Abstract Cardiovascular disease (CVD) is a leading cause of mortality among pregnant women in the United States (US). This study assessed cardiovascular health (CVH) using the Life’s Essential 8 (LE8) score, which includes sleep, in a nationally representative sample of pregnant women aged 20–44 years without CVD using the 2011–2020 NHANES data. The cohort included an estimated 1.6 million pregnant and 34.5 million non-pregnant women. Pregnant women had lower mean LE8 scores [69.3(1.2) vs. 72.3(0.4)], physical activity [42.7(3.9) vs. 56.2(1.3)], blood lipids [61.8(3.4) vs. 79.4(0.6)], BMI [54.4(3.2) vs. 60.5(1.0)], and diet [43.7(2.5) vs. 43.8(0.7)] than non-pregnant women. They were 51% less likely to have ideal CVH [ORadj: 0.49 (95%CI: 0.31–0.77)]. The mean LE8 score in pregnant women was 71.0 (2.2) in 2011–2012 and 66.4 (1.5) in 2017–2020.

BACKGROUND:NPs (natriuretic peptides) are bioactive hormones crucial for regulating blood pressure, glucose homeostasis, and lipid metabolism. Despite the high heritability of circulating NP levels, the genetic determinants of NP regulation, particularly across ancestries and sexes, remain poorly understood. The objective of the current study was to identify genetic variants associated with NT-proBNP (N-terminal pro-B-type NP) levels in a multiancestry study population. METHODS:Whole genome sequencing and array-based data from 81 213 individuals without heart failure were analyzed from the Trans-Omics for Precision Medicine cohorts, UK Biobank, All of Us Research Program, and REGARDS (Reasons for Geographic and Racial Differences in Stroke) study to identify common, rare, and structural variants associated with NT-proBNP levels. The main outcome of the study was rank-based inverse normal and standardized NT-proBNP levels. Genetic associations with NT-proBNP were examined, followed by gene prioritization, transcriptome-wide association studies, colocalization, and rare variant analyses. RESULTS:Nine novel loci and 3 previously reported loci were identified to be associated with NT-proBNP levels. Novel structural variants were detected across 12 loci. Similar effect sizes were observed for both common and rare variants. Key genes such as BAG3 (10q26.11) and SLC39A8 (4q24) were identified through gene prioritization, with prior animal models supporting their therapeutic relevance. Rare variant analysis identified 6 masks with significant associations, specifically non-coding masks, suggesting regulatory modulation of NT-proBNP. CONCLUSIONS:This study identifies novel common, rare, and structural variants associated with NT-proBNP levels, highlighting the contribution of both coding and regulatory non-coding variation. These findings advance our understanding of the genetic architecture of NT-proBNP and may inform future cardiometabolic therapeutic strategies.

INTRODUCTION:Standardized nursing-sensitive indicators (NSIs) are essential for evaluating nursing quality and safety. Within the Military Health System NSI measurement is challenged by electronic health record (EHR) limitations, inconsistent documentation patterns, and inefficiencies in administrative staffing data. Participation in a national nursing database (NND), such as the National Database of Nursing Quality Indicators (NDNQI), offers standardized definitions, benchmarking, and reporting tools to guide nursing quality improvement. This paper reports a cost-benefit analysis to guide recommendations for future participation in an NND across the Defense Health Agency (DHA). MATERIALS AND METHODS:A 12-month study was implemented at 2 military treatment facilities, evaluating 28 NSIs across 14 inpatient units. Data collection included automated EHR extraction, manual methods, or hybrid collection processes. Nursing leaders completed surveys at mid and end-of-study to assess data system compatibility and NDNQI report usefulness. Quantitative and qualitative costs to the enterprise were compared to benefits. RESULTS:Participation required over 450 hours logged in data collection and management. Barriers included limited automated extraction and consistent documentation. Actual benefits include demonstrating centralized extraction, and feasibility of submission. Potential benefits identified in the literature showed reductions in costly hospital-acquired conditions, improved benchmarking capability, and enhanced workforce retention. Overall, research has established that the act of monitoring performance and reporting tends to lead to improved outcomes over time. CONCLUSIONS:Although initial participation was resource-intensive, literature suggests that sustained participation can yield cost savings and improvements in quality once automation and documentation standardization are achieved.

BACKGROUND:The increased costs associated with the management of mild to moderate hyperglycemia in the hospital are unnecessary and can be decreased with treatment in an outpatient setting by a standardized treatment protocol. LOCAL PROBLEM:A nurse practitioner-led clinic provides care to patients with uncontrolled diabetes who are uninsured and often present in hyperglycemic states that could be managed outpatient to prevent hospital utilization. This quality improvement project focused on the initial implementation of an evidence-based protocol to help standardize management of mild-to-moderate hyperglycemic crisis. METHODS:An evidence-based protocol for treating critically high blood glucose (BG) values (≥350 mg/dl) for in-person visits was developed using incremental doses of rapid-acting insulin, monitoring of basic metabolic profile, and oral hydration. INTERVENTIONS:The protocol was presented to nurse practitioners and essential staff. Implementation of the protocol was evaluated with attention to provider adherence and patients' resulting BG values. RESULTS:A total of 39 patient cases were managed with the protocol: 12 were assessed to be adherent to the protocol and 27 were not. Overall, the BG levels in both groups decreased to safer levels after implementation of the protocol. Provider adherence to the protocol made a clinically relevant difference in BG levels, and patients' hyperglycemia was controlled more safely in the adherent group compared with the nonadherent group. CONCLUSIONS:This protocol can help safely control high BG levels in an outpatient setting and prevent hospital visits to control hyperglycemic crises. Ensuring provider adherence to the protocol is essential for achieving these outcomes.

Nonspecific chronic low back pain (NSCLBP) is associated with central sensitization, and both diet quality and epigenetic aging are proposed modifiable, mechanistic contributors to this process. We examined how dietary profiles and epigenetic aging affect central sensitization in NSCLBP. Participants completed dietary, epigenetic aging (DunedinPACE, GrimAge), and central sensitization indicators, including conditioned pain modulation (CPM), heat and mechanical temporal summation (TS), and pain sensitivity questionnaire (PSQ). Dietary profiles were derived from latent profile analysis of dietary inflammatory index components. Nested regression models examined how dietary profiles and epigenetic aging predict central sensitization, adjusting for age, sex, BMI, and race, followed by Benjamini-Hochberg’s false discovery rate correction. We included 200 adults with NSCLBP: mean age 44 years; 62% African American; 55% female; mean BMI 31.33 kg/m². Five tests remained significant after Benjamini-Hochberg correction. DunedinPACE acceleration increased PSQ (β = 2.936, raw p = .034, FDR p = .034), GrimAge acceleration decreased mechanical TS (β = -0.270, raw p = .008, FDR p = .016). Increased low pro-inflammatory diet increased CPM only after accounting for DunedinPACE (β = 49.788, SE = 15.433, raw p = .002, FDR p = .013) and GrimAge (β = 52.685, SE = 15.281, raw p = .001, FDR p = .013). Increased low pro-inflammatory diet decreased heat TS facilitation in the GrimAge-adjusted model (β = -22.028, SE = 8.270, raw p = .009, FDR p = .049). Diet and epigenetic aging jointly, rather than independently, shape central pain processing in NSCLBP, suggesting protective effects of healthier diets.

PURPOSE:The purpose of this study was to examine the association between adiposity and depressive symptoms in ethnically and racially diverse early adolescents, age 11-14 years old. DESIGN AND METHODS:The design was a cross-sectional observational study, with 78 participants from two middle schools in the southeast. Height, weight, and waist circumference were measured, and body fat percentage (BF%) was obtained using a bioelectrical impedance analysis (BIA) scale. Body mass index (BMI) and waist-to-height ratio (WHtR) were calculated. Participants completed the Children's Depression Inventory II (CDI-2) measure. Estimates of effect size based on general multiple linear regression was used to assess the association between adiposity and depressive symptoms, controlling for gender, puberty, and physical activity. RESULTS:Increased adiposity was associated with decreased depressive symptoms in the context of racially and ethnically diverse early adolescents, with a large effect size (ω2 = 0.14, 95% CI = 0.03, 1.00) between depressive symptoms and BMI category, and small effect sizes for the associations for WHtR (ω2 = 0.02, 95% CI = 0.00, 1.00) and BF% (ω2 = 0.01, 95% CI = 0.00, 1.00) with depressive symptoms. CONCLUSIONS:Our findings indicate an inverse association between adiposity and depressive symptoms among early adolescents, which contrasts with many prior studies and underscores the complexity of the relationship between adiposity and mental health during this developmental period. Given the pilot nature of the study and the small sample size, these findings should be interpreted cautiously and warrant confirmation in fully powered studies that include diverse populations across racial and ethnic groups. IMPLICATIONS TO PRACTICE:Greater attention should be paid to overweight and obesity status, and improved screening for depression should be implemented.

Introduction:Early identification of patients with initially mild hypertriglyceridemia-induced acute pancreatitis (HTG-AP) who are at risk of an unstable disease course remains challenging using conventional assessment alone. This study aimed to develop an interpretable machine learning model based on baseline clinical and non-contrast computed tomography (CT) features for early prediction of in-hospital progression. Methods:We retrospectively enrolled 164 patients with initially mild HTG-AP between October 2020 and October 2024. Baseline clinical variables, CT-based body composition parameters, and pancreatic radiomics features from non-contrast CT were collected at admission. Patients were classified into progression (n = 88) and non-progression (n = 76) groups based on clinically relevant worsening supported by clinical or CT evidence during hospitalization. Five-fold cross-validation was used for model development and internal validation. Four XGBoost-based models were constructed: clinical only, clinical + body composition, clinical + radiomics, and clinical + body composition + radiomics. Model performance was assessed using receiver operating characteristic analysis, calibration analysis, decision curve analysis, and Shapley additive explanations (SHAP). Results:The clinical + body composition + radiomics model achieved the best overall performance among the four models, with an AUC of 0.830 and an accuracy of 0.768. Calibration analysis showed relatively good agreement between predicted and observed risks, and decision curve analysis demonstrated a higher net benefit across most clinically relevant threshold probabilities. SHAP analysis identified triglycerides (TG) and the visceral fat area-to-abdominal cavity area ratio (VFA/ACA) as the dominant contributors to model prediction. Conclusion:The proposed interpretable multimodal model may improve early risk stratification for in-hospital progression in initially mild HTG-AP and help identify patients who require closer monitoring, although further external validation is needed to confirm its generalizability and clinical applicability.

Hypertrophic cardiomyopathy (HCM) has traditionally been considered a Mendelian disease driven by pathogenic or likely pathogenic variants in sarcomere-encoding genes (SARC-HCM-P/LP). However, these variants explain only one-third of cases, and variable penetrance suggests additional polygenic contributions. Existing HCM polygenic risk scores (PRSs), largely derived from European-ancestry cohorts, have limited generalizability. Here we develop a multiancestry PRS using summary statistics from the BioBank Japan, Million Veteran Program and a meta-analysis of seven European-ancestry cohorts and evaluate its association with HCM in a USA-based multiancestry population. Individuals with the highest PRS quintile had a 2.11-fold increased risk of HCM in the overall population and nearly 70-fold higher risk among SARC-HCM-P/LP carriers. The PRS improved risk stratification and showed trends toward improved ancestry-specific prediction. Among individuals with HCM, a higher PRS was also associated with adverse cardiovascular outcomes. These findings support the integration of multiancestry PRSs into HCM risk assessment and prognostication.

BackgroundSpinal manipulation (SM) may modulate immune and inflammatory responses in healthy and/or musculoskeletal pain populations, yet SM responses in neurodegenerative populations such as multiple sclerosis are essentially unknown. This pilot study estimated the potential effects of chiropractic thoracic SM combined with trigger point therapy on serum inflammatory cytokine/chemokine levels, neurodegeneration biomarkers, and clinical/performance-based outcomes in people with relapsing-remitting multiple sclerosis (RRMS). The goal was to inform the design of future research.MethodsThis pilot randomized, sham-controlled trial included 21 RRMS participants assigned to either SM (n = 11) or sham-SM (n = 10) groups. Interventions were delivered twice weekly for four weeks. Blood samples were collected at five timepoints: baseline (T0), 20 min and 2 h after first intervention (T1 and T2 respectively), and 20 min and 2 h after the final intervention (T3 and T4 respectively). Overall 21 inflammatory biomarkers, 3 neurodegenerative biomarkers and 12 clinical/performance outcomes were assessed. Between-group differences were evaluated by comparing change scores from baseline per group, and effect sizes were reported using Cohen's d.ResultsEight cytokines/chemokines in the SM group demonstrated moderate to large effect sizes (d ≥ 0.5) at a single timepoint post-intervention compared with the sham-SM group, whereas six (IL-8, IL-17A, GM-CSF, MIP-1β, IFNγ, Fractalkine) demonstrated moderate to large effect sizes at multiple timepoints post-intervention. Among neurodegeneration biomarkers, t-tau levels decreased in the SM group with a small effect size (d = −0.42). Most clinical- and performance-based outcomes had small effect sizes with the few moderate effect size changes being below clinical relevance thresholds.ConclusionThis study identified six cytokines/chemokines that had moderate to large effect sizes at multiple post-intervention timepoints favoring SM. Of these biomarkers, all are considered to be primarily pro-inflammatory. Such results support appropriately powered randomized controlled trials of SM in RRMS population that focus on evaluating these cytokines/chemokines across multiple timepoints including immediately (< 5 min), intermediately (< 30 min), and short-duration (≥2 h) post-intervention and seek to determine the contribution of soft tissue stimulation (i.e., trigger point therapy) preceding the SM to cytokine/chemokine response.Clinical Trial Registrationhttps://clinicaltrials.gov/ NCT04972929, registration date: April 27, 2021.

Background: Trauma resuscitation is time sensitive and complex. Whole blood (WB) and blood components are standard treatments for trauma related hemorrhage, yet their nursing workload and transfusion time have not been well evaluated. Purpose: To assess feasibility of a simulation-based crossover trial and obtain preliminary estimates comparing nursing workload and transfusion completion time between WB and blood component administration. Methods: A randomized crossover pilot study using in situ simulation was conducted with experienced trauma nurses. Time-motion analysis measured transfusion completion time, and the National Aeronautical and Space Administration Task Load Index assessed workload domains. Results: Strong feasibility was demonstrated across recruitment, retention, adherence, and completion. WB was associated with significantly shorter transfusion time, lower overall workload and mental demand, less effort, and better perceived performance. Conclusions: These findings support the feasibility and justify a fully powered trial. WB may improve resuscitation efficiency and reduce cognitive burden, with potential implications for patient outcomes and nursing workflow.

PURPOSE:The COVID-19 pandemic placed an unprecedented strain on the healthcare system, including military hospitals. Military hospitals leveraged a rigorous response plan, creating additional demands on military healthcare staff. The purpose of this project was to determine the levels of burnout, job satisfaction, intent to leave, potentially preventable loss, and healthcare quality, and identify lessons learned from the COVID-19 pandemic to support future organizational preparedness. METHODS:A cross-sectional survey was administered from October 2021 to April 2022 ( n = 1814) to military healthcare staff in various roles at four military hospitals. Analyses were conducted using descriptive statistics, t-tests, and generalized linear mixed modeling. RESULTS:Burnout was moderate to high across all healthcare staff, with the highest score among nurse practitioners (39.5) and the lowest among case managers and care coordinators (21.8). Higher care quality was significantly associated with potentially preventable loss ( p < .0001), lower burnout ( p < .0001), higher job satisfaction ( p < .0001), reduced intent to leave ( p < .0001), and improved pandemic preparedness ( p < .0001). CONCLUSIONS:Focus on traditional workforce improvement and leadership skills, as well as preparedness, is likely to strengthen the Military Health System's capacity to deliver high-quality care before, during, and after a global healthcare crisis.

Background Nocturnal non-dipping blood pressure (BP) pattern, defined as a <10% reduction in nighttime vs. daytime BP, is common among treated hypertensive individuals and is independently associated with increased cardiovascular risk. Obesity is associated with a high prevalence of non-dipping nocturnal BP and lower circulating natriuretic peptide (NP) levels. Given the role of NPs in circadian BP regulation, obesity-related disruption of NP-BP rhythmicity may contribute to impaired nocturnal BP dipping. Chronotherapy using timed administration of NP-augmenting sacubitril/valsartan (LCZ696) may restore these biological rhythms and improve the nocturnal BP dipping profile. Methods PRECISION-BP is an ongoing, double-blind, randomized, 2 × 2 factorial clinical trial, enrolling 160 obese hypertensive adults with non-dipping nocturnal BP, and without established cardiovascular disease. Participants are randomized in a 1:1:1:1 manner to one of these groups: A) morning dose strategy + LCZ696 49/51 mg (N=40), B) morning dose strategy + valsartan 80 mg (N=40), C) evening dose strategy + LCZ696 49/51mg (N=40), D) evening dose strategy + valsartan 80 mg (N=40) for 28 days. Participants undergo two 24-hour inpatient visits with serial blood sampling and continuous ambulatory BP monitoring, before and after 28 days of treatment. Planned analysis The primary endpoint is the change in the mean nocturnal systolic BP from baseline. Secondary exploratory endpoints include changes in nocturnal dipping, ambulatory BP parameters, and circulating and urinary biomarkers of NP biology and cardiovascular physiology. Conclusion PRECISION-BP will evaluate whether chronotherapy with sacubitril/valsartan improves nocturnal BP patterns and provide mechanistic insights into NP-mediated regulation of BP rhythmicity in obesity-associated non-dipping hypertension. Trial Status The trial started recruitment in February 2022. It has enrolled 159 participants as of 11th August, 2026 and is ongoing. Clinical trial registration (Clinicaltrials.gov) NCT04971720

Background: We (and others) have previously identified five clinically distinct diabetes subtypes. Currently, few models to identify diabetes subtypes are readily accessible. Further, while COVID-19 has been associated with increased risk of new-onset diabetes, it remains unknown whether the pandemic is also associated with changes in diabetes subtype distribution. Methods: We used the electronic health records of patients diagnosed with diabetes from 2010 to 2019 at the Kirklin Clinic of the University of Alabama at Birmingham (UAB) to train models to assign diabetes subtypes previously identified by hierarchical clustering. We then applied the trained model to conduct a retrospective cluster analysis of electronic health records of patients diagnosed with diabetes from 2020 to 2024 at UAB. We further validated our findings using data from the 2015-2023 National Health and Nutrition Examination Surveys (NHANES). Results: The trained classification model had an average specificity of 98% and an average sensitivity of 93%. Using the model, we identified a significant difference in the distribution of type 2 diabetes subtypes in patients at UAB and in participants in NHANES. In particular, the proportion of patients with severe insulin-dependent diabetes or severe insulin-resistant diabetes subtypes increased from 42% to 61% and 31% to 40% at the UAB and in NHANES, respectively. Conclusions: The model presented here can facilitate the identification of diabetes subtypes. The proportions of patients with severe subtypes of diabetes have seemed to increase in the more recent years following the pandemic. Further studies are required to determine the potential causes of this phenomenon.

Universal access to palliative care (PC) is a human right that most countries have not accomplished. Effective PC delivery requires an interprofessional team approach. Healthcare professional education is critical to bolstering PC service integration, especially in low- and middle-income countries (LMICs) where PC is least available. Jamaica is a LMIC with inadequate PC. This study aimed to explore the PC experiences and educational needs of healthcare interprofessionals in Jamaica to inform future PC advancement efforts. A qualitative multiple case study design was used with physicians, nurses, and social workers (n = 13) as selected distinct cases using maximum variation sampling. Semi-structured interviews were conducted. Verbatim transcripts were analyzed using an inductive thematic analysis within and across cases. Reflection notes, clarifying communications, and PC educational materials corroborated findings. Five key themes emerged including clinical experiences, cultural environment, communication, self-care, and education. Across cases, physicians were most familiar with PC and social workers least. Nurses did not recognize the full scope of PC. Perceptions of peer communication differed across disciplines. Social workers found interprofessional team involvement beneficial to communication and patient care. All disciplines struggled to maintain a reasonable work-life balance, which was attributed to resource limitations. Between cases, none of the participants had formal PC education. All expressed interest in future training and embraced interprofessional learning. Study findings can inform tailored interprofessional PC educational interventions focused on team collaboration, communication, and integration of PC into communities using resource-stratified approaches and capitalizing on all health professionals as equally important contributors. Advancement of PC should be supported by synergistic international academic-practice partnerships.

Background This study assessed cardiovascular health in women using the American Heart Association's Life's Essential 8 (LE8) score, and compared cardiovascular health across premenopausal, perimenopausal, and postmenopausal stages. Methods Data from the National Health and Nutritional Examination Survey cycles 2007 to 2020 were used and included women aged 18 to 80 years who were not pregnant or breastfeeding and without prior cardiovascular disease. Menopausal status was classified as pre‐, peri‐, or postmenopausal. LE8 scores were calculated as the continuous mean of 8 component scores and also categorized as poor, intermediate, or ideal. National Health and Nutritional Examination Survey analytical guidelines were followed. Adjusted linear regression models were used to assess temporal trends. Results A total of 9248 women were included in the final sample. In crude analyses, continuous median LE8 scores declined with advancing reproductive stage: 73.3 (premenopause), 69.1 (perimenopause), and 63.9 (postmenopause). Diet consistently received the lowest component score, while sleep received the highest. Across all stages, diet scores declined over time (Ptrend<0.001). Worsening body mass index scores were observed in pre‐ and postmenopausal women (Ptrend<0.001), while lipid and sleep scores improved in these groups (Ptrend<0.001). In comparison with premenopausal women, perimenopausal women were found to have higher age‐adjusted odds of categorical poor overall LE8 (adjusted odds ratio, 1.92 [95% CI, 1.13–3.26]), poor lipid score (adjusted odds ratio, 1.76 [95% CI, 1.12–2.76]), and poor glucose score (adjusted odds ratio, 1.83 [95% CI, 1.06–3.17]). Conclusions A decline in crude overall LE8 scores was observed from pre‐ to postmenopause, but age‐adjusted categorical analyses showed the highest odds of poor LE8 scores and poor lipid and glucose scores in perimenopause.