Citations

Introduction: Complex congenital heart disease (CHD) patients with atrial arrhythmias have higher rates of morbidity and mortality compared to less complex CHD patients. This study aims to identify echocardiographic predictors of thromboembolism (TE) and major bleeding in patients with Tetralogy of Fallot (ToF) or Pulmonary Atresia with Intact Ventricular Septum (PA-IVS) and atrial fibrillation or flutter (AF). Methods: This cohort study included patients with ToF or PA-IVS who had a diagnosis of AF who underwent a TTE across three sites. Outcomes were incidence rate of major bleeding or TE, calculated using univariable and multivariable cox regression with interaction for anticoagulant choice and fractional area change (FAC). The HAS-BLED score was augmented with major predictors of bleeding, and receiver operator curves compared. Results: We included 300 patients (287 ToF [95.7%], 13 PA-IVS [4.3%]), mean age 45.6 years. Most received warfarin (227 [79.4%]), 40 (13%) used DOACs, and 5 (1.6%) used enoxaparin. TTE predictors of TE included large LVOT diameter ≥3cm (HR 8.92, p=0.002), small LVOT VTI (p=0.014), FAC <30% (HR 7.08, p=0.026) and moderate RV dysfunction (HR 10.75, p=0.026). Predictors of major bleeding included moderate tricuspid regurgitation (HR 2.40, p=0.022), right atrial pressure (1.12, p<0.001), severe RA enlargement (HR 2.30, p=0.048), RV mid diameter (HR 1.06, p=0.005), RV end diastolic area (HR 1.04, p=0.021), RV end systolic area (HR 1.05, p=0.016) elevated RVSP and FAC ≤45% (HR 0.37, p=0.016). Among warfarin users, impaired RV function (FAC ≤45%) was linked to reduced major bleeding events (HR 0.27, p=0.025). There was a nonsignificant trend towards higher bleeding in DOAC users with FAC >45% (HR 3.87, p=0.284), but significantly higher bleeding in DOAC users with FAC ≤45% (HR 12.41, p=0.008) vs. warfarin users with normal RV function (table 1). We developed an augmented HAS-BLED score: the standard score plus one point for moderate-to-severe pulmonic or tricuspid regurgitation and one for FAC ≤45%. This outperformed the standard HAS-BLED in predicting major bleeding (AUC 0.67 augmented vs. 0.57 un-augmented, p=0.008) (figure 1). Conclusion: Echocardiographic evidence of right heart disease is a strong predictor of major bleeding in patients with ToF or PA-IVS. FAC is a useful tool to determine excess major bleeding risk, particularly in DOAC users. Augmenting HAS-BLED with right heart parameters improves diagnostic accuracy.

Abstract Understanding tumor cell dynamics can improve prognosis and treatment but remains limited for lung adenocarcinoma in people who have never smoked (NS-LUAD). With RNA sequencing data from 684 NS-LUAD cases and validation in an independent dataset, we identified three subtypes with distinct phenotypic traits and cell compositions. Additional genomic and histologic data further characterized the subtypes. “Steady,” marked by low proliferation, high alveolar cell fraction, moderate-to-well differentiation, and fewer driver gene alterations, is linked to prolonged survival and low immune evasion. “Proliferative” shows high proliferation markers, TP53 mutations, and gene fusions. “Chaotic,” with high epithelial-to-mesenchymal transition markers, has the worst prognosis, even within stage I tumors. Lacking known molecular or histologic characteristics, this aggressive subtype is solely identified by transcriptomic data. A 60-gene signature recapitulates the classification and predicts survival even within subgroups based on tumor stage or known genomic features, emphasizing its potential for improving early-stage NS-LUAD prognostication in clinical settings. Significance: The transcriptome of 684 NS-LUAD identifies three subtypes with different cellular dynamics and genomic and morphologic features. A 60-gene signature accurately stratifies subjects for mortality risk, even in stage I, offering a potential clinically applicable tool for treatment decision-making in patients with NS-LUAD. See related commentary by Azizi et al., p. 423

Abstract INTRODUCTION M0 images were missing in Siemens ASL data in Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, prohibiting cerebral blood flow (CBF) quantification. METHODS A conditional latent diffusion model was trained and evaluated on in‐house datasets, then applied to the Siemens data in ADNI‐3. Regional CBF differences by Alzheimer's disease (AD) stages, their accuracy for AD classification, and CBF trajectory slopes were compared between generated data (Siemens) and acquired data (General Electric). RESULTS The diffusion model generated M0 images with high fidelity (SSIM = 0.918 ± 0.023, PSNR = 31.361 ± 2.537) and minimal CBF bias (mean difference is 0.21 ± 1.58 mL/100 g/min). Both generated and acquired CBF showed similar spatial patterns and decreasing trends with AD progression in specific AD‐related regions. Generated CBF also improved accuracy in classifying AD stages compared to qualitative perfusion images. CONCLUSION This study shows the potential of diffusion models for imputing missing modalities in large‐scale studies exploring the use of ASL as a biomarker of AD. Highlights Using latent diffusion model, we can generate M0 image from control image in arterial spin labeling (ASL) with high fidelity. The generated M0 can be used for cerebral blood flow (CBF) quantification in Alzheimer's Disease Neuroimaging Initiative dataset. The performance of classification between Alzheimer's disease (AD) patients and cognitive normal people is better when using generated CBF maps than using non‐quantitative perfusion images. ASL CBF decreases with AD progression in key AD‐related brain regions.

Anthracyclines are potent chemotherapeutic agents, yet their clinical use is hampered by their cardiotoxicity. Anthracyclines achieve potent anti- cancer effects primarily via TOP2A, but at the same time they induce a dose limiting cardiotoxicity through TOP2B. The use of a catalytic TOP2 inhibitors such as dexrazoxane (ICRF 187) significantly reduces the incidence of anthracycline-induced cardiotoxicity. However, dexrazoxane targets the highly conserved TOP2 dimer interface that is identical between TOP2A and TOP2B, fostering persisting concerns that its inhibition of TOP2A isoenzyme may interfere with anthracycline anticancer effects and augment anthracycline-induced myelosuppression. Thus, isoform- selective TOP2 inhibitors that can control the DNA damage caused by TOP2A vs TOP2B are a significant unmet clinical need. We have developed a new class of highly potent and TOP2B-selective catalytic inhibitors through rational design by building upon the general pharmacophore present in isolates from Calophyllum Brasiliense. Using X-ray crystallography, we demonstrate that our newly developed compounds occupy a previously unidentified druggable binding-site in the TOP2 ATPase domain and function as a physical barrier to block the conformational change triggered by ATP hydrolysis. We have named the class of inhibitors that target this site “obex”, the Latin word for obstacle. The obex binding site contains residues that differ between the TOP2A and TOP2B isoenzymes, based on which we rationally designed, prepared, and systematically evaluated a targeted panel of obex inhibitors. We have identified the lead molecule, namely, topobexin, as the first- in-class TOP2B-specific obex inhibitor that can prevent anthracycline-induced DNA damage. This first TOP2 isoform-specific inhibition underscores the broader potential to improve drug specificity and minimize adverse effects in various medical treatments.

Importance Adverse events in otolaryngology–head and neck surgery (OHNS) are inconsistently reported. The Clavien-Dindo Classification has been modified and validated in several surgical subspecialties but has yet to be validated in OHNS. Objective To create and validate a modified Clavien-Dindo Classification for OHNS that reflects the severity and duration of harm for complications experienced by patients undergoing OHNS. Design, Setting, and Participants This is a multicenter survey study of subject matter experts (SMEs) from OHNS subspecialties from academic institutions within the US. A literature review identified publications reporting surgical complications in OHNS in the English language between January 2019 and April 2020. Complications were summarized and used to inform a modified Clavien-Dindo Classification. Feedback from internal SMEs was incorporated. Thirty-five clinical vignettes were created, and an electronic survey was sent to SMEs at outside institutions. Each SME was randomly assigned to 1 of 4 groups to evaluate 8 to 9 vignettes. The survey was conducted in September 2023, and data were analyzed from February to May 2024. Exposure Participation in the electronic survey. Main Outcomes and Measures Vignette scores were assessed and the Comprehensive Complication Index (CCI) calculator was used to assess cumulative morbidity. The scale is based on the grading by the Clavien-Dindo Classification and reflects overall morbidity on a scale from 0 (no complication) to 100 (death). Variability of the CCIs between reviewers, the primary outcome, was summarized with the SD. The percentage of reviewers with a high (≥26.2) or low (&amp;lt;26.2) CCI within a vignette was reported. Reliability was summarized using Krippendorff α. Results Of 106 SMEs, 43 (response rate, 40.6%) completed at least 1 vignette. Eighteen of 35 vignettes (51.4%; 95% CI, 34.9%-68.0%) had unanimous high CCI, and 8 of 35 vignettes (22.9%; 95% CI, 8.9%-36.8%) had unanimous low CCI (overall categorical agreement, 74.3%; 95% CI, 59.8%-88.8%). On average, the Krippendorff α was 0.74, indicating moderate reliability. A total of 21 850 OHNS complications were reviewed and categorized as surgical or medical with 12 including subcategorization for specificity. Each category was then assigned a modified OHNS Clavien Dindo classification grade. Conclusions and Relevance In this survey study of OHNS experts, a modified OHNS Clavien-Dindo Classification was developed and validated using case vignettes. The modified Clavien-Dindo Classification provided a granular subcategorization for each complication category and grade, duration of harm, and an overall summary complication score (CCI). Results suggest the modified OHNS Clavien-Dindo Classification reliably differentiated between high-grade and low-grade OHNS complications and could be utilized for assessing surgical outcomes.

Abstract Purpose: Polatuzumab vedotin (polatuzumab) was approved for up-front treatment of diffuse large B-cell lymphoma in combination with chemoimmunotherapy (Pola-R-CHP) based on the POLARIX trial. However, when stratified by cell of origin (COO), polatuzumab seems to have greater efficacy in activated B-cell than germinal center B-cell (GCB) subtype disease. Most studies of polatuzumab used RNA expression to assess COO, whereas in routine clinical practice, the immunohistochemistry-based Hans algorithm is used. Experimental Design: To assess the impact of COO by immunohistochemistry on polatuzumab efficacy, we conducted a multicenter real-world study of adults with large B-cell lymphoma (LBCL) receiving polatuzumab from 2015 to 2024, split by receipt of polatuzumab in first-line versus relapsed/refractory settings. The primary endpoint was overall response rate (ORR) to polatuzumab-based treatment in GCB versus non-GCB relapsed/refractory LBCL. Results: Of 740 patients, 305 received polatuzumab in the first-line setting and 435 in the relapsed/refractory setting. In the relapsed/refractory cohort, the ORR in non-GCB versus GCB LBCL was 59.7% versus 36.3% [OR, 2.6; 95% confidence interval (CI), 1.77–3.84; P &lt; 0.0001], with a complete response rate of 35.7% versus 17.7% (OR, 2.6; 95% CI, 1.66–4.02; P &lt; 0.0001). Progression-free survival was longer for patients with non-GCB versus GCB COO (HR, 0.64; 95% CI, 0.5–0.83; P = 0.0006). In the first-line cohort, ORR, complete response rate, and progression-free survival were similar in non-GCB versus GCB LBCL, as hypothesized based on outcomes in the Pola-R-CHP arm of POLARIX, suggesting that the addition of polatuzumab overcomes the adverse risk of non-GCB COO in patients receiving R-CHOP. Conclusions: Based on these data, COO classification by the Hans algorithm is a strong predictor of polatuzumab efficacy in LBCL, informing real-world treatment decisions.

Background: Tremor in multiple sclerosis (MS) is often refractory to medications. Deep brain stimulation (DBS) may help, but possible side effects and disease exacerbation limit its use. Objectives: Evaluate outcomes of DBS for MS-associated tremor. Methods: Retrospective review of 18 patients with MS-associated tremor who underwent DBS, analyzing Expanded Disability Status Scale (EDSS) and Fahn–Tolosa–Marin (FTM) tremor scores. Results: Median age at surgery was 49.5 years (range, 28–75), with postoperative follow-up 2.5 years (range, 0–22). No relapses (0/18) or new lesions (0/8) occurred postoperatively. All had ventral intermediate nucleus leads; other targets were not used in programming. EDSS remained stable (median 6 to 6.25; p = 0.2). FTM scores improved (median 14.5 to 10, p = 0.008). Patients with EDSS 3.5–6 had variable outcomes ( p = 0.02). Conclusions: DBS is a potential treatment for severe MS tremor and did not provoke relapse. Targeting VIM alone may optimize tremor control and maintain magnetic resonance imaging (MRI) access.

ABSTRACT As artificial intelligence (AI) continues to rapidly reshape health care, there is a critical need for clear frameworks for clinicians to ensure ethical, equitable, and effective integration and use of AI in patient care. Key integrations of AI include enhancing health communications, patient engagement, clinicians' training, pharmaceutical advertising, clinical decision‐making, and automation of clinical operations and workflow. However, there are growing concerns related to regulatory gaps, the spread of misinformation, security threats, patient and data privacy leaks, and widening health disparities gaps. These concerns are exacerbated by limited institutional infrastructure and limited AI literacy of clinicians and patients. Recent policy developments reflect efforts to guide responsible AI development and use. While progress has been made, the lack of standardized human oversight remains a critical gap, particularly as policies may not fully consider the challenges and complexities at institutional, societal, technical, and individual levels. Thus, herein, the Drug Information Practice and Research Network (DI PRN) of the American College of Clinical Pharmacy (ACCP) : (1) explores current and emerging multifaceted challenges, a call to action, and opportunities of AI integration in health care including examination of the regulatory, ethical, operational, and health equity implications; and (2) provides practical recommendations for responsible use of AI through DI PRN‐developed example case‐based approaches and best practices infographics to enhance AI literacy for diverse learners including clinicians, trainees, and patients. This DI PRN opinion paper highlights the importance of proactive governance frameworks and equips and empowers diverse learners with practical AI literacy tools to confidently engage with AI technologies in patient care.