Citations

INTRODUCTION: Adverse events (AEs) in health care—such as medical errors and patient harm—are a leading cause of death in the United States and have long-lasting emotional and behavioral effects on patients and families. Effective communication following AEs is critical, yet providers often lack training, institutional guidance, and confidence to navigate these conversations. Communication training programs have shown promise in improving provider empathy, competence, and confidence, but there is limited data on ob-gyn practicing providers, allied health care staff, and administrators. METHODS: A 4-hour multidisciplinary communication training was conducted at a large Midwestern academic hospital system (2022–2024). Training included didactics, simulated patient scenarios, and group debriefings. Participants were ob-gyn clinicians, nurses, and administrative staff. In 2025, 58 participants received follow-up surveys; 33 responded. Quantitative data were analyzed with SPSS, and qualitative responses underwent thematic analysis. RESULTS: Post-training, participants reported high empathy (mean 4.38, SD .38), communication competence (mean 4.45, SD .49), and confidence (mean 4.28, SD .43). No significant differences existed between clinical and nonclinical groups. Qualitative feedback included better empathy, structured conversations, and comfort apologizing. Ninety-seven percent reported changed communication practices, and 91% applied skills in practice. CONCLUSIONS/IMPLICATIONS: Training led to sustained empathy and confidence improvements across roles and specialties. Participants noted high uptake and ongoing use of skills. To our knowledge, there are no other published studies on the effect of communication training in practicing ob-gyn providers, allied staff, and administrators. Future efforts should add unscripted scenarios and behavioral assessments beyond self-report.

PURPOSE Although outcomes for nonmetastatic cancers have improved since the 1970s, it remains uncertain whether long-term survival has improved among patients presenting with de novo metastatic disease, defined as cancer presenting with distant metastases at the time of initial diagnosis. This study evaluated changes in 5-year survival among patients with de novo metastatic cancer diagnosed in 1976 versus 2015, with a minimum 5-year follow-up through 1981 and 2020, respectively. METHODS Population-based data were obtained from the SEER database. Patients diagnosed with de novo metastatic cancer in 1976 (n = 11,864) and 2015 (n = 26,324) were included. Five-year overall survival (OS) was compared between cohorts, and multivariable logistic regression identified demographic and clinical factors associated with survival. RESULTS The 5-year OS increased significantly from 10.6% in 1976-1981 to 23.6% in 2015-2020 ( P < .001). Survival gains were largest in breast cancer (12.6%-34.2%; P < .001), ovarian cancer (14.4%-32.5%; P < .001), colorectal cancer (3.7%-15.0%; P < .001), and hematologic malignancies (24.3%-53.9%; P < .001). Minimal improvement occurred in pancreatic cancer (0.25%-1.6%; P = .007) and small cell lung cancer (0.8%-3.1%; P = .008). Multivariable analysis demonstrated that older age, male sex, and Black race were associated with lower odds of 5-year survival (all P < .01) CONCLUSION Over the past four decades, long-term survival among patients with de novo metastatic cancer has more than doubled; however, progress remains uneven across cancer types. Gains appear concentrated in malignancies with substantial therapeutic advances, whereas others show persistently poor outcomes. Continued efforts are needed to address disparities and improve survival in resistant cancer types.

Abstract Background The IEC exposure index (EI), deviation index (DI), and target exposure index (EI T ), represent critical standardized metrics for the evaluation of exposure and quality in radiographic imaging. Purpose This work develops and validates a systematic procedure to estimate the EI T for eight of the most common radiography imaging protocols utilizing automatic exposure control (AEC) from measurements acquired under reference conditions. Methods A model was developed to define the relationship between a systems AEC logic, and an estimation of the EI under flat‐field conditions (EIFFC). Separately, clinical data and acquisition protocol information for resultant EI during patient studies were also collected for the eight protocols studied: Chest posteroanterior (PA), Chest lateral, Abdomen anteroposterior (AP), Pelvis AP, L‐Spine AP, C‐Spine AP, T‐Spine AP, and Ribs AP. Data were collected from 41 x‐ray units spanning seven institutions. For each protocol on each unit the EIFFC was computed based on the acquisition protocol, as well as median EI from clinical exams to produce a scaling factor (SF). Kruskal–Wallis statistical tests were used to compare SF's between vendors and AEC cell configurations. Results SFs for eight radiographic imaging protocols have been produced per vendor and per AEC cell selection. A workflow has been established for end‐users to follow to apply these SFs to flat‐field measurements taken at their own locations to establish local EI T . Conclusions The study results show that in seven of the eight imaging protocols, the SFs for most units included in the study report SFs within 1 DI (± 25%) of their respective final vendor reported SF (218/228). The ribs protocol is the exception to this finding (n = 26). SFs have high utility for establishing EI T values on individual x‐ray units and normalizing EI value distributions for quality assurance purposes.

ABSTRACT Aims To evaluate the real‐world associations between semaglutide 2.4 mg and cardiometabolic comorbidities, biomarkers and cardiovascular risk among adults with overweight or obesity. Methods This retrospective cohort study used US claims data and laboratory measurements from the Komodo Research Database (2016–2024). Adults with obesity or with overweight and ≥ 1 obesity‐related comorbidity were included. Patients on semaglutide 2.4 mg for ≥ 12 months were compared with non‐users (including users of other obesity medications) using propensity score weighting with residual imbalances adjusted in regression model. Outcomes included time to onset of cardiometabolic comorbidities, change in cardiometabolic biomarkers and changes in 10‐year ASCVD risk score at 12 months. Results 25 783 semaglutide 2.4 mg users and 8 948 913 non‐users were identified. Semaglutide 2.4 mg was associated with significantly lower risks for incident prediabetes or type 2 diabetes, type 2 diabetes only, hypertension, ASCVD, heart failure and CVD (HRs 0.45–0.75; all p < 0.05), as well as greater improvements in BMI (−4.1 kg/m 2 ), SBP (−6.2 mmHg), HbA1c (−0.4%), LDL cholesterol (−7.7 mg/dL), triglycerides (−28.6 mg/dL) and HDL cholesterol (+1.9 mg/dL; all p < 0.001). At 12 months, semaglutide 2.4 mg users ( N = 161) demonstrated a greater reduction in ASCVD risk score (−0.7% vs. +0.3%; between‐group difference −1.0%, p < 0.001), with a decrease in the proportion at intermediate‐high ASCVD risk (14.9%–9.3% vs. 17.7%–18.7%; OR 0.3 [95% CI: 0.1, 0.6], p < 0.001). Conclusions Semaglutide 2.4 mg was associated with lower risk of multiple cardiometabolic comorbidities, favourable changes in biomarkers, and lower estimated ASCVD risk in this population.

ABSTRACT Polyglucosan body myopathy type 2 (PGBM2; OMIM #616199) is an autosomal recessive myopathy caused by biallelic variants in GYG1 , which encodes glycogenin‐1. It is characterized by progressive muscle weakness and PAS‐positive, diastase‐resistant polyglucosan inclusions on muscle biopsy. We report a 64‐year‐old woman who developed progressive proximal weakness beginning in her early 50s, with polyglucosan bodies identified on muscle histopathology. Genome sequencing (GS) detected a single heterozygous pathogenic splice‐site variant, NM_004130.4( GYG1 ):c.143+3G>C. Given strong histopathologic evidence of PGBM2, GS data were reanalyzed, revealing an additional rare deep intronic variant, NM_004130.4( GYG1 ):c.7+992T>G, predicted to activate a cryptic exon. RNA sequencing (RNA‐seq) confirmed aberrant splicing from both variants, demonstrating exon 2 skipping associated with c.143+3G>C and cryptic exon inclusion caused by c.7+992T>G. Variant phasing posed a diagnostic challenge due to unavailable parental DNA, and long‐range PCR results were inconclusive. Long‐read GS definitively demonstrated that the two variants were in trans , establishing compound heterozygosity and confirming the molecular diagnosis. These findings enabled reclassification of the deep intronic variant as likely pathogenic. This case highlights the diagnostic limitations of conventional phasing approaches in adult‐onset recessive disorders and demonstrates the clinical utility of integrating genome reanalysis, RNA‐seq, and long‐read GS for resolving complex phasing challenges.

Cognitive impairment in sepsis survivors is a growing clinical challenge as the number of sepsis cases rise and acute mortality rates fall. It is estimated that up to 70% of sepsis patients experience cognitive dysfunction and many report persistent dysfunction post‐sepsis. Cognitive impairment is a broad term that refers to sepsis‐associated brain dysfunction or encephalopathy (SABD or SAE, respectively). While many contributors, such as inflammation, blood–brain barrier dysfunction, and extended microglial activation are implicated in SABD/SAE development, much is still unknown regarding the underlying mechanistic causes of persistent cognitive defects in sepsis survivors. Here, we employed cecal ligation and puncture (CLP) to model surgical sepsis in mice, after which mice were subjected to multiple memory function assays for up to 2 months post‐sepsis. Furthermore, single‐cell RNA sequencing and validation studies were performed with murine hippocampi to query alterations in the brain microenvironment. Our study shows that CLP mice exhibited decreased spontaneous alternation at 4 weeks and decreases in both short‐ and long‐term recognition (at 6 weeks and 2 weeks, respectively) accompanied by substantially altered cell type makeup of the hippocampus, including hippocampal neuron and pericyte loss. Finally, transcriptional alterations in the macrophage populations implicate aberrant activation in CLP survivors. In conclusion, post‐sepsis mice exhibit reduced memory capacity and altered hippocampal cell composition and transcriptional profiles. This study and associated data set will be valuable for further investigation of the underlying pathophysiology of SABD/SAE and elucidation of potential therapeutic candidates.

Diagnosing rare genetic diseases remains a major challenge despite widespread clinical testing. Long-read RNA sequencing (RNA-seq) offers a powerful approach to capturing the effects of genetic variants on the transcriptome, yet challenges with sequencing coverage, cost, tissue selection, and scalability have limited its clinical adoption. To address this, we developed STRIPE (Sequencing Targeted RNAs Identifies Pathogenic Events), a targeted long-read RNA-seq–based strategy for rare disease diagnosis and variant interpretation. STRIPE enables deep sequencing of full-length transcripts for any customized disease-specific gene panel such that a wide range of clinically informative readouts, including transcript aberrations and sequence variants, can be detected at haplotype-level resolution. Applying STRIPE to 88 individuals spanning two major rare disease groups, we accurately reidentified known pathogenic variants and revealed their transcript consequences, including many unexpected ones. For 8 of 15 splice site region variants, we observed more complex RNA processing defects beyond single exon skipping or cryptic splice site activation. Notably, we find that donor splice site variants frequently activate cryptic intronic polyadenylation sites, leading to premature transcript termination. Leveraging unique strengths of long-read RNA-seq, STRIPE also resolved variants of uncertain significance and uncovered disease-causing variants in five previously undiagnosed individuals. Overall, STRIPE is a powerful, adaptable, and scalable strategy with broad potential to improve clinical variant interpretation and advance genetic diagnosis of rare diseases.