Category: Statistics

J Radiol Prot. 2026 Feb 23. doi: 10.1088/1361-6498/ae490e. Online ahead of print.

ABSTRACT

Borated polyethylene is an effective neutron moderator and absorber in medical linear accelerator shielding; however, there is limited data regarding the required material thickness for adequate neutron attenuation. To address the gap in shielding data, our study systematically quantifies first and equilibrium tenth-value layers (TVL1 and TVLe) for polyethylene containing 0%, 5% and 30% natural boron by weight across neutron energies ranging from thermal to fast. Comprehensive Monte Carlo simulations (n = 3504) were performed to estimate TVL thicknesses from thermal to 20 MeV neutrons. A current tally was used to count neutrons exiting the shield and determine thicknesses corresponding to 10% and 1% transmission. Sixteen energies and 73 thicknesses of materials were modelled with statistical uncertainties below 3%. TVL thicknesses were independently validated with PHITS using identical simulation parameters. We found that TVL values ranged from 1.3 mm for thermal neutrons in borated polyethylene, to 50 cm for 20 MeV neutrons in pure polyethylene. In all cases, adding boron to polyethylene reduced the TVL, with the greatest effect at thermal energies, and a smallest effect at 12 MeV. Here we provide the first comprehensive characterization of borated polyethylene’s ability to attenuate neutrons, supporting shielding design for medical linear accelerators.

PMID:41730243 | DOI:10.1088/1361-6498/ae490e

Am Nat. 2026 Mar;207(3):347-355. doi: 10.1086/738891. Epub 2026 Jan 27.

ABSTRACT

AbstractGenomic forecasting is an emerging area of predictive ecology and evolution that leverages high-throughput sequencing to incorporate information on genomic variation into quantitative predictions of biological responses to environmental change. A central and increasingly applied concept in this field is genomic offset, a measure of the mismatch between current genomic composition and that predicted in new environments. This special issue brings together six studies spanning theoretical and methodological development, empirical evaluation, time series analysis, and conservation applications aimed at advancing the potential of genomic offset and related forecasting approaches for predicting population responses to environmental change. Contributions explore how genomic offset relates to stabilizing selection, compare individual- versus population-level offset models, and evaluate predictions using common garden experiments, long-term forest inventories, genomic time series, and conservation-relevant taxa. Collectively, the articles underscore both the promise and the current limitations of genomic forecasting while emphasizing that model predictive performance is often context dependent and influenced by statistical method, loci choice, and fitness proxies. Future progress will require rigorous validation, theory and methods development, and broader taxonomic coverage to ensure that genomic forecasting can realize its potential for informing biodiversity management in a rapidly changing world.

PMID:41730225 | DOI:10.1086/738891

Am Nat. 2026 Mar;207(3):356-367. doi: 10.1086/739079. Epub 2026 Jan 13.

ABSTRACT

AbstractGenomic offset metrics are increasingly used to predict population maladaptation under changing climates, based on the assumption of a negative statistical relationship between offset measures and local relative fitness. Recent theoretical advances have confirmed this relationship by relating genomic offset to phenotypic trait distances along selection gradients. However, these metrics typically rely on the assumption that stabilizing selection, which maintains local adaptive optima, operates on fitness-related traits through Gaussian-shaped selection gradients. In this study, we extend the theory to accommodate more diverse forms of selection gradients and introduce more general genomic offset measures that preserve the fitness-offset relationship. We validate this generalization through simulations and demonstrate the utility of these new measures in predicting relative fitness in common garden experiments involving three plant species: pearl millet, a vital staple cereal grown in arid soils, and two emblematic North American tree species, balsam poplar and red spruce. Our findings indicate that assuming a local Gaussian-shaped selection gradient for climate adaptation is a robust approximation for these species. These results have important implications for validating genomic offset predictions using fitness proxies and for studies that aim to predict fitness loss based on genomic offset metrics.

PMID:41730221 | DOI:10.1086/739079

JMIR Form Res. 2026 Feb 23;10:e82865. doi: 10.2196/82865.

ABSTRACT

BACKGROUND: In 2017, the US Department of Health and Human Services declared a national opioid crisis. In 2022, an estimated 81,806 overdose deaths involved an opioid. Emergency departments are critical in the pathway of care for providing resources and linkages to services. Studies investigating emergency medicine (EM) physicians’ perspectives on the opioid crisis have largely focused on prescribing.

OBJECTIVES: To investigate EM physicians’ perspectives on response strategies to the opioid crisis of biosurveillance and linkages to care. A secondary objective was to map reported challenges and recommendations using a sequential intercept model as an actionable framework.

METHODS: This is a qualitative study. Six EM physicians in an academic health care system were interviewed through semi-structured interviews. Interviews were transcribed, then thematically coded and analyzed to identify cross-sector settings and barriers to care with corresponding recommendations. Settings and recommendations were mapped as a sequential intercept model.

RESULTS: EM physicians identified 9 key settings as crucial touch points in the opioid crisis: home setting, emergency medical services, patient care, clinically relevant data and information, prescriptions and pain management, predischarge coordination, outpatient resources, biosurveillance sample collection, and the external partner and administrative environment. Biosurveillance challenges included concerns about collecting biological materials for state and regional monitoring, as well as the time burden for sample collection. Linkage to care challenges included social determinants of health and limited outpatient care access. Recommendations were specific to each setting and included care coordination and fostering cross-sector partnerships. A patient-centered approach and better integration of community resources were emphasized.

CONCLUSIONS: The service delivery culture is of acute and episodic care but needs to more seamlessly address care across its fragmented multicomponent complex system. EM physicians face systemic challenges and provide actionable recommendations to promote comprehensive care to patients presenting to the emergency department with opioid-related complaints.

PMID:41730220 | DOI:10.2196/82865

J Med Internet Res. 2026 Feb 23;28:e86262. doi: 10.2196/86262.

ABSTRACT

BACKGROUND: Traditional cognitive screening relies on episodic clinical assessments and may miss early changes preceding cognitive impairment and dementia. Wearable and mobile health technologies enable continuous monitoring of sleep, physical activity, and circadian rhythms, generating digital biomarkers that may support scalable early detection and prevention. However, current evidence remains fragmented across devices, analytic approaches, and cognitive outcomes.

OBJECTIVE: This study synthesizes and critically evaluates recent evidence on wearable devices for early detection and prevention of cognitive impairment and dementia, focusing on device categories, cognitive outcomes, analytic approaches, and prevention relevance.

METHODS: We searched PubMed, Scopus, ACM Digital Library, and SpringerLink for peer-reviewed studies published between January 2020 and December 1, 2025. Eligible studies included human participants with a mean age ≥50 years, continuous wearable-derived data collected for ≥24 hours, and validated cognitive outcomes; reviews, protocols, smartphone-only studies, and pharmacological interventions were excluded. Two reviewers independently screened studies, extracted data, and assessed risk of bias using the Appraisal Tool for Cross-Sectional Studies, Newcastle-Ottawa Scale, Cochrane Risk of Bias tool, and Quality Assessment of Diagnostic Accuracy Studies-2. Owing to substantial heterogeneity in devices, outcomes, and analytic methods, quantitative meta-analysis was not feasible; a structured narrative synthesis was conducted in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidance. This study was not prospectively registered.

RESULTS: We included 49 studies, with sample sizes ranging from 14 to 91,948 participants (>200,000 total) and a median sample size of 145. Most used research-grade actigraphy (43/49, 87.8%), while fewer used commercial wearables (7/49, 14.3%). Cognitive outcomes most frequently relied on global screening instruments, including the Mini-Mental State Examination (18/49, 36.7%), followed by ICD-10 (International Statistical Classification of Diseases, Tenth Revision)-based clinical diagnoses (7/49, 14.3%) and the Montreal Cognitive Assessment (7/49, 14.3%). Analytic approaches were predominantly statistical (36/49, 73.5%), with fewer studies applying machine learning (7/49, 14.3%) or deep learning methods (6/49, 12.2%). Statistical analyses linked disrupted sleep, circadian rhythm fragmentation, and irregular activity patterns to worse cognitive outcomes, with modest-to-moderate effect sizes. Machine learning and deep learning approaches reported classification performance with area under the curve values between approximately 0.70 and 0.95. Approximately one-quarter of the studies (13/49, 26.5%) addressed early detection or prevention through longitudinal risk estimation or predictive modeling. Key limitations included small sample sizes, short monitoring durations, and limited external validation.

CONCLUSIONS: Wearable-derived behavioral markers show promise for early risk stratification. This review advances the field by shifting from descriptive associations toward a digital phenotyping framework evaluating artificial intelligence-driven prediction in the preclinical window. Unlike prior reviews focused on established dementia, it differentiates direct predictive evidence from indirect correlational findings and critically assesses methodological maturity. Continuous, passive monitoring may enable scalable detection of subtle behavioral changes, supporting earlier and more personalized risk reduction strategies.

PMID:41730193 | DOI:10.2196/86262

J Neurosurg Case Lessons. 2026 Feb 23;11(8):CASE25725. doi: 10.3171/CASE25725. Print 2026 Feb 23.

ABSTRACT

BACKGROUND: While deep brain stimulation (DBS) is an effective therapy for essential tremor (ET), Gamma Knife radiosurgery (GKRS) offers a noninvasive alternative for patients who are poor surgical candidates or who experience DBS-related complications. Although GKRS ventral intermediate nucleus (VIM) thalamotomy is generally safe, very delayed adverse effects are uncommon and not well characterized.

OBSERVATIONS: A 69-year-old woman with medically refractory ET underwent right VIM DBS, but the device was later explanted due to infection. Because she was high-risk for reimplantation, she proceeded with GKRS VIM thalamotomy. Eight years later, she developed progressive left-sided weakness and gait deviation. MRI revealed a new right thalamic cystic lesion precisely colocalized with the prior GKRS target. Stereotactic aspiration demonstrated acellular, proteinaceous fluid without evidence of malignancy or infection, consistent with a delayed postradiosurgical cyst. Neurological function improved following drainage.

LESSONS: Delayed cyst formation may occur many years after GKRS VIM thalamotomy and should be recognized as a rare but clinically significant late complication. Given the typical 7- to 10-year latency observed across radiosurgical cystogenesis, long-term but low-frequency MRI surveillance, such as a 1-year posttreatment baseline followed by imaging every 2-3 years or sooner with new neurological symptoms, may facilitate earlier detection and intervention. https://thejns.org/doi/10.3171/CASE25725.

PMID:41730189 | DOI:10.3171/CASE25725

J Neurosurg Case Lessons. 2026 Feb 23;11(8):CASE25667. doi: 10.3171/CASE25667. Print 2026 Feb 23.

ABSTRACT

BACKGROUND: For small- to medium-sized vestibular schwannomas, especially in patients with preserved hearing and no mass-effect symptoms, Gamma Knife radiosurgery (GKRS) is a preferred initial treatment. It provides effective tumor control and long-term hearing preservation. In the event of a tumor progression, reirradiation remains an option. A rare occurrence is the development of a second schwannoma along the same nerve. In such cases, repeat GKRS can be challenging, as it requires balancing local control with minimizing integral radiation dose and potential toxicity from reirradiation. The authors highlight the feasibility of repeat GKRS and the dosimetric considerations involved in radiating a second schwannoma along the same nerve.

OBSERVATIONS: A 35-year-old woman with a history of headaches and a right-sided vestibular schwannoma underwent GKRS as treatment for the tumor. After being under surveillance from 2013 to 2025, the patient’s vestibular schwannoma remained stable. After experiencing a worsening right-sided tinnitus, an updated MRI study revealed a new intracanalicular nodular formation along the nerve, which was treated with GKRS.

LESSONS: This case demonstrates the safety and efficacy of GKRS as a retreatment option in the rare occurrence of a second vestibular schwannoma developing along the same cranial nerve. https://thejns.org/doi/10.3171/CASE25667.

PMID:41730187 | DOI:10.3171/CASE25667

Anesthesiology. 2026 Feb 23. doi: 10.1097/ALN.0000000000006005. Online ahead of print.

ABSTRACT

BACKGROUND: Preoperative gastric ultrasonography serves as an objective tool for evaluating the risk of pulmonary aspiration. However, measurements obtained from gastric ultrasonography at the abdominal aorta (AA) plane and the inferior vena cava (IVC) plane may vary substantially. This study aims to identify the measurement plane that most closely reflects the actual gastric volume (GV), thereby informing clinical practice.

METHODS: All participants initially underwent gastric ultrasonography at both the AA and IVC planes following a fasting period, representing the low GV state. Subsequently, they consumed apple juice at a volume of 2.3 ml/kg, after which gastric ultrasonography was repeated to represent the high GV state. The predicted ingested volume (PIV) was calculated as the predicted GV after ingestion minus the baseline predicted GV. Comparisons were made between AA plane and IVC plane measurements in both low GV and high GV. The agreement between the PIV and the actual ingested volume (AIV) was assessed for the AA plane, IVC plane, higher-measured gastric volume plane, and lower-measured gastric volume plane, along with their detection rates for high aspiration risk.

RESULTS: Ultimately, 196 volunteers were included in the final statistical analysis. The results showed that, in both low and high GV state, gastric ultrasonography measurements at the AA plane and the IVC plane differed significantly (P< 0.001). Among all measurement planes, only the higher-measured gastric volume plane showed no statistically significant difference between the predicted and actual GV, with the smallest bias (bias = -4.27 ml, P= 0.076).

CONCLUSIONS: Notable differences exist between gastric ultrasonography measurement planes. When applying existing predictive models, measurements obtained from the higher-measured gastric volume plane provide greater accuracy. Differentiating between measurement planes during model development may enhance the predictive accuracy of such models.

PMID:41730171 | DOI:10.1097/ALN.0000000000006005

JMIR Hum Factors. 2026 Feb 23;13:e75496. doi: 10.2196/75496.

ABSTRACT

BACKGROUND: Digital health tools are increasingly prevalent in postoperative care management, yet limited research exists on digital health literacy and tool adoption among safety-net hospital populations. Understanding these factors is crucial for developing effective digital health solutions for historically underserved communities.

OBJECTIVE: This study aimed to evaluate digital health literacy, assess technology adoption readiness, and examine the relationship between patient-reported capabilities and demographic factors in a postoperative care context at a safety-net hospital.

METHODS: We conducted a mixed methods study with 71 postoperative patients and 29 health care providers at a safety-net hospital. Participants completed a modified eHealth Literacy Scale (eHEALS) assessment and a demographic questionnaire, followed by usability testing of PocketDoc, a digital health prototype. The modified 7-item eHEALS demonstrated adequate internal consistency (Cronbach α=0.77). Qualitative data from think-aloud protocols during usability testing were collected for future analysis. This study focused on quantitative assessments of digital health literacy (using the modified eHEALS on a 5-point Likert scale) and technology adoption readiness (via usability metrics on a 10-point Likert scale) analyzed using nonparametric statistical tests. Correlations between demographic factors and digital health literacy were examined using Spearman rank-order correlation.

RESULTS: Despite common assumptions about technology barriers in safety-net populations, 69% (49/71) of patients reported high confidence (score of ≥3 on a 5-point scale) in finding health resources online, and 61% (43/71) expressed confidence in using the internet for health-related questions. However, only 49% (35/71) felt confident in using digital resources for health decision-making. Digital health literacy scores did not correlate with age or educational level, although 79% (56/71) of patients reported ≥10 years of digital device experience. Both patients and health care providers rated PocketDoc highly for ease of use (median 10, IQR 8-10) and task intuitiveness (median 10, IQR 8-10). Patients’ confidence in finding and using health resources online positively correlated with interface satisfaction (ρ=0.262-0.304 and ρ=0.010-0.027, respectively).

CONCLUSIONS: Our exploratory findings from 100 participants suggest that digital health tools may be more feasible in safety-net settings than previously considered, although the sample size and single-site design limit generalizability. However, the gap between patients’ ability to find health resources (49/71, 69% confident) and their confidence in using these resources for health decision-making (35/71, 49% confident) highlights the need for targeted support in translating digital capabilities to health management skills.

PMID:41730170 | DOI:10.2196/75496

JMIR Mhealth Uhealth. 2026 Feb 23;14:e68930. doi: 10.2196/68930.

ABSTRACT

BACKGROUND: The growth of mobile health has underscored the critical importance of equitable internet access in promoting healthy aging. Among older adults, particularly those in digitally underserved populations, access to mobile data is often limited due to affordability and technological barriers, leading to a phenomenon known as “data deprivation.” This form of digital inequality limits the older adults’ ability to participate in social, recreational, and community-based activities, which are protective against isolation and decline in later life. In South Korea, where unlimited smartphone data plans have become increasingly accessible, a unique opportunity exists to examine the real-world association of improved data accessibility on older adults’ social lives and digital engagement.

OBJECTIVE: This study aimed to examine whether switching to unlimited smartphone data plans enhances social participation among older adults in South Korea. It also explored whether this relationship differs by demographic and socioeconomic characteristics, such as age, gender, region, household composition, and income level. The study focused on offline domains of social participation, including hobby gatherings, religious services, volunteering, and routine activities such as shopping.

METHODS: Data were drawn from the Korea Media Panel Survey (2016-2022), a nationally representative longitudinal dataset. The final sample included 5021 individuals. Social participation was measured using a self-reported 8-item scale (8-64 points) covering outdoor activities, volunteering, and more. A difference-in-differences approach was used to assess the association of switching from limited to unlimited smartphone data plans on social activity scores. Subgroup analyses examined heterogeneity by gender, household composition, income, and region.

RESULTS: Overall, among individuals aged 60 years and older, switching to an unlimited data plan was not associated with a statistically significant change in social activity scores. However, within this group, those aged 70 years and older showed a more notable-though not statistically significant-improvement (differential of 1.54, 95% CI -0.41 to 3.50). In contrast, older men living alone experienced a significant differential improvement of 6.44 (95% CI 3.39 to 9.50) points, compared with those who remained on limited plans.

CONCLUSIONS: Although the overall association of unlimited data plans was limited, certain vulnerable subgroups-particularly older men living alone-experienced meaningful gains. These findings suggest that improving mobile data accessibility may enhance social engagement among digitally underserved older adults. Compared with more complex or resource-intensive interventions, expanding access to unlimited smartphone data plans may offer a relatively simple and scalable strategy to support healthy aging and reduce social isolation.

PMID:41730168 | DOI:10.2196/68930