Citations

Background Recurrent pericarditis may be mediated through inappropriate activation of the NACHT, leucine‐rich repeat, and pyrin domain‐containing protein 3 inflammasome. Pharmaceutically manufactured cannabidiol is an oral formulation that inhibits NACHT, leucine‐rich repeat, and pyrin domain‐containing protein 3 inflammasome activation and development of pericarditis in a preclinical model. Methods This Phase 2, open‐label, multicenter trial included adult patients with symptomatic recurrent pericarditis: pericarditis chest pain ≥4 on an 11‐point numerical rating scale with an elevated C‐reactive protein (≥1 mg/dL) or at least mild pericardial inflammation on cardiac magnetic resonance imaging. At enrollment, patients were on stable doses of non‐steroidal anti‐inflammatory drugs, colchicine, and/or corticosteroids. Cannabidiol was administered during an 8‐week treatment period and an optional 18‐week extension period when background therapy was tapered and discontinued. The primary efficacy end point was change in patient‐reported pericarditis pain. Secondary end points included normalization of C‐reactive protein and percentage of patients with recurrences. Results Among 27 patients (18 women, mean age 53 years), baseline maximal numerical rating scale pain score was 5.8±1.7, and 10 patients had elevated C‐reactive protein. At Week 8, maximal numerical rating scale pain score was 2.1±1.8, and median time to numerical rating scale score ≤2 was 5 days. Among the 10 patients with baseline C‐reactive protein elevation, C‐reactive protein was normal at Week 8 in 8 patients (80%). During the extension period, 17 (71%) of 24 patients remained free of pericarditis recurrence. A serious adverse event leading to cannabidiol discontinuation occurred in 1 patient. Conclusions In symptomatic patients with recurrent pericarditis, pharmaceutically manufactured cannabidiol appears safe and associated with reductions in pericarditis pain and systemic inflammation. Registration URL: clinicaltrials.gov ; Unique Identifier: NCT05494788.

Abstract Body surface gastric mapping (BSGM) enables non-invasive measurement of gastric electrophysiology, but the signals are approximately 100 times weaker than cardiac potentials and overlap spectrally with motion artifacts, necessitating labor-intensive manual review that limits clinical scalability. We present an uncertainty-aware deep learning framework combining a signal reconstruction network with a parallel uncertainty estimation network to automate artifact correction in high-resolution BSGM. Models were trained on 2,398 multihour, 64-channel recordings from 27 international clinical sites using weak supervision, a physiology-aware loss function, and uncertainty-gated quality control. In an independent cohort of 127 patients, the system achieved relative reductions of 39% in signal reconstruction error, 9% in total data removed, and 23% in amplitude–movement correlation compared with the industry-standard Wiener filter. Improved signal fidelity altered automated clinical phenotyping in 7% of patients by recovering previously obscured gastric rhythms. Uncertainty-aware deep learning enables reliable automated artifact correction in body-surface gastric mapping, improving signal fidelity and enabling scalable clinical interpretation. The system is FDA-cleared (510(k) K252504) and deployed in clinical practice, demonstrating that data-driven artifact correction can meet regulatory requirements for medical devices and reduce dependence on specialist manual review.

The Philadelphia chromosome-negative myeloproliferative neoplasms (MPN) are a group of heterogenous hematologic malignancies characterized by the proliferation of blood cells and consist of myelofibrosis, polycythemia vera, and essential thrombocythemia. The NCCN Guidelines for MPN were developed as a result of meetings convened by a multidisciplinary panel with expertise in MPN, with the aim of providing recommendations for the comprehensive care of adults with these diseases. The panel of experts convenes at least once a year to discuss requested changes to the Guidelines and to evaluate emerging data. These Guideline Insights focus on some of the recent updates for myelofibrosis.

Primary enlargement of the cerebrospinal fluid (CSF)–filled brain ventricles, known as congenital cerebral ventriculomegaly (CCV), is a hallmark of congenital hydrocephalus. CCV is also enigmatically but frequently associated with autism and other neurodevelopmental disorders. To gain insight into the developmental genetic regulation of the human CSF-ventricular system, we conducted an integrated, multiomic study of about 2700 trio-based exomes from patients with primary CCV. We found that about 25% of cases were associated with rare, damaging de novo variants in mutation-intolerant genes, many of which are linked to other dominant Mendelian disorders. Thirty-five exome-wide significant CCV genes and dozens of other high-confidence CCV genes converged on pathways involved in ATP-dependent Brahma-related gene 1/Brahma-associated factor chromatin remodeling, histone H3 lysine 4 methylation, and phosphoinositide 3-kinase signaling. Knockout of selected CCV genes in mouse models supported that de novo variants in CCV genes caused ventriculomegaly by impairing both CSF dynamics and cortical cytoarchitecture through dysregulation of neuroprogenitor cell growth and maturation in the ventricular and subventricular zones. These findings indicated that genetic and epigenetic programs coordinate the “hand-in-glove” development of the CSF-ventricular system with that of the cerebral cortex and establish a genetic connection between CCV and neurodevelopmental disorders, potentially explaining why some patients with hydrocephalus continue to exhibit CCV and neurodevelopmental disorders despite CSF shunting. We suggest that combined brain imaging and whole-exome sequencing could enable early detection of, and intervention for, autism and other neurodevelopmental disorders.

Importance High-quality evidence guiding opioid prescribing decisions for acute pain across common diagnoses is lacking. Objective To describe pain trajectories and patterns of opioid and nonopioid treatment use among individuals who were offered opioids for the treatment of acute pain. Design, Setting, and Participants This was a prospective cohort study of patients recruited from 5 US health systems between September 2020 and March 2023 in emergency departments (EDs), primary care clinics, dental practices, or after cesarean delivery or knee replacement. Eligible patients were opioid-naive adults aged 18 years or older at all study sites, as well as adolescents aged 15 to17 years undergoing impacted molar extraction at 1 site, who were offered an opioid prescription for acute pain. Analysis was conducted April 2023 through February 2026. Exposure Offer of a prescription for an opioid analgesic. Main Outcomes and Measures Time to pain resolution (3 consecutive reports of no pain), patterns of opioid and nonopioid treatment use, and opioid-related adverse effects, ascertained from digital questionnaires. Results Among 1708 enrolled patients (median age, 38 years [IQR, 28-52 years]; 615 [36.0%] reporting race or ethnicity underrepresented in studies of acute pain management) followed up for 180 days, 915 (53.6%) were recruited in EDs, 307 (18.0%) in primary or urgent care, 263 (15.4%) in dental settings, and 223 (13.1%) in inpatient settings. Pain sources included dental (302 patients [17.7%]), trauma or injury (302 [17.7%]), obstetric (176 [10.3%]), musculoskeletal (131 [7.7%]), and low back (100 [5.9%]). Among 1502 patients reporting pain level at least once, median time to pain resolution irrespective of the treatment approach was 20 days (IQR, 8-88 days), with longer durations for surgical pain (74 days [IQR, 30 days to not reached]) and low back pain (69 days [IQR, 18 days to not reached]). The median time to opioid discontinuation among 1189 patients (69.6%) who reported any opioid use was 7 days (IQR, 2-31 days); an estimated 10.0% (95% CI, 7.7%-12.7%) of patients used opioids for at least 90 days, with higher rates in people reporting frequent pain before enrollment. Of 1482 patients (86.8%) completing at least 1 survey during the first 2 weeks of follow-up, 1153 (77.8%) reported using any opioids and 1287 (86.8%) reported using acetaminophen or ibuprofen. Among 619 (52.1%) patients with any opioid use who reported the dose of opioids taken in the first 15 days, daily doses were low (median, 10 [IQR, 5-15] morphine milligram equivalents). Most respondents reported leftover opioids (657 of 982 responding [66.9%]). Conclusions and Relevance In this cohort study of opioid-naive patients with acute pain, opioid use was generally low dose and of short duration, although some patients reported prolonged opioid use; most reported achieving pain resolution within 3 weeks, with longer times for surgical and low back pain. The findings suggest current guidelines for multimodal treatment and for short-duration opioid prescriptions if needed will serve many but not all patients, and treatment should be tailored to address individual patients’ needs.

Abstract Background: The dynamic nature of surgical demand poses significant challenges in planning and scheduling resources to staff the surgical suite. Uncertainty in workload often leads to conservative upstream resource allocation, resulting in staffing misallocation. We propose a novel metric, the daily maximum number of open operating rooms (ORs), as an interpretable resource demand proxy to support staff planning. Methods: Using historical surgical data from Mayo Clinic in Rochester, Minnesota, from May 5, 2018 through October 8, 2023 (332,904 surgical cases), we developed a deep learning framework based on a wide-and-deep architecture to predict the daily maximum number of open ORs. The model incorporates features capturing historic OR use trends, seasonality effects, and anesthesia division–specific characteristics. Predictions are generated for forecast horizons of up to 90 business days. Results: Our results demonstrate strong predictive performance, with campus-level root mean square error values ranging from 5 to 7 available ORs across all forecast horizons. Validation across 9 anesthesia divisions confirms the frame- work’s capability to capture complex, nonlinear dependencies within longitudinal surgical datasets. Conclusions: This study introduces a novel operational metric and a robust predictive framework for perioperative resource management. By accurately fore- casting daily maximum open ORs, health care managers can better align staff capacity with anticipated demand, potentially enhancing staff use and improving the patient care experience by minimizing delays.

Abstract Objective This study was undertaken to examine acute and chronic electroencephalographic (EEG) and seizure characteristics in new onset refractory status epilepticus (NORSE). Methods Multicenter inpatient and follow‐up clinical and EEG data were analyzed using International League Against Epilepsy definitions and American Clinical Neurophysiology Society (ACNS) EEG terminology. Results Forty‐four patients were included from the Yale NORSE/FIRES Biorepository (median age = 29 years, 33 female, 38 cryptogenic). Nine hundred twenty inpatient EEG days were reviewed (median = 13.5 days/patient). Presenting status epilepticus (SE) types included 24 convulsive SE (CSE), five focal–motor (FMSE), and 15 nonconvulsive (NCSE). Of 39 patients with post discharge follow‐up (median = 14.7 months), 61.5% ( n = 24) had seizures and required more antiseizure medications than seizure‐free patients (median = 4 vs. 1, p < .001). Inpatient EEG captured epileptiform discharges in all and periodic discharges in 38 patients. Seizures were captured in 38 patients: 33 electrographic (11 only electrographic) and 27 electroclinical. Total seizure burden ranged 6.5–29 615.0 min (median = 50.7). Seizures fulfilling ACNS EEG criteria for SE were captured in 20 patients; two had CSE and the remainder NCSE with coma, nine of whom also had FMSE. Inpatient seizure days (median = 50.0 vs. 15.5%, p = .004) and seizure burden (median = 42.9 vs. 0 min, p = .009) were higher in the first half of monitored days. Interictal findings were equally present and did not predict postdischarge seizures, whereas electroclinical seizures (90.9% vs. 45.5%, p = .037), seizure burden (median = 116.8 vs. 32.5 min, p = .045), and proportion of seizure days (36.3% vs. 20.0%, p = .037) did. Among 12 patients with follow‐up EEGs (median = 19.6 months post onset), posterior‐dominant rhythm (PDR) returned in nine; five had periodic discharges, and three had seizure captured. Significance Seizures are most commonly convulsive upon presentation and nonconvulsive or clinically subtle throughout the inpatient course in NORSE. Inpatient seizures, but not interictal abnormalities, occur earlier in the inpatient course and presence of electroclinical seizures, seizure burden, and proportion of seizure days but not interictal findings are associated with postdischarge seizures. Although return of PDR reflects neurological recovery, seizure persistence and EEG abnormalities post‐NORSE are common.

The adult chronic pancreatitis (CP) working group, formed at the inception of the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer (CPDPC), has developed a robust framework and infrastructure to conduct clinical, translational, and mechanistic studies of CP. At its core is PRO spective Evaluation of C hronic Pancreatitis for E pid E miologic and Translational Stu D ies (PROCEED), the first longitudinal cohort study of CP in US adults, launched in 2017. PROCEED has developed a well-annotated clinical data set of over 2000 deeply-phenotyped participants, a biorepository and an imaging repository. Investigators have published promising data on blood-based and imaging-based biomarkers of CP diagnosis and pain, which are awaiting validation. Clinical observations include classification of patients into mechanism-based pain phenotypes using responses to PROMIS questionnaires, prevalence and predictors of opioid use, prevalence of psychological comorbidity, and osteopathy in CP patients. Pilot clinical trials have evaluated the effect of oral indomethacin on pancreatic fluid prostaglandin E2 levels and Internet-based cognitive behavioral therapy (CBT) for chronic pain. Results of pilot trials have led to an ongoing definitive randomized clinical trial for CBT. The rich environment and resources have facilitated mentorship and academic development of many early-stage investigators. Investigators outside of the consortium have opportunities for collaboration. In the next 5 years, the working group plans to further strengthen the research platform, complete primary and key secondary analyses of PROCEED and ancillary studies, continue efforts to develop biomarkers for diagnosis and prognosis of CP, and complete ongoing clinical trials to address unanswered questions in the field.