Hodge, David O.

AbstractBackgroundSimultaneous liver kidney (SLK) transplant protects against acute cellular rejection. In 2017, UNOS implemented a “safety net” policy to allow patients with renal recovery to avoid renal transplantation. Whether kidney after liver transplantation (KALT) increases the risk of rejection is unknown.MethodsWe performed a retrospective analysis of the Organ Procurement and Transplantation Network (OPTN) database of adult patients who received liver transplant, SLK or KALT between 2010 and 2020. We examined rejection of the liver within 6 months and 1 year of the liver transplant, as well as rejection of the kidney within 6 months and 1 year of receiving the kidney, as well as patient and graft loss.ResultsSixty‐six thousand seventy‐nine patients were transplanted; 60 168 with liver transplant alone, 5627 with SLK, and 284 with KALT. Acute or chronic liver rejection rates within 6 or 12 months were statistically higher in the KALT group (10.0% and 10.9%) compared to the SLK group (6.1% and 7.5%), but comparable to the LTA group (9.3% and 11.1%). Kidney rejection and graft survival rates were not different. Liver graft survival was worse in KALT than SLK or LTA (Kaplan‐Meier estimates .61 vs. .89 and .90), but these patients were more ill at the time of transplantation. KDPI and LDRI scores were notably lower in the SLK than KALT group. Patient survival was not clinically different between the groups.ConclusionKALT does not increase the risk of acute or chronic kidney rejection. SLK has a lower risk of early liver rejection, but this effect diminishes by one year to being not clinically different compared to KALT. Given that KALT is immunologically safe, and potentially avoids unnecessary renal graft use, it should be preferred over SLK.Brief summaryPatients undergoing sequential kidney after liver transplant do not have an increased risk of liver or kidney rejection when compared to liver transplant alone or simultaneous liver and kidney transplant.

Abstract Aims Recently, deep learning artificial intelligence (AI) models have been trained to detect cardiovascular conditions, including hypertrophic cardiomyopathy (HCM), from the 12-lead electrocardiogram (ECG). In this external validation study, we sought to assess the performance of an AI-ECG algorithm for detecting HCM in diverse international cohorts. Methods and results A convolutional neural network-based AI-ECG algorithm was developed previously in a single-centre North American HCM cohort (Mayo Clinic). This algorithm was applied to the raw 12-lead ECG data of patients with HCM and non-HCM controls from three external cohorts (Bern, Switzerland; Oxford, UK; and Seoul, South Korea). The algorithm’s ability to distinguish HCM vs. non-HCM status from the ECG alone was examined. A total of 773 patients with HCM and 3867 non-HCM controls were included across three sites in the merged external validation cohort. The HCM study sample comprised 54.6% East Asian, 43.2% White, and 2.2% Black patients. Median AI-ECG probabilities of HCM were 85% for patients with HCM and 0.3% for controls (P < 0.001). Overall, the AI-ECG algorithm had an area under the receiver operating characteristic curve (AUC) of 0.922 [95% confidence interval (CI) 0.910–0.934], with diagnostic accuracy 86.9%, sensitivity 82.8%, and specificity 87.7% for HCM detection. In age- and sex-matched analysis (case–control ratio 1:2), the AUC was 0.921 (95% CI 0.909–0.934) with accuracy 88.5%, sensitivity 82.8%, and specificity 90.4%. Conclusion The AI-ECG algorithm determined HCM status from the 12-lead ECG with high accuracy in diverse international cohorts, providing evidence for external validity. The value of this algorithm in improving HCM detection in clinical practice and screening settings requires prospective evaluation.

Abstract Multiple myeloma (MM) therapeutics have evolved tremendously in recent years, with significant improvement in patient outcomes. As newer treatment options are developed, stem cell transplant (SCT) remains an important modality that provides excellent disease control and delays the progression of disease. Over the years, SCT use has increased overall in the U.S., but two distinct gaps remain, including suboptimal use overall, and racial-ethnic disparities. We evaluated the National Cancer Database (NCDB) to study what sociodemographic factors might play a role within a given racial-ethnic group leading to disparate SCT utilization, such that targeted approaches can be developed to optimize SCT use for all. In nearly 112,000 cases belonging to mutually exclusive categories of non-Hispanic Whites (NHW), non-Hispanic Blacks (NHB), Hispanics, non-Hispanic Asians (NHA), and others, we found certain factors including age, comorbidity index, payor type, facility type (academic vs. community) and facility volume to be uniformly associated with SCT use for all the racial-ethnic groups, while gender was not significant for any of the groups. There were several other factors which had a differential impact on SCT utilization among the various race-ethnicity groups studied, including year of diagnosis (significant for NHW, NHB and Hispanics), income level (significant for NHW and Hispanics), literacy level (significant for NHW and NHB), and geographic location of the treatment facility (significant for NHW and NHA). The suboptimal SCT utilization overall in the U.S., suggests that there may be room for improvement for all, even including the majority NHW, while we continue to work on factors that lead to disparities for the traditionally underserved populations. This study helps identify sociodemographic factors that may play a role specifically in each group and paves the way to devise targeted solutions such that resource utilization and impact can be maximized.

Objective The aims of this study were to assess whether a relationship between anti–SSA-52 and interstitial lung disease (ILD) can be further defined, and to enhance screening, detection, and potentially guide treatment. Methods A historical cohort study of 201 patients was conducted at a single tertiary care center between January 1, 2016 and December 31, 2020. All included patients were anti–SSA-52 antibody positive. Chart review was performed for laboratory values, symptoms, pulmonary function tests, treatment, and imaging. Chest computed tomographies were reviewed by chest radiologists. Results Among anti–SSA-52 antibody–positive patients, ILD was found in 125 (62.2%) compared with 76 (37.8%) with no ILD (p = 0.001). For those with ILD, 78 (62.4%) were diagnosed with connective tissue disease (CTD)–associated ILD, 28 (22.4%) were diagnosed ILD only, and 19 (15.2%) met the criteria for interstitial pneumonia with autoimmune features. In patients with CTD-ILD, 18 (23.0%) had their ILD diagnosis made over 6 months before a CTD diagnosis, and an additional 43 (55.1%) had their ILD and CTD diagnosed within 6 months of each other (p < 0.001). Common computed tomography patterns were nonspecific interstitial pneumonia/organizing pneumonia overlap in 44 (35.2%), 25 (20.0%) nonspecific interstitial pneumonia, and 15 (12%) usual interstitial pneumonia. Twenty-eight (35.9%) had antisynthetase syndrome, followed by 16 (20.5%) with dermatomyositis, 10 (12.8%) with CTD overlap, and 6 (7.7%) with systemic scleroderma. Conclusions There was a significant association between anti–SSA-52 antibodies and ILD across a wide spectrum of rheumatological diagnoses. A significant portion of patients were diagnosed with ILD either at the same time or before their CTD diagnosis. Further study will be needed to assess effective treatment and response.

Abstract Premortem clinical presentation of cancer‐associated non‐bacterial thrombotic endocarditis (Ca‐NBTE), therapy, and the clinal course is limited to case reports and small clinical series. An electronic search of Mayo Clinic records (03/31/2002–06/30/2022) with a subsequent manual review was performed to identify adult patients with echocardiographically detected NBTE and active malignancy, excluding those with infectious endocarditis or lupus anticoagulant/antiphospholipid antibodies. In this retrospective cohort study, we analyzed 115 Ca‐NBTE patients (mean age 63.2 ± 9.7 years, 66.1% female) involving 71 (61.7%) mitral, 58 (50.4%) aortic, 8 (6.9%) tricuspid, and 1 (0.9%) pulmonary valve. The most common cancer was lung ( n = 45 cases (39.1%), followed by pancreatic ( n = 19, 16.5%), gynecological (17, 14.8%), gastrointestinal ( n = 10, 8.7%), and 10 (8.7%) with hematologic malignancy; 6 patients had two active cancers. Embolic complications at presentation were frequent: 94 (81.7%) brain, 11 splenic, 10 renal, 6 coronary, and 4 to the extremities. Of 104 anticoagulated patients, 60 received low molecular weight heparin, 17 unfractionated heparin, 16 apixaban, 8 warfarin, and 3 rivaroxaban. There were 18 arterial thromboembolisms; the Kaplan–Meier estimates of the incidence at 2 years were consistent with a rate of 15.9% [95% Confidence Interval (CI) 9.9–23.3], including 14 strokes (12.4%, 95%CI, 7.1–19.2), and 8 other arterial emboli (10.5%, 95%CI, 4.7–18.9); there were 10 venous thromboembolisms (8.9%, 95%CI, 4.5–15.0). Fourteen major bleedings occurred (12.8%, 95%CI, 7.3–19.9) and 94 patients died during follow‐up (77.9%, 95%CI, 71.1–85.8). Ca‐NBTE predominantly affected women with lung adenocarcinoma or digestive tract cancers and manifested by stroke with high mortality and frequent embolic and bleeding complications during anticoagulation therapy.

Background: Identifying the projected incidence of hepatobiliary cancers and recognizing patient cohorts at increased risk can help develop targeted interventions and resource allocation. The expected incidence of subtypes of hepatobiliary cancers in different age groups, races, and genders remains unknown. Methods: Historical epidemiological data from the Surveillance, Epidemiology, and End Results (SEER) database was used to project future incidence of hepatobiliary malignancies in the United States and identify trends by age, race, and gender. Patients ≥18 years of age diagnosed with a hepatobiliary malignancy between 2001 and 2017 were included. US Census Bureau 2017 National Population projects provided the projected population from 2017 to 2029. Age–Period–Cohort forecasting model was used to estimate future births cohort-specific incidence. All analyses were completed using R Statistical Software. Results: We included 110381 historical patients diagnosed with a hepatobiliary malignancy between 2001 and 2017 with the following subtypes: hepatocellular cancer (HCC) (68%), intrahepatic cholangiocarcinoma (iCCA) (11.5%), gallbladder cancer (GC) (8%), extrahepatic cholangiocarcinoma (eCCA) (7.6%), and ampullary cancer (AC) (4%). Our models predict the incidence of HCC to double (2001 to 2029) from 4.5 to 9.03 per 100,000, with the most significant increase anticipated in patients 70–79 years of age. In contrast, incidence is expected to continue to decline among the Asian population. Incidence of iCCA is projected to increase, especially in the white population, with rates in 2029 double those in 2001 (2.13 vs. 0.88 per 100,000, respectively; p < 0.001). The incidence of GC among the black population is expected to increase. The incidence of eCCA is expected to significantly increase, especially among the Hispanic population, while that of AC will remain stable. Discussion: The overall incidence of hepatobiliary malignancies is expected to increase in the coming years, with certain groups at increased risk. These findings may help with resource allocation when considering screening, treatment, and research in the coming years.

Précis: Damage to disposable selective laser trabeculoplasty (SLT) lenses correlated with the amount of total laser energy. Furthermore, greater lens damage was associated with diminished patient treatment response. Purpose: Disposable SLT lenses have been observed to be damaged during use by laser, potentially affecting therapeutic response. This study sought to identify factors associated with the magnitude of lens damage and its effect on treatment outcomes. Patient and Methods: We analyzed 113 eyes from 82 patients who underwent SLT between 2020 and 2021 at an American academic medical center. For each procedure, we recorded baseline patient characteristics, procedure settings, physician age (as a possible factor causing laser defocus due to accommodation), and area of lens damage. Treatment response was calculated as the difference between preoperative and postoperative intraocular pressure (IOP). Results: Area of lens damage was associated with greater total laser energy (r=0.34, P<0.001) and greater mean energy per application (r=0.37, P<0.001). IOP reduction decreased with increasing lens damage (r=−0.19, P=0.022). Lens damage was not associated with patient characteristics indicative of glaucoma severity or user settings (physician age and slit lamp used). Greater IOP reduction was associated with higher preop IOP (r=0.46, P<0.001) and a smaller cup-to-disc ratio (r=0.22, P=0.036). IOP reduction was not associated with retinal nerve fiber layer thickness, patient age, or the number of glaucoma medications. Conclusions: Increased laser damage to disposable SLT lenses was associated with diminished treatment effect. The amount of damage was correlated with total and average laser energy, but not patient or physician factors. Overall, these findings call for reconsideration of using disposable SLT lenses as part of routine practice.

Background: Ca-NBTE primarily affects the mitral valve (MV) and aortic valve (AV), with rare involvement of the right heart valves. Premortem descriptions of this condition are limited to a few case reports. This study presents an initial clinical series focusing on patients with Ca-NBTE specifically affecting their right heart valves. We describe the underlying cancers, types of valve lesions, and associated embolic complications. Patients and Methods: A electronic search of medical records (March 31, 2002, to June 30, 2022) was followed by a manual review to identify adult patients with echocardiographically detected NBTE, active cancer, and no infectious endocarditis or lupus anticoagulant/antiphospholipid antibodies. Results: Out of 115 identified patients with Ca-NBTE (mean age 63.2±9.7 years, 66.1% female), there were 8 cases (7.0%) affecting right heart valves (mean age 64.5±12.1 years, 3 females) with underlying cancer: pancreatic (n=3), lung (n= 2), genitourinary (n=1), gastric (n=1) and neck sarcomatoid carcinoma (n=1). TV was affected in 8 patients and PV in one case; 4 patients had Ca-NBTE limited only to PV, 2 patients had MV and TV, 1 patient had mitral, aortic and TV, and 1 patient with pancreatic cancer had all four valves affected by NBTE. 5 patients had embolic complications to the brain with one patient in that group also experiencing emboli to the kidney and spleen. Out of 4 patients with NBTE limited to TV, two still had brain emboli, one had only pulmonary embolism, and one patient had no embolic complications. Conclusion: Around 7% of Ca-NBTE cases involve the right heart valves, with half of these cases limited to the TV. The cancer profile in these cases resembles that seen in left heart valve involvement.

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.

Introduction: Pulmonary vein thrombosis (PVT) is often diagnosed incidentally but data on its management and outcomes are sparse. Methods: We queried our institutional health record to identify patients ≥18 years of age diagnosed with PVT. Demographics, medications, risk factors, diagnostics, treatment, and sequelae were collected by manual chart review. Suspected tumor thrombus cases were excluded. Results: Seventy-two patients with PVT were identified (median age 62 years, 50% male). The cohort was mostly white (85%), overweight (BMI 26 kg/m), with frequent comorbidities including hypertension (44%), hyperlipidemia (38%), atrial fibrillation/flutter (29%), and history of venous thromboembolism (21%). The most common PVT risk factors were active malignancy (54%), lobectomy (21%), surgery within 30 days (19%), and extrinsic vein compression (15%). Most PVT were diagnosed by CT (86%) and affected a single vein (86%), mostly commonly the left upper PV (32%). Laboratory studies revealed median platelet count 243 х 10 9 cells/L (n=58) and D-dimer elevated in 6 patients when measured (67%, n=9). About one-third of patients were on therapeutic anticoagulation (37%) at PVT diagnosis. Most patients were started on new anticoagulation (78%, n=56), with unfractionated heparin as the most common initial therapy (68%). Of those anticoagulated, few were treated with a limited duration (20%, n=11, median 54 d, IQR 95) while most received indefinite anticoagulation (80%, n=45), primarily warfarin (45%), apixaban (24%), or enoxaparin (21%). Serial imaging was obtained in 69% (n=50, median 65 d, IQR 116) and demonstrated resolution of PVT in 32 (64%) patients. Common PVT complications noted were as follows: 4 year risk of LA thrombus (26%, 12/16 anticoagulated), mechanical ventilation (13%), pneumonia (9%), and ischemic stroke (9%, 5/6 anticoagulated). Conclusions: PVT is often associated with active malignancy, lobectomy, recent surgery, and extrinsic vein compression. Most PVT resolve on serial imaging. Clinicians should be aware of potential high-risk sequelae including LA thrombus and stroke as well as high anticoagulation failure rates when managing PVT.