Citations

Importance: Chronic liver disease requires sustained engagement with the health system, which co-occurring social and functional risks may disrupt. Whether these risks form reproducible patterns with different mortality associations is uncertain. Objective: To identify social and functional risk patterns among US adults with chronic liver disease and evaluate their associations with all-cause mortality. Design, Setting, and Participants: Nationally representative cohort study of National Health Interview Survey sample adults interviewed from 2011 through 2018 and linked to the National Death Index through 31 December 2019. Participants were aged 18 years or older, eligible for mortality linkage, reported a chronic liver condition, and had no baseline liver cancer. Exposures: Latent class membership derived from 7 binary indicators: poverty, food insecurity, uninsurance, cost-related delayed care, no usual place of care, single-adult household status, and activity limitation. A complete 0- to 7-item count was a secondary exposure. Main Outcomes and Measures: All-cause mortality. Survey-weighted Cox models estimated hazard ratios (HRs) with sequential demographic, clinical, and liver-specific adjustment. Prespecified sensitivity analyses used 20 multiple imputed data sets, sampling-weighted pseudo-likelihood latent class models, complete-case re-estimation, a fixed 5-year horizon, and class-by-age interaction testing. Results: Among 3407 adults (weighted mean age, 54.0 years; 49.4% female), 529 deaths occurred over 17,297.6 person-years (median follow-up, 5.0 years [IQR, 3.0–7.0]). Four classes were retained: low social and access burden (weighted prevalence, 63.1%); functional limitation with financial strain (13.2%); poverty, single-adult household, and functional limitation (15.0%); and uninsurance with major access barriers (8.7%). Compared with the low-burden class, the functional-limitation/financial-strain class had higher adjusted mortality (HR, 1.95; 95% CI, 1.34–2.82; p < 0.001); the other 2 classes did not differ significantly. Sampling-weighted latent class analysis after multiple imputation reproduced 97.2% of modal assignments, and the association persisted with attenuation (HR, 1.55; 95% CI, 1.08–2.22; p = 0.02). Each additional risk was associated with higher mortality (exact count: HR, 1.24 [95% CI, 1.13–1.36]; imputed count: HR, 1.19 [95% CI, 1.10–1.29]). The class-by-age interaction was not significant (p = 0.41). Conclusions and Relevance: Among US adults with self-reported chronic liver disease, social and functional adversity was both cumulative and patterned. A profile combining functional limitation, food insecurity, and cost-related delayed care had the clearest independent mortality association despite largely retained insurance coverage. These profiles are not a validated clinical score, but the findings argue against reliance on any single indicator, particularly insurance status, as a marker of vulnerability.

Abstract Although sequencing costs have steadily decreased with advances in technology, they remain high for large scale studies. The design of traditional individual-disease sequencing studies is either case only or cases with relatively few controls, resulting in potential loss of statistical power for discovery of disease associated genes. Here we show that for a given number of sequenced cases, a large control sample size is critical to maximize power for rare variant burden analysis. Furthermore, we have developed an end-to-end workflow based tool (CoCoRV-nf) to facilitate the use of external biobank sequence resources as controls. The modules include consistent variant QC, variant annotation, ancestry population prediction, and gene based burden analysis using summary genotype information, and combined analysis from multiple independent results. The tool supports exomes and genomes from gnomAD and All of Us as controls with preprocessed datasets. We apply the tool in two rare neurological diseases: amyotrophic lateral sclerosis and neuroblastoma. For each disease, two case cohorts are paired with gnomAD and All of Us data, respectively, followed by a combined analysis. Not only did we recapture known genes, but also, we identified new candidate genes for both diseases. By leveraging multiple large external biobank sequence data, we demonstrate the feasibility of using our tool to maximize statistical power to identify new disease predisposition genes.

Abstract Background While biologic and small molecule therapies have expanded treatment options for moderate to severe ulcerative colitis (UC), prior research revealed that only 26% of patients in routine practice would have qualified for pivotal randomized controlled trials (RCTs) due to stringent eligibility criteria. This study aimed to evaluate contemporary clinical trial eligibility for UC patients in a tertiary care setting based on more recently approved therapies. Methods We performed a retrospective cohort study of adult patients with moderate to severe UC (total Mayo score ≥6) seen between January 2022 and February 2023. Inclusion and exclusion criteria from seven phase III RCTs conducted between 2012 and 2022 (eg, VARSITY, UNIFI, OCTAVE, LUCENT) were applied to determine patient eligibility and identify reasons for ineligibility. Results Of 150 patients (mean age 44.9 years; 55.7% male), only 42.7% were eligible for at least one RCT. The most common exclusion factor was current or prior medication use, followed by anemia, dysplasia, and disease extent. Trial eligibility did not significantly differ by age, gender, or disease duration. Conclusions Despite modest improvements since 2012, over half of real-world UC patients remain ineligible for current RCTs. Expanding inclusion criteria, especially regarding prior medication exposure, and adopting more inclusive trial designs may enhance external validity. Addressing disparities in trial access and participation remains essential to ensuring equitable representation and improving clinical applicability of RCT findings.

Transfers are high-risk events, and outside hospital admissions lack standardized processes to ensure timely delivery of essential clinical information. We piloted a novel, standardized process for outside admissions to a single academic medical center’s resident- and hospital medicine-attending-based medicine services. Following literature review, Epic UserWeb review, and frontline physician input, a workflow and templated electronic health record accept note were developed to centralize outside admission documentation. Completed by physicians during real-time communication with outside physicians, the template captures key clinical data and incorporates a communication checklist. Physician education was delivered electronically and in person. Subjective attending and resident perceptions were assessed via electronic prepost surveys administered 1 week before and 90 days after implementation. Secondarily, exploratory patient clinical outcomes were assessed through 90-day prepost manual retrospective chart review. Survey responses were obtained from 60/38 residents and 12/7 attendings (pre/post). Documentation sufficiency on patient arrival was directionally promising among residents (21.7% vs 39.5%, P = 0.062). Satisfaction with the admission process and perceived patient safety improved significantly among residents and attendings ( P ≤ 0.036). Most respondents rated the note as useful or very useful (84% residents; 86% attendings), and attendings reported reduced time managing outside admissions. The intervention was associated with exploratory, nonsignificant reductions in rapid response team activation, intensive care unit transfer, 30-day readmission, mortality, and length of stay compared with preintervention patients. A standardized documentation and communication process improved physician satisfaction and perceived patient safety, with promising exploratory patient outcomes. Further study is warranted to assess impact at scale.

Marketing authorizations for oncology drugs are often based on single‐arm trials (SATs), and real‐world data‐based external comparator cohorts (ECCs) are increasingly explored to contextualize results. In retrospective studies, comparators may be identified by time of diagnosis but included based on time of relapse; such sampling strategies can introduce bias, potentially leading to erroneous efficacy conclusions. Simulated diffuse large B‐cell lymphoma (DLBCL) cohorts were generated using published time‐to‐relapse and post‐relapse survival distributions. Three ECC sampling strategies were evaluated: naïve (screening and inclusion periods coincide), delayed (inclusion period extends beyond screening), and displacement (screening and inclusion periods shifted relative to each other). Different sampling strategies caused significant changes in the time‐to‐relapse distribution in the ECC and, by proxy, the estimated 2‐year post‐relapse overall survival (22.5–52.2%). Naïve sampling consistently resulted in oversampling of early relapses, though bias was reduced with extended inclusion periods; in hypothetical trials, it produced inflated Type I errors (10.5–84.9%) despite α = 0.025. Delayed sampling reduced bias when the inclusion period was sufficiently extended to capture late relapses, yielding unbiased estimates under long delays (Type I error of 2.5% at a 6‐year delay). Displacement sampling depended strongly on the degree of shift: moderate shifts minimized bias, whereas long displacements introduced substantial distortion (Type I error of 2.7% and 0.0% at displacements of 2 and 5, respectively). Real‐world data‐based ECCs in relapsed/refractory oncology are susceptible to selection bias from sampling strategies, particularly through distortions in time‐to‐relapse, leading to erroneous efficacy conclusions; similar bias may occur in non‐oncology settings where time‐to‐treatment initiation is prognostic.

Abstract Background The potential risks and benefits of moderate‐intensity exercise in the management of fetal growth restriction (FGR) are controversial. Objective We sought to evaluate fetal responses to a 30‐min bout of moderate‐intensity exercise in pregnancies complicated by FGR. Study design This prospective study included 28 participants at a single academic institution. Pregnant individuals between 28w0d and 36w6d gestation with a diagnosis of FGR with normal Dopplers were enrolled. FGR was defined as total estimated fetal weight less than 10th percentile for estimated gestational age or abdominal circumference less than 10th percentile. Participants were excluded for body mass index (BMI) > 40, tobacco or substance use, hypertension on medications, or other contraindications to exercise. Participants exercised on a treadmill at a moderate intensity monitored using rate of perceived exertion (Borg scale) for 30 min. Fetal umbilical artery (UA), middle cerebral artery (MCA), aortic Dopplers, and maternal uterine artery Dopplers were sampled immediately before and after exercise. Biophysical profile and non‐stress tests were also performed. Maternal vital signs and rate of perceived exertion were monitored throughout exercise. Cerebro‐placental ratios (CPRs) were calculated after sampling. We hypothesized that there is no significant difference in fetal well‐being or Doppler flow in fetuses with FGR immediately after a 30‐min bout of moderate‐intensity maternal exercise compared to pre‐exercise. Results Biophysical profiles and non‐stress tests were reassuring before and after exercise. The primary outcome of UA Doppler values did not differ from pre‐ to post‐exercise. There was no difference in MCA, aortic Dopplers, or CPR. There was an increase in fetal heart rate ( p < 0.05) post‐exercise, which returned to baseline within several minutes. There was a decrease in uterine artery Dopplers ( p < 0.05) post‐exercise, which was driven by a non‐significant decrease in systolic flow and an increase in diastolic flow. Conclusions In this cohort, there were no acute adverse changes in fetal status after a single bout of moderate‐intensity maternal exercise with fetuses with FGR. These findings add to the limited available data in pregnancies complicated by FGR with normal Dopplers. Additional studies are needed to investigate the fetal and maternal effects of vigorous‐intensity and chronic exercise in this population or in populations with more evidence of placental dysfunction. Clinical trial registration NCT06039319.

Introduction Functional hypothalamic amenorrhea (FHA) accounts for 30% of secondary amenorrhea and is characterized by hypothalamic hypercortisolemia, hypothalamic hypothyroidism, and anovulation with hypoestrogenemia due to disrupted GnRH drive. While FHA is associated with decreased bone mineralization; it remains unclear how bone health compares to menopausal women, who also experience bone loss. This study compared dual-energy x-ray absorptiometry (DXA) bone health parameters among women with FHA, eumenorrheic controls, and recently menopausal women. It also examined the impact of prior combined oral contraceptive (COC) use on bone mineral density (BMD) in women with FHA. Methods This cross-sectional study included 20 women with FHA, 9 eumenorrheic controls, and 12 recently menopausal women who underwent hip and spine DXA. None of the participants were taking hormone therapy. FHA was defined as ≥3 months of amenorrhea, estradiol &lt;50 pg/ml, FSH and LH &lt;10 mIU/L, excluding other etiologies. DXA bone parameters were measured using Lunar iDXA (GE) including BMD from lumbar spine (L1-L4) and hip. Results By design, age differed significantly across groups (p &lt; 0.0001), with median ages of 27.8 years [23.4, 34.1] in women with FHA, 29.6 years [28.3, 32.4] in eumenorrheic controls, and 55.3 years [53.5, 56.6] in recently menopausal women. There were no significant differences in weight or BMI across groups. Significant differences were observed at all measured skeletal sites, including all lumbar spine levels, femur neck, total femur, and total BMD (all p &lt; 0.05). Pairwise comparisons revealed that lumbar spine BMD was significantly lower in FHA compared to eumenorrheic controls (p = 0.04), while FHA and menopausal women did not significantly differ from each other (p = 0.07). Among FHA women with prior COC use, L1–4 BMD was not significantly different from controls (p = 0.19). Conclusions Lumbar spine BMD in young women with FHA was comparable to that of recently menopausal women, highlighting the profound skeletal impact of chronic estrogen deficiency. Prior COC use may partially attenuate FHA-associated bone loss, though larger studies are needed to confirm this observation. Future studies should explore whether skeletal outcomes vary by FHA etiology and the potential role of COC duration in preserving BMD.

ABSTRACT Background Gastric emptying scintigraphy (GES) is considered the standard for differentiating gastroparesis from functional dyspepsia and other foregut disorders characterized by nausea and vomiting but provides only a brief physiologic snapshot that may not accurately reflect daily function. We utilized a non‐invasive wireless patch system (WPS) to characterize multiday gastric myoelectrical activity, evaluate its relationship with GES, and assess changes following a therapeutic intervention. Methods Adults referred for GES for symptoms thought to represent gastroparesis were enrolled in a prospective study. Patients wore a WPS for up to 6 days, starting on the day of scintigraphy. Gastric myoelectrical activity was analyzed and categorized into relatively weak, relatively moderate, and relatively strong activity phenotypes. A subset of patients underwent repeat monitoring following individualized therapeutic interventions (e.g., anti‐emetics, proton pump inhibitors, lifestyle changes). Results Forty‐eight patients (mean age 44; 79% female) completed the study. GES identified delayed gastric emptying in 18%, rapid in 22%, and normal in 60% of subjects. During the 4‐h concurrent GES window, gastric activity in patients with delayed emptying was lower, but this difference did not reach statistical significance ( p = 0.08). When compared to the full multiday recording period, GES results showed no correlation with the myoelectric readings. Significant day‐to‐day variability was observed, both random and systemic. In the latter category, a “Test‐Day” dip was observed with gastric activity lowest on Day 1 (GES test day) and increasing significantly on subsequent days, stabilizing by Day 4 ( p < 0.001). Healthy control subjects recorded during normal daily routines showed no such day‐to‐day variation. In the retesting cohort, anti‐emetics produced robust increases in gastric amplitude, whereas PPIs showed minimal impact. Conclusions The WPS effectively captures distinct gastric phenotypes and quantifies physiologic responses to therapy in both gastric and intestinal regions, demonstrating its clinical utility as a robust tool for evaluating and managing foregut symptoms in real‐world settings. Importantly, the multiday WPS highlights significant day‐to‐day physiologic variability in gastric activity that extends beyond the single‐day GES ‘snapshot’.

Background: Inefficiencies in the revenue cycle, such as elevated claim denial rates, extended duration of accounts receivable (A/R), and excessive administrative rework are significant financial challenges for acute-care hospitals. Existing HL7 v2 billing workflows are very manual and error-prone which leads to operational inefficiencies. The solution lies at the intersection of artificial intelligence (AI) and HL7 Fast Healthcare Interoperability Resources (FHIR), enabling automated claim validation and denial prediction. Methods: Retrospective comparative observational study in acute-care hospitals using Epic Professional Billing systems. Revenue cycle performance metrics were obtained for a 12-month pre-intervention period (manual HL7 v2 workflow) followed by a 12-month post-intervention period after AI-enabled FHIR deployment. The primary outcomes were first-pass claim denial rate, accounts receivable length of time to pay, and claim rework. Statistical analysis was conducted by using the chi-square and independent t-tests, where p < 0.05 was considered significant. Results: We analysed 48,392 claims. AI-driven international financial reporting standards (IFRS) validation resulted in significantly improved patient first-pass denial rates which fell 14.4% to 7.4% (p < 0.001), account-receivable trailing days reduced from 41.7 to 28.4 days (p < 0.001) and decrease of claim reworking rate from 18.1% to 8.5% (p < 0.001). They also reduced processing time, and the manual review burden. Conclusion: FHIR, coupled with AI capabilities, streamlines the documentation and authorization processes within the revenue cycle while minimizing denials-based losses through a fully integrated infrastructure creating tangible operational and financial advantages compared to traditional manual pathways. Keywords: Artificial intelligence; HL7 FHIR; revenue cycle management; claim denial reduction; interoperability; healthcare finance; predictive analytics; Epic Professional Billing