Tag: pubmed

JAMA Netw Open. 2026 Apr 1;9(4):e265009. doi: 10.1001/jamanetworkopen.2026.5009.

ABSTRACT

IMPORTANCE: Disparities in outcomes for emergency general surgery (EGS) procedures may reflect structural inequities in access and care. Understanding how social and economic determinants contribute to these disparities could help identify opportunities to reduce them.

OBJECTIVE: To assess racial disparities between: (1) surgical setting (elective vs EGS), (2) surgical modality (minimally invasive [MIS] vs open), and (3) clinical outcomes of EGS procedures stratified by modality.

DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study using data from Premier Healthcare Database, a national, all-payer hospital discharge dataset, spanning 2016 to 2022. Participants were non-Hispanic Black or non-Hispanic White adult patients undergoing cholecystectomy, inguinal hernia repair, ventral hernia repair, or colorectal resections. Data analysis was performed from March 2025 to February 2026.

EXPOSURE: Surgical setting (elective vs EGS) and surgical modality (MIS vs open).

MAIN OUTCOMES AND MEASURES: The primary outcome was operative setting and modality, analyzed with multivariable logistic regression. Secondary outcomes included length of stay, perioperative complications, 30-day readmission, conversion to open modality, and in-hospital mortality. Propensity score matching was used to compare clinical outcomes between Black and White patients undergoing EGS by surgical modality.

RESULTS: Among 2 443 304 procedures, 254 281 (10.4%) were performed on Black patients, 2 189 023 (89.5%) were performed on White patients, 1 231 252 (50.3%) were performed on female patients, and 788 205 (32.3%) were performed emergently. Most patients were aged 45 to 64 years (939 123 patients [38.4%]). Black patients had higher adjusted odds of undergoing emergency vs elective procedures (adjusted odds ratio [aOR], 1.29; 95% CI, 1.28-1.30) and open vs MIS in the emergency setting (aOR, 1.06; 95% CI, 1.03-1.08) compared with White patients. Patients undergoing EGS were more likely to be older, female, Black, publicly insured, have higher comorbidity, live in rural areas, and be treated at nonteaching hospitals. Among MIS procedures, Black patients had higher rates of 30-day readmission, longer lengths of stay, and higher conversion to open surgery. For open surgical procedures, Black patients had longer lengths of stay.

CONCLUSIONS AND RELEVANCE: In this retrospective cohort study, Black patients faced disparities in surgical setting, access to MIS, and outcomes. These inequities highlight the need for targeted, equity-focused interventions to expand access to MIS and improve outcomes across diverse populations.

PMID:41931291 | DOI:10.1001/jamanetworkopen.2026.5009

JAMA Health Forum. 2026 Apr 3;7(4):e260414. doi: 10.1001/jamahealthforum.2026.0414.

ABSTRACT

IMPORTANCE: Amid an ongoing addiction crisis, private equity (PE) firms have acquired large numbers of residential substance use disorder (SUD) treatment facilities in the US. How PE ownership affects SUD care prices and facility characteristics is not well understood.

OBJECTIVE: To evaluate prices and facility characteristics of residential substance use treatment facilities owned by PE firms compared with other for-profit facilities.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study using a secret shopper framework was conducted from June 2024 to April 2025. PE-acquired residential SUD treatment facilities were matched to non-PE-acquired, for-profit control facilities by geographic proximity. Trained callers posed as individuals seeking residential SUD care for a family member with pending Medicaid insurance.

EXPOSURES: Ownership by PE vs non-PE for-profit entities.

MAIN OUTCOMES AND MEASURES: The primary outcome was daily rate. Secondary outcomes included bed availability and wait times, admission requirements, services, staffing, amenities, and facility-initiated contact.

RESULTS: This study included 341 residential facilities with completed call data (127 PE-acquired, 214 geographically matched non-PE for-profit). Mean (SD) daily rates were 15.6% higher at PE facilities ($910.73 [$463.16]; median, $854.29 [IQR, $589.29-$1071.43]) compared with non-PE facilities ($779.87 [$501.92]; median, $750.56 [IQR, $480.64-$952.38]; Benjamini-Hochberg-adjusted P = .04). This significantly higher daily rate was also found after adjustment for geographic cluster-matched fixed effects (β = $127.73; 95% CI, $29.57-$225.87; adjusted P = .03). Compared with non-PE-acquired control facilities, PE-acquired facilities were less likely to offer detox services (74.8% vs 88.8%; adjusted P = .02) and private rooms (12.1% vs 25.7%; adjusted P = .02), and more likely to make postcall contact attempts (mean [SD], 0.68 [1.39] vs 0.18 [0.47]; adjusted P < .001).

CONCLUSIONS AND RELEVANCE: In this national secret shopper study, PE-acquired residential SUD treatment facilities reported higher daily prices than geographically matched non-PE for-profit facilities. Price differences persisted after accounting for local market factors, suggesting systematic cost differences associated with ownership structure. This study provides facility-level evidence on pricing differences by ownership type in residential SUD treatment and highlights the need for further research to understand the mechanisms underlying these differences and their implications for patients and payers.

PMID:41931287 | DOI:10.1001/jamahealthforum.2026.0414

JAMA Health Forum. 2026 Apr 3;7(4):e260491. doi: 10.1001/jamahealthforum.2026.0491.

ABSTRACT

IMPORTANCE: Variation in cardiovascular care completion is well documented. However, less is known about differences originating from earlier, intermediate stages such as ordering or scheduling of testing or referrals, despite their role as key prerequisites for care access.

OBJECTIVE: To examine the care cascades for coronary artery disease (CAD) after emergency department (ED) visits and to identify the specific stages at which variation emerges for CAD testing and cardiology referrals.

DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective cohort study using data and metadata from electronic health records from a large multicenter health system. Participants were adult patients with established primary care and no history of ischemic heart disease or cardiology care who presented to an ED from January 1, 2020, to June 30, 2022, and underwent a troponin test, a proxy for clinically suspected myocardial ischemia. Variation in cardiovascular follow-up care (CAD testing and cardiology referrals) was identified and analyzed. Analyses were restricted to patients with above-median electrocardiogram (ECG)-derived ischemia risk scores to enrich for higher likelihood of benefit from cardiovascular follow-up.

MAIN OUTCOMES AND MEASURES: Receipt of an order for CAD testing (stress tests, coronary computed tomography angiography) or cardiology referral, scheduling of the service, and completion within 6 months. Outcomes were compared by insurance type, race and ethnicity, language, and sex using multivariable logistic regression adjusted for demographic characteristics, clinical factors, and ECG-derived cardiovascular risk.

RESULTS: Among 16 475 patients with an ED visit (median [IQR] age, 67.4 [54.9-77.9] years; 36% female and 64% male individuals) and elevated cardiovascular risk, marked variation in follow-up care emerged. Compared to commercially insured patients, those with Medicare dual or disabled coverage had lower adjusted odds of completing CAD testing (adjusted odds ratio [aOR], 0.45; 95% CI, 0.36-0.56) and cardiology referrals (aOR, 0.47; 95% CI, 0.39-0.57); similar patterns were seen for Medicaid coverage. Patients whose primary language was not English were less likely to complete either service (CAD testing aOR, 0.77; 95% CI, 0.61-0.98; referral aOR, 0.75, 95% CI, 0.61-0.92), and female patients had lower adjusted odds of completing CAD testing (aOR, 0.86; 95% CI, 0.77- 0.96). Adjusted differences by race and ethnicity were modest. Variation was primarily associated with ordering differences and with additional scheduling barriers for select groups. Once scheduled, completion rates exceeded 75%, without differences between groups.

CONCLUSIONS AND RELEVANCE: This retrospective cohort study found that among patients who visited the ED with elevated ischemic risk, attrition in follow-up care was concentrated early in care cascades and most pronounced among those with noncommercial health insurance. This stepwise analytic framework offers a novel, reproducible approach for health systems to identify where and for whom care gaps arise, which can enable targeted interventions to improve equity and efficiency.

PMID:41931286 | DOI:10.1001/jamahealthforum.2026.0491

Brain Inform. 2026 Apr 3. doi: 10.1186/s40708-026-00299-w. Online ahead of print.

ABSTRACT

PURPOSE: MELD Graph is a state-of-the-art artificial intelligence (AI) model for automated detection of focal cortical dysplasia (FCD), but its performance remains limited, highlighting the need to investigate which aspects of the pipeline affect its accuracy.

METHODS: A retrospective failure-mode analysis of the MELD Graph pipeline was performed in 242 subjects, with model predictions and FreeSurfer segmentations reviewed to classify errors as segmentation-associated or algorithm-related. FCD imaging features salient to humans were quantified, with statistical associations examined for both MELD Graph detection and focal FreeSurfer segmentation failure.

RESULTS: MELD Graph demonstrated overall performance similar to previously published non-harmonized results, achieving a sensitivity of 69%, specificity of 44%, and positive predictive value (PPV) of 75%. Focal FreeSurfer segmentation failures were associated with 21% of false negative patients, 25% of false positive clusters in patients, and 16% of false positive clusters in controls. Following manual cortical segmentation correction and rerunning of MELD Graph, 67% of the segmentation-associated missed lesions were detected, and segmentation-associated false positive clusters were reduced or eliminated in 75% of controls with such clusters. Higher conspicuity on T1-weighted images was associated with MELD Graph detection, whereas greater conspicuity on T2-FLAIR images relative to T1 was associated with detection failure. Non-bottom-of-sulcus lesion location, higher human conspicuity measures, and low T1 image quality were positively associated with focal FreeSurfer segmentation failures.

CONCLUSION: FreeSurfer segmentation failures are a significant potential source of error in the MELD Graph pipeline. FCD imaging features salient to humans and image quality were also associated with variability in algorithm performance. Robust cortical segmentation and stronger integration of T2-FLAIR imaging features may be beneficial for automated FCD detection tools.

CLINICAL TRIAL REGISTRATION: Not applicable. This study is a retrospective analysis of previously acquired open-source imaging datasets and does not constitute a clinical trial.

PMID:41931246 | DOI:10.1186/s40708-026-00299-w

Drugs R D. 2026 Apr 3. doi: 10.1007/s40268-026-00543-y. Online ahead of print.

ABSTRACT

BACKGROUND AND OBJECTIVES: Viloxazine, which has been used to treat depression and attention-deficit/hyperactivity disorder (ADHD), has been termed a moderate-affinity, selective norepinephrine reuptake inhibitor based on high selectivity for norepinephrine relative to serotonin and dopamine transporters. However, accumulated research suggests a more complex mechanism of action, based on studies showing activity at serotonin 5-HT_2C, 5-HT_2B, and 5-HT₇ receptors, as well as findings that viloxazine increases extracellular serotonin (along with norepinephrine and dopamine) in the rat prefrontal cortex. This in vitro pharmacology study aimed to replicate and expand prior experiments to better characterize viloxazine’s affinity for and activity at the norepinephrine transporter (NET) and individual serotonin receptors and to clarify how these effects contribute to the mechanism of action.

METHODS: Using in vitro binding competition and functional assays and ex vivo receptor occupancy studies in rats, we assessed viloxazine activity at human NET isoforms and 5-HT_2C, 5-HT_2B, and 5-HT₇ receptors relative to clinically relevant unbound viloxazine plasma concentrations (0.4-3.6 μM).

RESULTS: Viloxazine showed moderate binding affinity for NET (inhibition constant [K_i] = 0.13 µM) and 5-HT_2C (K_i = 0.66 µM), 5-HT_2B (K_i = 0.83 µM), and 5-HT₇ (K_i = 1.90 µM) receptors. In vitro functional studies showed viloxazine acted as a NET inhibitor, 5-HT_2C partial agonist, and 5-HT_2B and 5-HT₇ antagonist. At clinically relevant concentrations, viloxazine could potentially occupy nearly 95% of NET, more than 80% of 5-HT_2C and 5-HT_2B, and 65% of 5-HT₇ receptors. Subsequent ex vivo studies in rats confirmed high NET occupancy (67-94%) at clinically relevant concentrations.

CONCLUSIONS: These results validate previous experiments showing that viloxazine, in addition to displaying high NET occupancy, acts as a partial agonist at 5-HT_2C receptors and an antagonist at 5-HT_2B and 5-HT₇ receptors at clinically relevant concentrations for ADHD treatment. Therefore, both NET inhibition and serotonin receptor activity may contribute to viloxazine’s clinical efficacy. These findings are contributing to a renewed understanding of viloxazine’s pharmacodynamic profile and likely multimodal mechanism of action.

PMID:41931242 | DOI:10.1007/s40268-026-00543-y

Trop Anim Health Prod. 2026 Apr 3;58(3):217. doi: 10.1007/s11250-026-05018-5.

NO ABSTRACT

PMID:41931203 | DOI:10.1007/s11250-026-05018-5

CNS Neurol Disord Drug Targets. 2026 Mar 26. doi: 10.2174/0118715273434957260202115619. Online ahead of print.

ABSTRACT

INTRODUCTION: Inflammatory and coagulation pathways are crucial in the pathogenesis and clinical progression of ischemic stroke. The objective of this study was to evaluate serum concentrations of interleukin-2 (IL-2) and interleukin-10 (IL-10), as well as the gene expression of tissue factor (TF) in peripheral blood mononuclear cells (PBMCs), and to examine their correlations with stroke severity and clinical outcomes.

MATERIALS AND METHODS: We enrolled 148 patients with ischemic stroke and 30 healthy controls matched for age and sex in a cross-sectional design. We used ELISA to measure the levels of IL-2 and IL-10 in serum and real-time PCR to look at TF gene expression in PBMCs. The NIH Stroke Scale (NIHSS) was used to measure the severity of strokes, and the results were compared to clinical variables.

RESULTS: Patients with severe stroke showed significantly lower levels of IL-2 and IL-10 (p < 0.001), and TF expression in PBMCs was significantly higher in both mild and severe stroke groups compared to controls (p < 0.001). There was no statistically significant difference between the mild and severe groups (p = 0.213). In severe cases, IL-2 and TF were negatively correlated (p = 0.036). Nonetheless, none of the biomarkers independently forecasted survival outcomes.

DISCUSSION: The results show that the immune-coagulation axis is not working properly in severe ischemic stroke. Lower levels of IL-2 and IL-10 may indicate that regulatory T-cells aren’t working properly and that anti-inflammatory control isn’t working, which can cause monocytes to become active and TF levels to rise. This interaction probably makes thromboinflammatory cascades worse, which leads to more damage to the nervous system. These changes, even though they don’t predict survival, give us a better understanding of how strokes work and open up new possibilities for targeted immunomodulatory therapy.

CONCLUSION: The changes in IL-2, IL-10, and TF expression indicate a coordinated disruption of immune and thrombotic pathways in individuals with severe ischemic stroke. Although not prognostic of mortality, these biomarkers may indicate disease severity and represent potential targets for future therapeutic interventions. Longitudinal studies are necessary to validate their prognostic significance and investigate their incorporation into clinical decision-making algorithms for stroke.

PMID:41930584 | DOI:10.2174/0118715273434957260202115619

Cancer Treat Res Commun. 2026 Mar 12;47:101171. doi: 10.1016/j.ctarc.2026.101171. Online ahead of print.

ABSTRACT

BACKGROUND: TFE3-RCC is rare, hard to distinguish from common RCC on CT, posing preoperative diagnostic challenges for clinicians. This two-center study aimed to develop interpretable machine learning models using radiomics to differentiate Xp11.2/TFE3 translocation renal cell carcinoma (TFE3-RCC) from common renal cell carcinoma (RCC) subtypes using computed tomography (CT) images.

METHODS: Retrospective data from 1394 patients (39 TFE3-RCC, 1355 non-TFE3 RCC) were analyzed. A propensity score matching (PSM) was applied, resulting in 234 cases (TFE3: n = 39, non-TFE3: n = 195) included in the radiomics study. CT images were segmented using an AI-based model, and 102 radiomic features (shape, first-order statistics, texture) were extracted. Recursive feature elimination (RFE) with random forest and gradient boosting models were used for feature selection and model development. Performance was evaluated via area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity.

RESULTS: The patients with TFE3-RCC were significantly younger (36.51 ± 12.68 vs. 57.30 ± 12.00 years, P < 0.05), and had more frequent calcification (30.8% vs. 6.4%, P < 0.05) and were larger (5.50 ± 3.17 cm vs. 4.11 ± 2.06 cm, P = 0.005) than those with non-TFE3 RCC, and preferred to implicate females (female: 46.2% vs. 29.3%, P = 0.023). The model identified six optimal features, with skewness (relative weight: 44.57%) and first-order statistics as key predictors. The training set and test set achieved stable performances with AUC (0.951 (95% CI: 0.920-0.983) and 0.864 (95% CI: 0.749-0.979)) and accuracy (0.878 and 0.852).

CONCLUSION: Interpretable radiomics-based machine learning models effectively differentiate TFE3-RCC from common RCC subtypes, with skewness and intensity features as critical biomarkers. This approach may improve preoperative diagnosis, though larger multi-center studies and integration of multi-omics data are needed for clinical translation.

PMID:41930555 | DOI:10.1016/j.ctarc.2026.101171

Int Emerg Nurs. 2026 Apr 1;86:101815. doi: 10.1016/j.ienj.2026.101815. Online ahead of print.

ABSTRACT

BACKGROUND: Workplace violence (WPV) is a major occupational hazard for emergency nurses, with verbal, psychological, and physical threats undermining safety. Multiple safety strategies have been proposed, yet little research has examined their prevalence or link to perceived safety.

METHODS: A cross-sectional design was employed using an anonymous electronic survey of emergency nurses across 17 U.S. states. The survey, validated by nursing experts, assessed demographics, workplace characteristics, exposure to WPV, and 14 safety precautions. Perceived safety was rated on a 10-point scale. Descriptive statistics, bivariate tests, and multivariate regression with bootstrapping were conducted.

RESULTS: Among 134 participants (M age = 42.8 years, 84.3% female), 48.1% reported experiencing WPV in the past month. Mean safety rating was 6.84 (SD = 2). De-escalation and security presence were most prevalent (90.3%), followed by controlled access (80.6%) and security cameras (77.6%). Regression analysis showed urban nurses reported lower safety than suburban nurses (b = – 1.62, 95% CI [-2.438, -0.913], p < 0.001). Security presence, controlled access, and lighting were associated with higher safety perceptions (b = 1.31, 95% CI [0.487, 2.322], p = 0.018; b = 1.12, 95% CI [0.396, 1.881], p = 0.008; b = 1.09, 95% CI [0.478, 1.784], p = 0.004, respectively).

CONCLUSION: Findings highlight the prevalence of WPV in EDs and identify key safety interventions linked to nurses’ perceptions of safety. Results can inform policy and guide workplace improvements.

PMID:41930553 | DOI:10.1016/j.ienj.2026.101815

Neural Netw. 2026 Mar 22;201:108889. doi: 10.1016/j.neunet.2026.108889. Online ahead of print.

ABSTRACT

Federated learning, a vital paradigm in modern machine learning, enables private and decentralised training of models that is crucial for learning from sensitive data. Noisy label learning, another vital paradigm in modern machine learning, addresses the training of models from the data with potentially incorrect labels. Their integration, namely federated learning with noisy labels (FLNL), is an emerging but challenging topic arising from the practice of machine learning, which, however, still lacks a review of its research progress. The aim of this paper is to fill in this gap. We first summarise four core challenges to FLNL: localised label noise, across-client heterogeneity of label noise, localised overfitting to label noise, and inadequate benchmarking. We then propose a taxonomy to categorise current FLNL studies into four types that address the four challenges correspondingly: sample-wise methods, client-wise methods, model-wise methods, and benchmark-wise studies. This work offers the first comprehensive and concise review dedicated to FLNL; moreover, we also provide future research directions for this rapidly evolving and practically significant field.

PMID:41930546 | DOI:10.1016/j.neunet.2026.108889