001), and splanchnic DVT (11.1% vs 6.9%, p&lt;0.001) were more frequent among cancer patients. In contrast, leg DVT was more frequent among non-cancer patients (65.4% vs.47.2%, p&lt;0.001). While mean duration of anticoagulation was similar between groups, notable differences in 3 month and &gt; 9 month durations were evident as were initial anticoagulant choices (Table 1). Despite a well-organized protocol driven and guideline sanctioned management strategy, patients with active cancer experienced a 2.2-fold higher rate of VTE recurrence (p&lt;0.001) and a 1.8 fold higher rate of major bleeding (p&lt;001) compared to non-cancer patients (Table 2). CRNMB rates did not differ by cancer status. Conclusions: In this large prospective, guideline-driven and patient-centric registry of VTE management, patients with cancer had significantly higher rate of VTE recurrence and major bleeding, compared to non-cancer patients. These data provide important estimates for power calculations for future randomized trials of VTE treatment.

Background: Reduced or low-dose direct oral anticoagulants (DOACs) have been studied in randomized control trials for the extended prevention of venous thromboembolism (VTE) after 6 months of treatment at full, therapeutic doses. The real-world effectiveness as well as utilization of this approach in clinical practice compared to continuing at therapeutic doses is unclear. Aims: Examine the effectiveness, safety and utilization of reduced-dose DOACs in cancer patients and overweight patients. Methods: Consecutive patients with VTE were identified using the Mayo Clinic VTE Registry from March 1st, 2013 to December 31st, 2021. Patients were followed prospectively for outcomes of VTE recurrence, death, major bleeding and clinically relevant non major bleeding (CRNMB) either in person or by survey. Patients with recurrent VTE or bleeding during the first 3 months were excluded from further analysis. After completion of anticoagulation treatment for 3 months with either rivaroxaban or apixaban, patients continuing anticoagulation were evaluated in a nested case-control study. Results: A total of 404 patients (283 (70%) on apixaban and 121 (30%) on rivaroxaban) were identified in the low dose DOAC and 3060 in the full dose anticoagulation group. Overall, the mean age was 60.7 years (SD 14.4), mean weight was 89.9 kg (SD 23.8) and 55.1% were males. Within the full cohort, patients with active cancer were less likely to be prescribed low dose DOACs (HR 0.56; 95%CI 0.42-0.73; p&lt;0.001). However, low dose DOAC prescription was more likely in patients with pulmonary embolism alone (HR 1.48; 95%CI 1.21-1.80; p&lt;0.001) or in combination with DVT (HR 1.54; 95%CI 1.25,1.90; p&lt;0.001). Patients transitioned to low dose DOACs had similar age, sex and weight compared to the full dose anticoagulation group, however, fewer patients with weight ≥120 kg had reduced dosing (HR 0.68; 95%CI 0.46,0.99; p=0.046). The mean time to start of a low dose DOAC was 5.1 months overall, 5.4 months in cancer patients, and 3.6-4.9 months in non-cancer patients (Table 1). Non-cancer patients had significantly lower transition numbers in those ≥120kg (HR 0.62; 95%CI 0.40,0.97; p=0.038). In non-cancer patients In comparing weight, ≥120kg to &lt;120kg, in the low dose group, only death was statistically different with higher risk in those ≥120kg (HR 6.44; 95%CI1.27,32.81; p=0.025). Cancer patients transitioned to low dose DOACs around 5 months on average with a median of 3.3 months. Apixaban continued to be the dominant DOAC used (78%) in the low dose group. The cancers with the most patients on low dose DOACs include lymphoma, prostate, melanoma, ovarian, and breast. There was no significant difference in VTE recurrence or death in the cancer group on different DOAC doses. Conclusion: Our results show that anticoagulant prescribers are not always waiting until 6 months to transition to low doses and low doses are being utilized in cancer patients despite lack of cancer-specific studies during the analyzed time period. Although the sample size limits the precision of this analysis, we did not find statistically significant increases in VTE recurrence with low dose DOACs in either cancer patients or with elevated body weight. We did find CRNMB but not MB was observed more frequently in weights above 120kg, possibly from unadjusted confounding in this unadjusted analysis.

Background: Guidelines recommend placement of inferior vena cava (IVC) filters in patients with acute thrombotic episodes and a concurrent contraindication to anticoagulation, however filter placement during or immediately postpartum presents significant technical challenges. The use and complications of IVC filters in the peripartum period is poorly documented in current literature. Objective(s): To evaluate the use of and outcomes related to IVC filters in an obstetric population at a large tertiary care center. Study Design: Retrospective review of all patients at a tertiary academic medical center from 2001-2016 who either conceived with an IVC filter in place or underwent IVC filter placement during the antepartum or postpartum interval. Manual abstraction of each chart was performed, with data stored in a RedCap database. Results: A total of 24 patients were included in the final analysis: 5 with IVC filter placement prior to pregnancy, 7 with antepartum placement, and 12 with postpartum placement. One patient had multiple pregnancies during our study timeframe and was therefore included twice. The cohort of postpartum placement were the youngest mean age (23.7 years), had a higher number of IVC filters placed for polytrauma (n=4), and had the shortest time to removal (135.9 days). The vast majority (91.3%) of IVC filters placed during pregnancy were retrievable filters in the suprarenal position, while most deployed in an infrarenal position (83.3%) when placed prior to conception. Complications encountered included multiple attempts to remove IVC filter, severe angulation, embedded struts, fracture, and one case of cardiac tamponade during filter placement requiring emergent sternotomy and evacuation. Of the filters requiring multiple attempts for removal, in 1 patient (4%) it was unable to be removed despite multiple attempts and the filter was ultimately left in situ. Complications were more common when placement was performed prior to pregnancy or antepartum (40% and 57.1% respectively) versus postpartum (16.7%). From an obstetrical perspective, 1 patient (4%) required early preterm delivery due to preeclampsia; 1 maternal death occurred in a postpartum patient who experienced a massive pulmonary embolism and subsequently died despite emergent thrombectomy and IVC filter placement, and 1 neonatal death occurred due to congenital heart disease following periviable preterm delivery. Conclusion(s): In our study across 16 years at a large academic medical center we identified 23 patients who had an IVC filter placed prior to pregnancy or placed during the antepartum or postpartum periods. Data from our experience suggested a higher incidence of complications with preconceptual and antepartum placement, although the majority of these did not impact clinical outcomes. While not frequently needed, IVC filters remain an option for clinicians treating pregnant and postpartum patients but should be considered a last resource as they can lead to various complications.

We identified a patient with a recently described syndrome, monoclonal gammopathy of thrombotic significance (MGTS; Blood. 2023 Apr 6;141(14):1772-1776), and three additional patients with high 4Ts scores who were consistently negative in the PF4-polyanion HIT ELISA (Lifecodes PF4 IgG, Immucor). The MGTS patient, with a monoclonal IgG kappa, had recurrent thrombosis, and transient mild thrombocytopenia (nadir in the low 100s) over a period of years, and was noted to have a HIT ELISA optical density (OD) of 0.117. The three HIT patients experienced thrombocytopenia and thrombosis with ELISA ODs of 0.37, 0.18 and 0.20. All patients were positive in platelet-activation (functional) testing demonstrating PF4 dependence and inhibited with both high concentrations of heparin (100U/mL) and the FcγRIIa blocking monoclonal antibody (mAb) IV.3, consistent with the presence of anti-PF4 antibodies in the patient samples ( data not shown). Because the serologic profile of these patients suggested a novel HIT subtype characterized by negative HIT ELISA results, we undertook a functional platelet assay screen of 500 consecutive HIT ELISA-negative patients tested in our diagnostic laboratory. Research studies were approved by the Institutional Review Board of Mayo Clinic. Of the 500 patients tested, 20 (4.0%) stimulated platelet activation in the PF4-dependent P-selectin Expression Assay (PEA ≥19%; data not shown). To exclude non-specific activation that can be induced by HLA antibodies, additional testing was performed to evaluate whether platelet activation was PF4-dependent using buffer or PF4-treated platelets. Three patients demonstrated PF4-dependent activation that was inhibited by high heparin concentrations and mAb IV.3, as would be expected for HIT antibodies (ELISA-negative HIT, EN-HIT1-3; Figure 1). On retrospective review, all three patients thus identified had clinical histories and courses consistent with high clinical probability for HIT. To develop tools to study this new class of antibodies, monoclonal HIT antibodies were generated in mice after PF4/heparin immunizations and screened using a novel approach that included simultaneous testing of hybridoma supernatants in the PEA and PF4-polyanion ELISA. This strategy was designed to enabled us to identify mAbs that activated platelets (in the PEA), but that did not bind antigenic targets in the HIT ELISA. A novel mAb 431.4 that was developed using this approach, and the well-characterized HIT-like mAb KKO were evaluated for their abilities to both bind PF4-polyanion targets in ELISA, and to activate PF4-treated platelets in the PEA (Figure 2). In significant contrast to KKO, mAb 431.4 did not bind PF4/polyanion complexes, however, like KKO, strongly activated platelets in a PF4-dependent manner. Activation induced by both KKO and mAb 431.4 was inhibited by high heparin concentrations, as would be expected for HIT antibodies. In vivo murine studies using this novel mAb are pending at this time. In summary, the non-canonical diagnostic profile of HIT ELISA-negative but platelet activation-positive antibodies were found at a relatively high incidence in HIT-suspected patients (0.6%; 3 of 500 ELISA-negative patients). These findings have important diagnostic/management implications and suggest a re-evaluation of ASH's HIT management guidelines as noted in recommendations 2.7 and 2.8 of that document (“In patients with an intermediate (Recommendation 2.7) or high (Recommendation 2.8)-probability 4Ts score and a negative immunoassay, the ASH guideline panel recommends discontinuation of the non-heparin anticoagulant and resumption of heparin, if indicated ”; Blood Adv (2018) 2 (22): 3360-3392). Figure 1. A subset of ELISA-negative HIT-suspected patients harbor anti-PF4 platelet-activating antibodies. Three ELISA-negative (EN) HIT patient samples from a screen of 500 samples demonstrate PF4-dependent platelet activation and inhibition with high heparin concentration and mAb IV.3 incubation. PBS, phosphate buffered saline; IC, isotype control; HDH- high dose heparin (100U/mL). Figure 2. Murine mAb 431.4 serologically mimics pathogenic ELISA-negative HIT/MGTS antibodies. ELISA and PEA testing was performed using the “HIT-like” mAb KKO, novel mAb 431.4, or an isotype control (IC) antibody. PVS-polyvinyl sulfonate (polyanion used in the Immucor IgG ELISA assay).

AbstractBackgroundBier anemic spots, cyanosis with urticaria‐like eruption (BASCULE) syndrome is a recently described entity with episodic urticarial lesions and white anemic halos on a background of erythrocyanosis, commonly affecting the lower extremities. Possible association with autonomic dysfunction remains poorly understood. Existing publications are limited, but the condition is suggested as highly underrecognized.ObjectiveTo further characterize clinical and epidemiologic data for BASCULE syndrome.MethodsWe performed an IRB‐approved retrospective chart review on patients with BASCULE syndrome evaluated at Mayo Clinic from April 2021 to November 2022.ResultsA total of 17 patients were identified (13 female, 4 male). Median age of onset was 12 years (range 9–17). Lower extremities were involved in all patients (17). Most patients were symptomatic with pruritus (8) or burning pain (8); three were asymptomatic. Triggers were standing (11), hot showers or hot environments (7), or no clear trigger (4). Autonomic dysfunction was present in 10 patients. Treatment responses were observed from propranolol (3) and high‐dose cetirizine (1).ConclusionNovel epidemiologic data from 17 pediatric and young adult patients with BASCULE syndrome further supports an association with autonomic dysfunction and suggests a higher prevalence than previously acknowledged.