Citations

ABSTRACTMedical advances have enabled the realization of vascularized composite allografts and to date have demonstrated reasonably successful graft survival rates. Larynx and Trachea Transplantation (LT) has long been contemplated as a therapeutic option for severe laryngeal trauma and patients following total laryngectomy. Progress has been limited most likely due to lack of awareness as an option, technical and surgical expertise, limited transplant centers worldwide, need for multidisciplinary engagement from hospital leadership, Otolaryngology, and transplant medicine to build a successful program. As one of the first programs to exist in the United States, we have had to create new pathways, develop new workflows, work with numerous regulatory bodies, educate many people about the need for an LT, and learn many lessons along the way. The objectives of this paper are to help others navigate the complexities of creating a new LT transplant program so that this important treatment option may become more available to patients worldwide. We will provide a checklist for developing an LT program and discuss our experiences with the strategic development of an LT transplant program in an academic medical institution.

ABSTRACTOpioid use disorder is a persistent epidemic despite several FDA‐approved medications for its treatment. While the pathogenesis of opioid use disorder has been classically attributed to dopamine pathways in the brain, there is emerging evidence and interest surrounding the role of inflammation and inflammatory signaling in its development and treatment. Buprenorphine has become the most prescribed medication for opioid use disorder, largely due to its ease of access and tolerability. This review aimed to better characterize contemporary knowledge of how buprenorphine modulates the human immune system and inflammatory functions in this population. A comprehensive review was conducted using 11 key databases, including Embase, MEDLINE, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov. This review captured 8177 records, and 14 studies were ultimately selected for inclusion and discussion in this review. Notably, all 14 clinical studies evaluated buprenorphine's effect on the peripheral immune system, and the majority of the studies supported the notion that initiation and maintenance of buprenorphine restore immune suppression caused by opioid use disorder. In addition, we discuss how recent and ongoing work utilizing advanced imaging and cellular technologies is advancing the understanding of how buprenorphine affects the immune and inflammatory signaling in the brain.

Interest in the potential applications of artificial intelligence in medicine, anesthesiology, and the world at large has never been higher. The Anesthesia Research Council steering committee formed an anesthesiologist artificial intelligence expert workgroup charged with evaluating the current state of artificial intelligence in anesthesiology, providing examples of future artificial intelligence applications and identifying barriers to artificial intelligence progress. The workgroup’s findings are summarized here, starting with a brief introduction to artificial intelligence for clinicians, followed by overviews of current and anticipated artificial intelligence–focused research and applications in anesthesiology. Anesthesiology’s progress in artificial intelligence is compared to that of other medical specialties, and barriers to artificial intelligence development and implementation in our specialty are discussed. The workgroup’s recommendations address stakeholders in policymaking, research, development, implementation, training, and use of artificial intelligence–based tools for perioperative care.

Importance and Objective: Menopause is the natural cessation of ovarian function, typically occurring at a mean age of 52 years in the United States. Vasomotor symptoms (VMS; hot flashes and night sweats) affect over 75% of midlife women and typically last 7 to 9 years, with only 54% seeking medical attention. Although hormone therapy is the most effective treatment for VMS, <4% of women currently use it, primarily due to safety concerns. There is evidence that cognitive behavioral therapy (CBT) is an effective management strategy for VMS. Virtual reality (VR) has shown promise in delivering an immersive form of CBT for various medical conditions, including acute and chronic pain, sleep, and mood disorders, potentially overcoming barriers such as access and cost while improving quality of life. This narrative review aims to summarize the existing literature on VR for managing menopause symptoms. Methods: A comprehensive literature review was conducted through PubMed and Medline databases. The search focused on keyword combinations related to VR, artificial intelligence, and menopause symptoms. Discussion and Conclusion: The search yielded one study specifically targeting symptoms related to menopause. A pilot study (n = 42) evaluating an immersive VR and artificial intelligence intervention based on CBT and mindfulness techniques for managing hot flashes in women with breast or ovarian cancer demonstrated a significant reduction in frequency of hot flashes ( P < 0.01) and improvements in sleep quality, mood, anxiety, stress, and overall quality of life. However, these women experienced hot flashes that might have been associated with their cancer diagnosis or treatment rather than relating specifically to menopause, potentially limiting the generalizability of the findings to women with menopause symptoms. Although VR has shown effectiveness in delivering CBT for other conditions, there remains a significant gap in research on its specific use for menopause-related symptoms.

Background and Aims: Clinical hepatology research often faces limited data availability, underrepresentation of minority groups, and complex data-sharing regulations. Synthetic data—artificially generated patient records designed to mirror real-world distributions—offers a potential solution. We hypothesized that diffusion models, a state-of-the-art generative technique, could produce synthetic liver transplant waitlist data from the United Network for Organ Sharing database that maintains statistical fidelity, replicates clinical correlations and survival patterns, and ensures robust privacy protection. Approach and Results: Diffusion models were used to generate synthetic patient cohorts mirroring the United Network for Organ Sharing liver transplant waitlist database between the years 2019 and 2023. Statistical fidelity was assessed using maximum mean discrepancy (MMD) and Wasserstein distance, correlation analysis, and variable-level metrics. Clinical utility was evaluated by comparing transplant-free survival via Kaplan–Meier curves and the MELD score performance. Privacy was quantified using the Distance to Closest Record (DCR) and attribute disclosure risk assessments. The synthetic dataset was nearly indistinguishable from the original dataset (MMD=0.002, standardized Wasserstein distance <1.0), preserving clinically relevant correlations and survival patterns as evidenced by similar median survival times (110 vs. 101 days) and 5-year survival rates (22.2% vs. 22.8%). MELD-based 90-day mortality prediction was maintained (original AUC=0.839 vs. synthetic AUC=0.844). Privacy metrics indicated no identifiable patient matches, and mean DCR values ensured that synthetic individuals were not direct replicas of real patients. Conclusion: Artificial intelligence–generated synthetic data derived from diffusion models can faithfully replicate complex hepatology datasets, maintain key clinical signals, and ensure strong privacy safeguards. This approach can help address data scarcity, enhance model generalizability, foster multi-institutional collaboration, and accelerate progress in hepatology research.

Key Points The Standard versus Accelerated Initiation of Renal Replacement Therapy in AKI trial found that starting dialysis earlier for AKI resulted in a 74% higher risk of still receiving dialysis at 90 days. Among patients who likely would have started dialysis under usual practice, the risks of dialysis dependence were similar. This suggests much of the risk observed may have been due to starting dialysis (versus never starting) rather than starting slightly earlier. Background The Standard versus Accelerated Initiation of Renal Replacement Therapy in AKI Trial showed that among critically ill patients with AKI, an accelerated KRT initiation strategy resulted in more KRT dependence at 90 days, as compared with a standard strategy. However, it is unclear whether this difference exists among participants who likely would have been treated with KRT in usual practice. Methods Secondary analysis of the Standard versus Accelerated Initiation of Renal Replacement Therapy in AKI randomized controlled trial, analyzing participants who received more than the median number of days of KRT, which served as a proxy for high probability of requiring KRT under usual practice. Two sensitivity analyses redefined the cohort as ( 1 ) those with ≥24 hours of oliguria who received KRT and ( 2 ) those who received any KRT. Using the same statistical approach as the original trial, we calculated unadjusted relative risks with 95% confidence intervals (CIs) for the exposure of randomized KRT initiation strategy (accelerated versus standard) on the outcome of KRT dependence at 90 days among survivors. Results Among the 1184 participants who received ≥6 days of KRT (670 and 514 in the accelerated and standard arms, respectively), baseline characteristics remained balanced between treatment arms. The relative risk of KRT dependence at 90 days was attenuated and nonsignificant: 1.21 (95% CI, 0.84 to 1.78), compared with 1.74 (95% CI, 1.24 to 2.43) in the overall trial. The results were similar in sensitivity analyses. Conclusions Among patients who likely would have been treated with KRT in usual practice, there was no significant difference in 90-day KRT dependence among survivors between those randomized to the accelerated and standard KRT initiation strategies. These results suggest that the harm of long-term KRT dependence may be largely due to KRT initiation (versus never initiation) rather than earlier initiation. Clinical Trial registry name and registration number: NCT02568722.

ABSTRACTAnetumab ravtansine, like other ADC drugs, has high inter‐patient variability in its pharmacokinetic (PK) and pharmacodynamic (PD) outcomes, which raises concerns about whether current dosing regimens are optimal for patients. The objective of this study was to evaluate covariates, especially body habitus and the innate immune system (IIS), which may affect anetumab ravtansine PK and PD as part of two clinical trials in patients with ovarian cancer and mesothelioma. Biomarkers of Fcγ receptors(FcγR) CD64 on IIS cells, total body weight (TBW), body surface area (BSA), and other covariates, such as sex and age, were analyzed for an association with anetumab ravtansine PK. Higher FcγR CD64, TBW, and BSA were associated with higher clearance (CL) of anetumab ravtansine (p < 0.05). However, there was no relationship between TBW or BSA and FcγR CD64. Female patients had a lower anetumab ravtansine CL (0.030 ± 0.007 L/h) compared to male patients (0.042 ± 0.006 L/h) (p < 0.05). In both studies, patients with stable disease (SD) and partial response (PR) had higher anetumab ravtansine AUC0‐inf compared to patients with progressive disease (PD). Individualizing the dose of anetumab ravtansine and potentially other ADCs based only on TBW is not optimal, whereas precision dosing of an ADC based on the inclusion of novel metrics of IIS biomarkers, body habitus, and sex may be more appropriate to reduce variability in PK exposure, reduce toxicity, and improve response.