Citations

Abstract Introduction Inflammatory bowel disease (IBD) is a chronic immune-mediated disease that includes Crohn’s disease and ulcerative colitis. People with IBD experience poor sleep health, including short and highly fragmented sleep and extraintestinal manifestations including alterations to cognitive functioning; however, the relationships between sleep health and cognitive symptoms have not been evaluated in this population. The purpose of this study was to identify the associations between sleep health and perceived cognitive impairments in adults with IBD. Methods We conducted a descriptive, correlational study of adults (18 to 59 years old) with IBD. We used the Pittsburgh Sleep Quality Index (PSQI) to obtain self-reported data on sleep health, the FACT-Cog Perceived Cognitive Impairments questionnaire to elicit cognitive symptoms, and the Manitoba IBD Index to describe IBD disease activity. Descriptive statistics, point-biserial correlations, and Pearson’s correlations were used to describe relationships. Results Of the 59 participants [Mean age 40.8 (SD 10.5), 71.2% female, 94.9% white], 67.8% (n=40) had clinically active IBD. 79.7% (n=47) had a PSQI total score >5, indicating poor sleep health. The most common cognitive symptoms, occurring two or more times a week, were trouble concentrating (55.9%), walking into a room and forgetting an intended task (44.1%), and forgetting the names of people soon after being introduced (44.0%). PSQI total score was positively and significantly correlated with 12 of 13 questions on the FACT-Cog. The strongest correlations included trouble concentrating (r = .497, P<.001), slower thinking (r = .450, p<.001), trouble forming thoughts (r=.550, p<.001), and difficulty finding the right words to express oneself (r=.546, p<.001). Longer self-reported sleep latency was associated with higher frequency of 12 out of 13 cognitive symptoms, while sleep efficiency was associated with 4 and sleep duration was associated with 2. Having clinically active IBD was associated with trouble forming thoughts (r=-.261, p=.046), slower thinking (r=-.307, p=.018), and trouble concentrating (r=-.346, p=.007). Conclusion Cognitive symptoms are common among people with IBD, highly correlated with sleep health, and not fully explained by IBD disease activity. Future studies should include objective measures of sleep health and cognition to further elucidate these relationships. Support (if any) Mayo Clinic Bonner Fund

Abstract Background: Pancreatic adenocarcinoma (PDAC) is an aggressive malignancy with dismal prognosis. Most patients present with advanced stages. Heightened levels of serum interleukin-6 (IL-6) are associated with carcinogenesis, immune suppression, and poor prognosis in PDAC. Preclinical data of dual inhibition of IL-6 and programmed death ligand-1 (PD-L1) facilitates CD8+ T-cell migration into pancreatic tumors and was effective in controlling tumor growth in syngeneic and genetically engineered PDAC mouse models. Siltuximab (Sil) is a chimeric monoclonal antibody which targets the IL-6 molecule specifically. Spartalizumab (Sparta) is a high-affinity ligand-blocking humanized IgG4 antibody against the PD-1 receptor. We developed a phase Ib/II trial to evaluate the safety, immunogenicity and preliminary antitumor activity of Sil and Sparta in metastatic PDAC (mPDAC). Methods: Patients (pts) with mPDAC who have progressed on at least one line of systemic chemotherapy were eligible for the trial. Other selected inclusion criteria were ≥18 years of age, ECOG PS 0-1 and measurable disease per RECIST v1.1. The phase Ib trial design is standard 3+3, with a primary endpoint of recommended phase II dose (RP2D). An additional 24 patients were planned for an expansion cohort. Sil was administered at escalating dose levels of 6 mg/kg (DL1) and 11 mg/kg (DL2), in combination with Sparta at 300 mg IV on day 1 of each 21-day cycle. Key secondary endpoints included overall response rate (ORR = CR + PR), progression-free survival (PFS) and overall survival (OS). Results: We enrolled 4 patients on DL1 and escalated to DL2/RP2D in the absence of a dose limiting toxicity (DLT). A total of 31 patients were subsequently treated at the RP2D (escalation + expansion). The median age was 68 years, 42% were male. Majority were White (63%) and 20% were Black. About 43% had head of pancreas primary tumors and 86% had liver involvement. The median number of lines of prior therapy was 3 (range 1-4). There was no objective response among the 4 patients on DL1; 1 had stable disease (SD) for 11 weeks as best response. 17 of 31 patients on RP2D had only a baseline assessment and came off study for progression of disease, prior to follow-up imaging assessment for response evaluation. Of the 14 RP2D patients with a follow-up assessment, ORR was 0% (3 were SD and 11 had progression of disease (PD) as best response), mPFS - 2.2 mos (95% CI: 1.9, 2.6), mOS - 5.5mos (95% CI: 2.8, 6.5). Treatment related adverse events (TRAEs) of any grade included fatigue (23%), anemia (18%), and increased liver enzymes (9.5%). There were no grade 4-5 TRAEs. Conclusions: The combination Sil/Sparta had an acceptable safety profile but did not elicit responses in advanced PDAC pts. Correlative studies using paired biopsies and blood are ongoing to determine how dual IL-6/PD-1 blockade impacts stromal and immune biomarkers in relationship to the clinical outcome measures. Funding and medications for the study were provided by Novartis and Recordati Rare Diseases Inc (NCT04191421) and NIH/NCI (R21CA266088). Citation Format: Olatunji B. Alese, Olumide Gbolahan, Kathleen M. Coleman, Yichun Cao, Sujata Kane, Sarah Craven, Emily Greene, Natalie Horvat, Andrew McDonald, Walid L. Shaib, Christina S. Wu, Mehmet Akce, Maria Diab, Jeffrey M. Switchenko, Gregory B. Lesinski, Bassel F. El-Rayes. Phase Ib study of siltuximab and spartalizumab in advanced pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr CT136.

ABSTRACT Introduction Recovering from neuromuscular injuries or conditions can be a challenging journey that involves complex surgeries and extensive physical rehabilitation. During this process, individuals often rely on orthotic devices to support and enable movement of the affected limb. However, users have criticized current commercially available powered orthotic devices for their bulky and heavy design. To address these limitations, we developed a novel powered myoelectric elbow orthosis. Materials and Methods The orthosis incorporates 3 mechanisms: a solenoid brake, a Bowden cable-powered constant torque elbow mechanism, and an extension limiter. The device controller and battery are in a backpack to reduce the weight on the affected arm. We performed extensive calculations and testing to ensure that the orthosis could withstand at least 15 Nm of elbow torque. We developed a custom software effectively control the orthosis, enhancing its usability and functionality. A certified orthotist fitted a subject who had undergone a gracilis free functioning muscle transfer surgery with the device. We studied the subject under Mayo clinic IRB no. 20-006849 and obtained objective measurements to assess the orthosis’s impact on upper extremity functionality during daily activities. Results The results are promising since the orthosis significantly improved elbow flexion range of motion by 40° and reduced compensatory movements at the shoulder (humerothoracic joint) by 50°. Additionally, the subject was able to perform tasks which were not possible before, such as carrying a basket with weights, highlighting the enhanced functionality provided by the orthosis. Conclusion In brief, by addressing the limitations of existing devices, this novel powered myoelectric elbow orthosis offers individuals with neuromuscular injuries/conditions improved quality of life. Further research will expand the patient population and control mechanisms.

Objective: The objective was to explore and describe the role of pharmacists in providing postdischarge care to patients with kidney disease. Data Sources: PubMed, Embase (Elsevier), CINAHL (Ebscohost), Web of Science Core Collection, and Scopus were searched on January 30, 2023. Publication date limits were not included. Search terms were identified based on 3 concepts: kidney disease, pharmacy services, and patient discharge. Experimental, quasi-experimental, observational, and qualitative studies, or study protocols, describing the pharmacist’s role in providing postdischarge care for patients with kidney disease, excluding kidney transplant recipients, were eligible. Study Selection and Data Extraction: Six unique interventions were described in 10 studies meeting inclusion criteria. Data Synthesis: Four interventions targeted patients with acute kidney injury (AKI) during hospitalization and 2 evaluated patients with pre-existing chronic kidney disease. Pharmacists were a multidisciplinary care team (MDCT) member in 5 interventions and were the sole provider in 1. Roles commonly identified include medication review, medication reconciliation, medication action plan formation, kidney function assessment, drug dose adjustments, and disease education. Some studies showed improvements in diagnostic coding, laboratory monitoring, medication therapy problem (MTP) resolution, and patient education; prevention of hospital readmission was inconsistent. Limitations include lack of standardized reporting of kidney disease, transitions of care processes, and differences in outcomes evaluated. Relevance to Patient Care and Clinical Practice: This review identifies potential roles of a pharmacist as part of a postdischarge MDCT for patients with varying degrees of kidney disease. Conclusions: The pharmacist’s role in providing postdischarge care to patients with kidney disease is inconsistent. Multidisciplinary care teams including a pharmacist provided consistent identification and resolution of MTPs, improved patient education, and increased self-awareness of diagnosis.

Abstract Aims Augmenting echocardiography with artificial intelligence would allow for automated assessment of routine parameters and identification of disease patterns not easily recognized otherwise. View classification is an essential first step before deep learning can be applied to the echocardiogram. Methods and results We trained two- and three-dimensional convolutional neural networks (CNNs) using transthoracic echocardiographic (TTE) studies obtained from 909 patients to classify nine view categories (10 269 videos). Transthoracic echocardiographic studies from 229 patients were used in internal validation (2582 videos). Convolutional neural networks were tested on 100 patients with comprehensive TTE studies (where the two examples chosen by CNNs as most likely to represent a view were evaluated) and 408 patients with five view categories obtained via point-of-care ultrasound (POCUS). The overall accuracy of the two-dimensional CNN was 96.8%, and the averaged area under the curve (AUC) was 0.997 on the comprehensive TTE testing set; these numbers were 98.4% and 0.998, respectively, on the POCUS set. For the three-dimensional CNN, the accuracy and AUC were 96.3% and 0.998 for full TTE studies and 95.0% and 0.996 on POCUS videos, respectively. The positive predictive value, which defined correctly identified predicted views, was higher with two-dimensional rather than three-dimensional networks, exceeding 93% in apical, short-axis aortic valve, and parasternal long-axis left ventricle views. Conclusion An automated view classifier utilizing CNNs was able to classify cardiac views obtained using TTE and POCUS with high accuracy. The view classifier will facilitate the application of deep learning to echocardiography.

AbstractChronic lung disease (CLD) is the second leading cause of pulmonary hypertension (PH) and is associated with significant morbidity and mortality. Although PH associated with CLD (PH‐CLD) leads to impaired health‐related quality of life (HRQOL), there are no validated tools to assess HRQOL in PH‐CLD. The Pulmonary Arterial Hypertension–Symptoms and Impact Questionnaire (PAH‐SYMPACT) is an HRQOL instrument aimed at assessing the symptoms and impact of PH on overall function and well‐being. We performed a single‐center prospective cohort study using PAH‐SYMPACT scores to compare symptoms, exercise capacity and HRQOL in patients with PAH and PH‐CLD. One hundred and twenty‐five patients (99 patients with idiopathic/heritable PAH and 26 with PH‐CLD) completed the PAH‐SYMPACT questionnaire which consists of 22 questions that assess HRQOL across four domains: cardiopulmonary (CP) symptoms, cardiovascular (CV) symptoms, physical impact (PI), and cognitive/emotional (CE) impact. Higher scores indicate worse HRQOL. We compared patients with PAH and PH‐CLD using a Wilcoxon rank sum or chi‐squared test as appropriate. Multivariate linear regression analysis was used to assess the relationship between PH classification and SYMPACT scores. Compared to PAH, patients with PH‐CLD were older, more likely to use oxygen and had worse functional class and exercise capacity. While there was no significant difference between the two groups in CP, CV, or CE domain scores, patients with PH‐CLD had significantly worse PI scores by univariate (1.79 vs. 1.13, p < 0.001) and multivariate analysis (1.61 vs. 1.17, p = 0.02) and overall worse SYMPACT scores (1.19 vs. 0.91, p = 0.03). In conclusion, patients with PH‐CLD have worse HRQOL as assessed by the PAH‐SYMPACT questionnaire versus patients with PAH. Although PAH‐SYMPACT has not been validated in PH‐CLD, the results of this study can guide clinicians in understanding the symptoms and impact of PH‐CLD relative to PAH.

Abstract Background Inflammatory bowel disease (IBD) management has become increasingly complex, and education varies across fellowship programs. IBD 101 was designed to introduce first-year gastroenterology (GI) fellows to IBD care and training. Methods In 2019, a cohort of fellows participated in a 1-day course with small group learning and group observed structured clinical examinations. Pre- and postcourse surveys were administered to evaluate the course. To assess the long-term impact, surveys were emailed in May 2022 to all third-year fellows from previously participating programs. The primary outcome was comfort managing IBD scenarios and information regarding each fellow’s exposure to IBD education. Results Fifty-five fellows from 32 programs participated. A total of 49 (89%) of 55 completed pre- and postcourse surveys. All fellows agreed that the course content was appropriate. In the postcourse survey, all fellows reported increased comfort managing IBD patients. Ninety-six percent of attendees stated that they would strongly recommend this course. Thirty-six fellows completed surveys in 2022, 21 (58%) attendees and 15 (42%) nonattendees. Attendees reported equivalent or higher levels of comfort compared with nonattendees. Higher global competence was noted among attendees (odds ratio, 5.21; 95% confidence interval, 0.91-29.9; P = .06) after adjusting for presence of a local IBD specialist, number of IBD patients seen monthly (≤5 vs &gt;5), and rotation through an IBD service. Conclusions IBD 101, an introductory course for first-year GI trainees, was associated with increased comfort managing IBD with a durable benefit independent of individual access to IBD education. Continuation of this program will further enhance the IBD education of future GI fellows.

AbstractBackgroundNo specific clinical rating scale currently exists for Lewy body dementia (LBD). Clinical rating scales developed for other diseases are therefore used instead for LBD clinical trials. However, these scales are not optimized for LBD and may not sufficiently reflect the complex array of LBD‐related phenomenology, making it more difficult to interpret outcome data from LBD clinical trials.MethodA working group comprised of 14 members bridging various international LBD‐focused research groups was convened to develop the first iteration of the LBD‐DRS with a focus on inclusion of key LBD related symptom domains, ensuring that any scale is mapped to regulatory expectations, and an emphasis on being patient‐centered. This draft was then subsequently presented to a broader stakeholder group (»50 participants) at the International Lewy body Dementia Conference in June 2022 for further feedback, leading to a further iteration of the scale.ResultThe LBD‐DRS has been designed to capture ratings of the frequency and severity of symptoms across the key domains relevant to LBD – cognitive, neuropsychiatric, motor, autonomic and sleep – as well as the functional impact and perceived burden of symptoms for patients and their care partners. An international Delphi exercise is now planned with many LBD‐relevant stakeholders, which will be coupled with workgroup engagement (for example, with patient‐caregiver groups) to further develop the scale with the resulting final draft anticipated for pilot use in the near future.ConclusionsIn this presentation we will elaborate on the development of the scale, key areas that it will cover as well as challenge points and next steps. Upon completion of the development and refinement of the LBD‐DRS, we propose that this scale will have utility as valid and LBD specific outcome measure in LBD clinical trials.

Background: Enlargement or dilation of the left ventricle (LV) is associated with increased cardiovascular morbidity and mortality, and is an established precursor of ventricular dysfunction and heart failure in almost all major cardiovascular conditions. Although there are existing artificial intelligence frameworks that make use of deep learning to detect LV enlargement, many entail LV segmentation, which can be error-prone especially for point-of-care ultrasound (POCUS) images. Goal: To develop a fully end-to-end deep learning framework that takes as input either transthoracic echocardiographic (TTE) or POCUS 2D image clips, and classifies directly (i.e., without first segmenting the LV) whether a patient has an enlarged LV. Methods: Using a sample of retrospective TTE data enriched for LV enlargement (out of 13,868 patients total, 3,351 had an enlarged LV defined using sex-specific guideline-directed criteria), we trained a classifier that takes as input apical 2-chamber and parasternal long axis videos, and provides as output a binary label denoting whether a patient has an enlarged LV. Then, we evaluated the trained model using a holdout testing dataset of retrospective TTE data (2,087 patients) as well as data from a prospective cohort of 428 patients from whom TTE and POCUS were collected simultaneously. Results: For the retrospective TTE testing dataset, the AUC was 0.851 (95% confidence interval (CI) of 0.830-871). For the prospective cohort, the model performed comparably for both TTE and POCUS video clips (TTE: AUC of 0.865, 95% CI of 0.823-0.906; POCUS: AUC of 0.840, 95% CI of 0.797-0.883). Conclusions: The current deep learning model performed comparably well for both TTE and POCUS echocardiograms. We regard these results as a proof-of-concept of the potential utility of this model in helping point-of-care clinicians make decisions regarding whether patients should receive further evaluation for LV enlargement and associated conditions.

Background: Diagnosis of heart failure with preserved ejection fraction (HFpEF) is challenging due to non-diagnostic imaging outputs and discordant clinical features. Using only a single videoclip from a standard transthoracic echocardiogram (TTE), we developed an artificial intelligence (AI) model to differentiate patients with HFpEF from those without HFpEF. In a separate test population, we assessed the model’s ability to predict cardiac mortality. Methods: A 3-dimensional convolutional neural network was developed and trained on apical 4-chamber videoclips to classify patients with HFpEF (cases) versus without HFpEF (controls). Overall and cardiac mortality were obtained from the National Death Index. Results: The model was independently tested in 646 cases and 638 controls from 8 centers in 4 states. Sensitivity (87.8%; 84.5-90.9%) and specificity (81.9%; 78.2-85.6%) were high and sustained in various subgroups, including increased left atrial volume index, average E/e’ ≥15, and pulmonary artery systolic pressure >35 mm Hg. During follow-up (median [IQR] 3.4 [1.7-6.5] years), 540 patients died. There were 135 cardiac deaths attributable to heart failure (47%), coronary artery disease (41%), valve disease (4%), arrhythmia (4%), and others (5%). Compared to a negative output, all-cause mortality was higher in patients with a positive (HR 2.9 [2.4-3.5]) or uncertain output (HR 1.8 [1.2-2.5]), and cardiac mortality (Figure) was also higher in patients with a positive (HR 7.7 [4.5-13.3]) or uncertain output (HR 3.4 [1.4-8.1]). Cardiac mortality differences according to AI model prediction remained after age adjustment (positive: HR 5.9 [3.3-10.4], p<0.001; uncertain: HR 2.8 [1.2-6.8], p=0.02). Conclusion: A novel AI model to detect HFpEF based on a single routinely acquired TTE videoclip also identifies those at increased risk of cardiac mortality.