Tag: statistics

Eur J Heart Fail. 2026 Jan 14:xuag008. doi: 10.1093/ejhf/xuag008. Online ahead of print.

ABSTRACT

AIMS: The association between heart rate (HR) and clinical outcomes is well understood in patients with heart failure with reduced ejection fraction (HFrEF) but less clear in those with HFmrEF/HFpEF, especially among individuals with atrial fibrillation (AF). In a prespecified analysis of the FINEARTS-HF trial, we examined the association between baseline HR and clinical outcomes by heart rhythm and evaluated finerenone’s effect across the spectrum of HR.

METHODS: The primary outcome was a composite of cardiovascular death and total (first and recurrent) HF events. Heart rhythm (sinus rhythm or AF) was determined from the baseline ECG. Patients with pacemaker rhythm or missing HR/rhythm data were excluded.

RESULTS: Among patients with sinus rhythm (SR n = 3497; 62%), higher baseline HR was associated with a higher incidence rate for the primary outcome. In patients with AF (n = 2190; 38%), no association between HR and outcomes was observed. The effect of finerenone on the primary outcome was consistent across the HR spectrum, regardless of rhythm (P for interaction = 0.96 in SR; 0.49 in AF). In patients with SR, there was no significant HR change with finerenone versus placebo. In AF patients, finerenone led to a small but statistically significant HR reduction: a placebo-corrected decrease of 1.35 bpm (95% CI: 0.41-2.29) from baseline to 12 months.

CONCLUSIONS: Among patients with HFpEF/HFmrEF in FINEARTS-HF, higher baseline HR was associated with a higher risk of the primary outcome in patients with SR but not in those with AF. Finerenone’s effect on the primary outcome was consistent across the HR spectrum, irrespective of rhythm.

TRIAL REGISTRATION: ClinicalTrials.gov NCT04435626.

PMID:41771075 | DOI:10.1093/ejhf/xuag008

Eur J Heart Fail. 2026 Jan 21:xuag010. doi: 10.1093/ejhf/xuag010. Online ahead of print.

NO ABSTRACT

PMID:41771072 | DOI:10.1093/ejhf/xuag010

Eur J Heart Fail. 2026 Jan 12:xuaf023. doi: 10.1093/ejhf/xuaf023. Online ahead of print.

ABSTRACT

AIMS: For many years, fluid and sodium restriction have been considered an essential strategy for achieving effective decongestion in acute heart failure (AHF), but this paradigm has recently been questioned. This analysis aims to evaluate and compare the effectiveness of three different fluid strategies for decongestion: no fluid, fluid with sodium/chloride, and fluid without sodium/chloride in AHF.

METHODS: This post-hoc analysis of two prospective, single-centre, mechanistic studies included 55 patients with AHF and fluid overload. All patients received standardized furosemide dosing. A total of 21 patients received a continuous infusion of 0.9% NaCl (83 mL/h), 19 patients received 5% glucose (83 mL/h), and 15 did not receive any fluids. The primary outcome is urine volume and natriuresis at 6 h after loop diuretic administration.

RESULTS: There was a significant difference in cumulative (6 h) net natriuresis between patients receiving fluid therapy (n = 40) and those without fluid therapy (n = 15) (139 [66-264] mmol vs. 79 [15-144] mmol, P = .043). There was no significant difference in cumulative net diuresis between these groups (1170 [880-1890] mL vs. 1010 [475-1270] mL, P = .078), respectively. The NaCl group had a better diuretic response when compared with the glucose and no-fluids groups (absolute: 1980 [1620-3150] mL vs. 1510 [1075-2175] mL vs. 1010 [475-1270] mL, P < .001, net: 1480 [1120-2650] mL vs. 1010 [575-1675] mL vs. 1010 [475-1270] mL, P = .019, respectively) but the difference in natriuresis did not meet statistical significance (P = .126).

CONCLUSION: Intravenous fluid replacement during decongestion in patients with AHF was associated with increased net natriuresis and a trend towards higher urine output, with a significant augmentation of diuresis with sodium chloride supplementation.

PMID:41771069 | DOI:10.1093/ejhf/xuaf023

J Phys Chem B. 2026 Mar 2. doi: 10.1021/acs.jpcb.5c07449. Online ahead of print.

ABSTRACT

A molecular understanding of the solvation and dynamics of ions under static electric fields is crucial for modeling a wide range of natural and technological processes. Yet, traditional simulation methods suffer from a trade-off that has to be made between accuracy and statistical convergence. To bridge this gap, herein, we extend our recently introduced perturbed neural network potential molecular dynamics (PNNP MD) approach to investigate the solvation structures and ionic transport mechanisms of electrified alkali cationic solutions. We obtain ionic conductivities for Li⁺, Na⁺, and Cs⁺ from the field dependence of the ionic current density in good agreement with experiment. Surprisingly, the migration mechanism is found to be strikingly different for the three ions, despite their similar ionic conductivities. While Li⁺ conducts predominantly through vehicular migration of a stable 4-fold coordinated ion at all field strengths, Cs⁺ conducts strictly through a structural diffusion mechanism, where 9-12 transient first shell water coordination bonds are continuously broken and reformed. Notably, aqueous Na⁺ emerges as a “Goldilocks” ion: its ion-water interactions are strong enough to maintain distinct 5-6-fold coordination shells at zero field (unlike Cs⁺) yet labile enough to be strongly perturbed by electric fields (unlike Li⁺). As a consequence, we observe an electric-field-induced transition from vehicular to structural ionic transport for Na⁺ that is accompanied by a marked increase in ionic current density. Our results imply that the conductance mechanism of ions with moderate ion-solvent interactions can be effectively tuned by external electric fields.

PMID:41771043 | DOI:10.1021/acs.jpcb.5c07449

Neurology. 2026 Apr 14;106(7):e214710. doi: 10.1212/WNL.0000000000214710. Epub 2026 Mar 2.

ABSTRACT

BACKGROUND AND OBJECTIVES: Vagus nerve stimulation (VNS) is the most common neuromodulation technique used to treat drug-resistant epilepsy (DRE) in children. Despite this, approximately half of those implanted do not realize a benefit and there are currently no means to preoperatively identify responders. Recent neuroimaging work has suggested that intrinsic differences in brain connectivity may explain some heterogeneity in VNS responsiveness. In the current work, we sought to study whether preimplantation functional network perturbations in relation to interictal epileptiform discharges (IEDs) are associated with VNS response in children with focal DRE.

METHODS: We retrospectively studied resting-state magnetoencephalography in children with focal DRE (n = 65), recorded before VNS implantation. Beamforming was used to reconstruct source-level estimations of neural activity within a parcellation of 52 cortical brain regions. Static functional connectivity was estimated using amplitude envelope correlation, followed by general linear modeling and network-based statistics to identify spatial networks associated with VNS response (>50% seizure reduction at 6 months). Perturbations in brain connectivity were estimated by inferring dynamic cortical microstates from amplitude envelopes and extracting event-related microstate probability time courses surrounding IEDs. Differences in microstate dynamics after IEDs were assessed using t tests at each time point, comparing responders and nonresponders, followed by temporal cluster-based correction for multiple comparisons.

RESULTS: A total of 44 children were included in the final analysis (mean age 15 years, 57% male, 52% responders). No clinical variables, including IED topographies, were associated with VNS response. Significant static networks were identified in alpha-band connectivity relating to both VNS response (anterior-dominant, t = 4.52) and nonresponse (posterior-dominant, t = -4.98). From the dynamic microstate analysis, one microstate related to a frontotemporal network showed significantly greater perturbation in nonresponders compared with responders (temporal cluster p < 0.05), in the 500 milliseconds after IEDs.

DISCUSSION: Our results provide evidence that connectivity of an intrinsic, anterior-dominant network is associated with response to VNS. Responders to VNS are characterized by stronger baseline connectivity of this network and greater resilience of this network to IED-related disruption.

PMID:41771009 | DOI:10.1212/WNL.0000000000214710

NCHS Data Brief. 2026 Jan;(549). doi: 10.15620/cdc/174639.

ABSTRACT

INTRODUCTION: This report uses 2023-2024 National Vital Statistic System data to present the demographic group and by the type of drugs involved, specifically opioids and stimulants, with a focus on changes from 2023 to 2024.

METHODS: Data from the 2023-2024 NVSS were used for this analysis. Estimates are based on the National Vital Statistics System multiple-cause-of-death mortality files (1). Drug poisoning (overdose) deaths were defined as having an International Classification of Diseases, 10th Revision underlying cause-of-death code of X40-X44 (unintentional), X60-X64 (suicide), X85 (homicide), or Y10-Y14 (undetermined intent). Population estimates for 2023-2024 were estimated as of July 1, based on the blended base produced by the U.S. Census Bureau instead of the April 1, 2020, decennial population count. All of the race categories are single race, meaning that only one race was reported on the death certificate.

KEY FINDINGS: The age-adjusted drug overdose death rate decreased between 2022 and 2024, with the largest decrease, 26.2%, occurring from 2023 to 2024, from 31.3 deaths per 100,000 standard population to 23.1. From 2023 to 2024, rates of drug overdose deaths declined for all age groups, with the largest decrease occurring for younger age groups. From 2023 to 2024, rates declined for each race and Hispanic-origin group, with the largest decreases occurring for Black non-Hispanic people. Between 2023 and 2024, the drug overdose death rate involving synthetic opioids other than methadone decreased by 35.6% (from 22.2 to 14.3). Between 2023 and 2024, the rates of drug overdose deaths involving psychostimulants with abuse potential and cocaine both declined.

PMID:41770984 | DOI:10.15620/cdc/174639

IEEE Trans Vis Comput Graph. 2026 Mar 2;PP. doi: 10.1109/TVCG.2026.3667949. Online ahead of print.

ABSTRACT

We develop a probabilistic approach to understanding user preferences for adaptive placement of augmented reality (AR) interfaces in the physical environment through a series of user studies conducted using simulated desktop and virtual reality (VR) environments. From the first online crowdsourcing study and its validation in VR, we derived a set of potential factors behind user preferences for AR interface adaptation by assessing user-created layouts and analysing subjective user feedback. Building on this prior knowledge, we implemented a probabilistic optimisation system to generate adapted AR interfaces. Using generated layout pairs that prioritise different factors, we conducted a second online crowdsourcing study (N = 250) to elicit user preference rating data to quantify posterior probabilities for the weighting coefficients of the factors in the optimisation utility function. Overall, we found that the overall structures of layouts, such as shape and distribution, are more important to users than adapting to specific features of the environment, such as semantic associations between AR widgets and objects in the physical environments. We contribute a statistical model containing probabilistic distributions of different factors as a universal prior model that represents user preferences for AR interface placement that adapts to changing physical environments. Based on the results, we distil concrete guidelines for future adaptive AR interface systems regarding layout consistency, structure, and relationships between virtual widgets and physical objects.

PMID:41770971 | DOI:10.1109/TVCG.2026.3667949

IEEE J Biomed Health Inform. 2026 Mar 2;PP. doi: 10.1109/JBHI.2026.3669176. Online ahead of print.

ABSTRACT

Accurate segmentation of lesion in fundus OCT images an assist ophthalmologists to determine the degree of retinopathy and choroidopathy. However, OCT images are often acquired from various manufacturers’ OCT devices, which is challenging for traditional models due to domain shift. In this paper, a novel multi-source domain adaptation framework is designed to address the challenge of segmenting fundus lesions in OCT images acquired from devices produced by different manufacturers with three core methodological innovations: (1) A multi-order moment consistency approach using moment generating function (MGF) to align feature distributions across domains. By approximating multi-order central moments using derivatives of the MGF, our method theoretically enables efficient alignment of high-order statistical features without explicit computation of polynomial expansions. (2) A perturbation-based feature consistency strategy to improve model robustness. By using segmentation and moment losses to guide perturbation generation, our method explicitly links semantic consistency with feature distribution alignment. (3) A population stability whitening technique to separate style-related and content-related features. By analyzing covariance matrix variances across perturbations, our method attempts to automatically separate style and content features. Our method is compared with several state-of-the-art approaches on two datasets, comprising diverse domains collected from various manufacturers’ OCT devices. Experimental results clearly demonstrate the significant superiority of our method.

PMID:41770964 | DOI:10.1109/JBHI.2026.3669176

Genet Epidemiol. 2026 Apr;50(3):e70037. doi: 10.1002/gepi.70037.

ABSTRACT

In the last decade, genome-wide association studies (GWAS) have identified tens of thousands of common variants associated with a wide array of complex traits and diseases. Integration of GWAS with molecular data has informed the development of statistical tools for causal gene discovery. In this paper, we give an overview of commonly used causal inference methods and discuss the strengths and limitations of colocalization, Mendelian randomization (MR) and network-based approaches. Colocalization is often used to assess whether the genetic association signals for two traits arise from the same causal variant, thereby strengthening inferred causal associations. MR was developed to tackle issues of confounding and reverse causality, providing a rigorous approach to causal inference and demonstrating improved false discovery rates. Unlike MR, network-based analyses employ a discovery approach and model complex relationships between multiple variables. All causal inference methods are, to varying degrees, susceptible to spurious associations due to genetic confounding, pleiotropy and linkage disequilibrium. Here, we discuss the latest developments in the field of causal gene inference and limitations of these methods. We give an overview of interplay between different approaches as well as practical applications with reference to published examples in context of heart disease.

PMID:41770856 | DOI:10.1002/gepi.70037

PLoS One. 2026 Mar 2;21(3):e0343871. doi: 10.1371/journal.pone.0343871. eCollection 2026.

ABSTRACT

BACKGROUND: Pesticides are essential in agriculture for protecting crops from pests, diseases, and weeds, but improper use can lead to health issues like neurological disorders and carcinogenic effects. Strengthening regulatory frameworks, promoting integrated pest management strategies, and raising farmer awareness can mitigate pesticide misuse. In Ethiopia, widespread pesticide use in vegetables raises concerns about consumer exposure to pesticide residues. This study determined the pesticide residue in vegetables in Southwest Ethiopia.

METHODS: The study was conducted in randomly selected districts of the Jimma zone. Samples of tomatoes, potatoes, cabbage, and onions were collected from vegetable farmers. The modified QuEChERS (Quick, Easy, Cheap, Effective, Rugged, and Safe) methods were used for sample preparation and extraction. The analysis of pesticide residues was performed using gas chromatography coupled with a mass spectrometer (GC-MS) and an ion trap analyzer with an automatic injection. The pesticide detection levels among types of vegetables and locations were analyzed using one-way Analysis of variance (ANOVA) with statistical significance set at p < 0.05.

RESULTS: Pesticide residues were detected in vegetables from Seka Chokorsa, Goma, and Dedo districts. Detected pesticides include Lindane, Aldrin, Chlorpyrifos, 4,4-DDE, Hexachlorobenzene, and Endosulfan II. The highest concentrations were found in the Dabo Gibe onion sample (Seka Chokorsa), the Waro Kolobo potato sample (Dedo), and the Ganji Dalacho cabbage sample (Goma). Lindane residues were found in onion and potato (Seka Chokorsa), exceeding the Maximum Residue Limit (MRL) of 10-50 µg/kg. Chlorpyrifos residues were detected below MRLs across all districts, while 4,4-DDE residues were also detected in some vegetables, indicating historical use of banned pesticides. ANOVA results showed small variation between groups, and there was no statistically significant difference across the four groups (p-value = 0.305). The study highlights the need for stricter regulation, farmer education, and residue monitoring to ensure food safety.

PMID:41770822 | DOI:10.1371/journal.pone.0343871