Tag: statistics

J Gerontol A Biol Sci Med Sci. 2026 Aug 28:glag209. doi: 10.1093/gerona/glag209. Online ahead of print.

ABSTRACT

BACKGROUND: Telomere length (TL) is a well-established biomarker of cellular senescence, yet the metabolic profile of TL and its associations with aging-related phenotypes and responses to modifiable lifestyle factors remain unclear.

METHODS: TL was measured using quantitative real-time polymerase chain reaction (qPCR) in 282 participants from the West China Health and Aging Cohort (WCHAC). Plasma metabolites were analyzed using Liquid Chromatography-tandem Mass Spectrometry. TL-associated metabolic signatures (Met-TL) were identified through elastic net regression models. Associations between Met-TL and aging-related phenotypes and modifiable lifestyle factors were evaluated using linear and logistic regression models in a larger, non-overlapping sample of 5,957 WCHAC participants. Furthermore, we employed mediation analysis to explore the mediating effects of Met-TL between lifestyle factors and aging-related diseases.

RESULTS: We identified a plasma metabolite signature comprising 26 metabolites explaining 17.5% of TL variance. Met-TL significantly associated with aging-related phenotypes (44 Bonferroni-corrected associations) and modifiable lifestyle factors (4 associations). Notably, Met-TL showed robust associations with steatohepatitis and hepatic biomarkers. Mediation analysis revealed that Met-TL partially explained the protective association between healthy lifestyle and steatohepatitis, with a mediation proportion of 8.2%.

CONCLUSION: These findings provide novel insights into the metabolic profile of TL in older adults. The Met-TL may serve as a promising biomarker of cellular aging, particularly in identifying liver dysfunction, facilitating the development of personalized aging monitoring and anti-aging intervention strategies.

PMID:42663576 | DOI:10.1093/gerona/glag209

Ann Am Thorac Soc. 2026 Aug 28:aaoag264. doi: 10.1093/annalsats/aaoag264. Online ahead of print.

ABSTRACT

INTRODUCTION: Fall-related injuries are a common cause of morbidity and impaired quality of life among patients with severe respiratory disease. Use of long-term oxygen therapy (LTOT) may be associated with a further increased risk.

METHODS: This was a longitudinal study of patients starting LTOT between 2006 and 2023 in the Swedish DISCOVERY cohort. Rates of healthcare contact due to three types of fall-related injuries (distal radius fracture, hip fracture, and skull trauma) were compared to those of age- and sex-matched population controls using nationwide registries. For patients on LTOT, pre-identified potentially predictive factors were analyzed against a composite outcome of any fall-related injury using Cox and Fine-Gray regression, independently, adjusting for age, sex and Charlson Comorbidity Index (CCI), and in a joint model adjusting for all predictive factors.

RESULTS: A total 16,915 patients with LTOT (mean age 76±9 years, 57% female, 63% underlying COPD) and an equal number of matched controls were included. Compared with controls, LTOT patients had increased overall rates of both hospitalizations (15.5 vs 7.3 per 100 patient-years) and outpatient (16.9 vs 13.6 per 100 patient-years) healthcare contacts due to fall-related injuries, driven by hip fractures and skull trauma, whereas distal radius fractures were more common among patients without LTOT. The strongest independent predictive factors for fall-related injury during LTOT were history of previous fall-related injury (HR1.8; 95% confidence interval 1.7-2.0) and increased CCI. The overall predictive capability of the model was poor (C-statistic 0.65).

CONCLUSION: Patients on LTOT have a high rate of health care contacts due to hip fractures and skull trauma, but whether this increase is caused by use of oxygen equipment or underlying frailty remains unknown. While individual falls were difficult to predict, indicators such as previous fall injury and comorbidities, may inform optimized follow-up and interventions aimed at mitigating risk.

PMID:42663560 | DOI:10.1093/annalsats/aaoag264

Ann Plast Surg. 2026 Aug 28. doi: 10.1097/SAP.0000000000004719. Online ahead of print.

ABSTRACT

BACKGROUND: Acute compartment syndrome (ACS) is a time-sensitive diagnosis, with mortality rates as high as 15%. Diagnosis relies on clinical evaluation and intracompartmental pressure (ICP) measurements, which are only 68% accurate. Microdialysis has been shown to be reliable in detecting flap ischemia before clinically evident. Therefore, we hypothesized that intramuscular (IM) microdialysis could detect early ACS with high diagnostic test accuracy (DTA). Given IM perforators supply overlying skin, we further hypothesized that subcutaneous (SC) biomarkers closely correlate with IM metabolic changes and can detect ACS in a swine model.

METHODS: Eleven Yorkshire swine (male, ~50 kg) were used to model tourniquet-induced ACS in the bilateral anterior hind limbs (n=22). ACS was induced for 6 hours. Microdialysis probes were placed in both IM and SC tissue compartments to collect interstitial fluid for analysis of glucose, pH, and lactate. Tissue oxygenation (SrO2) and hindlimb temperature were also monitored. Maximal diagnostic test accuracy and correlation coefficients were calculated for these metrics.

RESULTS: ICP increased immediately after tourniquet inflation [preinflation: 15.6±4.7 mm Hg vs. postinflation: 53.0±38.2 mm Hg (P=0.0012)]. IM glucose decreased significantly at hour 2, while SC glucose decreased significantly at hour 3. SC glucose below 6.6 mg/dL had a DTA of 75%. Both IM and SC pH decreased significantly at hour 2. SC pH below 7.17 had a DTA of 78%. IM and SC lactate increased over the course of the experiment, but these changes were not statistically significant. SC lactate above 3.85 mg/dL had a DTA of 70%. SrO2 decreased significantly immediately after tourniquet inflation (DTA 100% below 58.5%), and hindlimb temperature decreased significantly within 30 minutes (DTA 99.6% below 27.8 °C). SC and IM glucose had the closest correlation (R2=0.931), followed by pH (R2=0.911), while lactate showed a less reliable correlation (R2=0.667).

CONCLUSIONS: In a porcine model of ACS, SC biomarkers closely correlate with IM biomarkers and exhibit a high DTA with pH, having the highest accuracy. SrO2, and surface temperature also decreased rapidly and significantly. Future research should investigate these modalities in pilot clinical trials.

PMID:42663554 | DOI:10.1097/SAP.0000000000004719

Am J Manag Care. 2026 Aug;32(8):464-468. doi: 10.37765/ajmc.2026.90002.

ABSTRACT

OBJECTIVES: Regular use of nonsteroidal anti-inflammatory drugs (NSAIDs) poses a risk to patients with chronic kidney disease (CKD), heart failure (HF), and hypertension (HTN). We evaluated changes in NSAID utilization among a large cohort of Virginia patients with CKD, HF, and/or HTN during the COVID-19 pandemic and assessed variation by patient demographic characteristics.

STUDY DESIGN: Quasi-experimental difference-in-differences approach.

METHODS: Using claims from the Virginia All-Payer Claims Database, we identified NSAID prescriptions dispensed to patients with CKD, HF, and/or HTN during the years 2019-2021. We applied Poisson regression to assess the impact of the COVID-19 pandemic (March 1, 2020- December 31, 2021) on NSAID utilization rates, stratifying incidence rate ratios (IRRs) by rurality, sex, and age.

RESULTS: Extrapolated to the statewide population, approximately 3.8 million NSAID prescriptions were dispensed to Virginians with CKD, HF, and/or HTN between 2019 and 2021. Utilization rates declined by 23% during the first 2 years of the pandemic, were greater in rural vs urban areas (IRR, 1.594; 95% CI, 1.408-1.803) and among those aged 40 to 64 years, 65 to 79 years, and 80 years and older vs those aged 18 to 39 years (40-64 years: IRR, 6.366; 95% CI, 5.979-6.778; 65-79 years: IRR, 6.980; 95% CI, 6.568-7.417; ≥ 80 years: IRR, 5.223; 95% CI, 4.772-5.715); and were lower among men than women (IRR, 0.779; 95% CI, 0.758-0.800). The pandemic impacted rural and urban areas and women and men similarly but was associated with lower NSAID utilization among the 3 older age groups vs those aged 18 to 39 years (40-64 years: IRR, 0.869; 95% CI, 0.812-0.931; 65-79 years: IRR, 0.788; 95% CI, 0.733-0.847; ≥ 80 years: IRR, 0.769; 95% CI, 0.709-0.833).

CONCLUSIONS: Despite a modest decline during the first 2 years of the pandemic, NSAID use remains prevalent among patients with CKD, HF, and/or HTN, especially in rural areas and among women. Results highlight the need for tailored deprescribing efforts.

PMID:42663549 | DOI:10.37765/ajmc.2026.90002

Am J Manag Care. 2026 Aug;32(8):456-462. doi: 10.37765/ajmc.2026.90001.

ABSTRACT

OBJECTIVES: Medicare Advantage (MA) Star Ratings influence bonus payments and health plan enrollment. Current approaches to accounting for enrollee social risk may not fully capture differences in beneficiary populations. This study assessed how MA contract performance rankings for statin receipt and adherence change under a social risk-weighted scoring approach.

STUDY DESIGN: Cross-sectional analysis of 2019 MA encounter, prescription drug, and enrollment data for 165 MA contracts.

METHODS: Contract-level statin receipt and adherence scores were calculated for disability and dual-eligibility subgroups and aggregated using empirically derived weights from a constrained optimization framework that equalized each subgroup’s contribution to overall contract performance. Ordered logistic regression assessed associations between contract characteristics and weighted performance.

RESULTS: Social risk-weighted scoring reclassified 24.2% of contracts for statin receipt and 20.6% for adherence relative to unweighted scoring. For statin receipt, 11.5% of contracts moved up, 12.7% moved down, and 75.8% were unchanged; for adherence, 7.3% moved up, 13.3% moved down, and 79.4% were unchanged. Under the weighted approach, higher disability prevalence remained associated with lower performance ratings even after weighting: Each 1-percentage point (PP) increase in disability prevalence corresponded to a 0.7-PP higher probability of receiving 3 or fewer stars for statin receipt and a 1.3-PP higher probability for adherence. Larger contracts also had lower predicted probabilities of receiving 4 stars, decreasing by 3.4 PPs for receipt and 3.8 PPs for adherence per 1-unit increase in log enrollment.

CONCLUSIONS: Social risk weighting rebalanced contract rankings but did not consistently improve ratings for high-risk plans. Remaining variation may reflect differences in quality or unmeasured factors.

PMID:42663548 | DOI:10.37765/ajmc.2026.90001

Am J Manag Care. 2026 Aug;32(8):444-451. doi: 10.37765/ajmc.2026.90000.

ABSTRACT

OBJECTIVE: To assess whether Medicare Advantage (MA) beneficiaries in socially vulnerable counties face more restrictive prior authorization (PA) requirements.

STUDY DESIGN: Cross-sectional analysis of 2945 US counties in 2022.

METHODS: The primary outcome was the mean percentage of Medicare-covered service categories requiring PA across all MA plans in a county, adjusted for service mix and plan enrollment and derived from the CMS MA benefit, landscape, and enrollment files. Secondary outcomes included county-level PA rates for selected service categories, the number of plans with more vs less restrictive PA policies, and mean monthly premiums. The exposure was the county-level Social Vulnerability Index (SVI) subdomains (socioeconomic status, household characteristics, racial/ethnic minority status, housing and transportation), categorized into deciles. Unadjusted linear regression models were used, weighted by county MA enrollment.

RESULTS: Counties in the highest vs lowest SVI decile in the socioeconomic domain had overall PA rates that were 7.2 percentage points (PP) higher ( P < .001), with the largest gap for psychiatric services (16.9 PP; P < .001). Conversely, mean monthly premiums declined across socioeconomic deciles, from $29 in the first decile to $8 in the 10th ( P < .001). Total plan counts were stable across deciles, but the composition differed: The most vulnerable counties offered 5 fewer plans with less restrictive PA policies and 4 more plans with more restrictive policies (both P < .001).

CONCLUSIONS: MA beneficiaries in socially vulnerable counties face more restrictive PA requirements, especially for psychiatric services. These disparities may compound existing structural barriers and warrant consideration in future MA policy reforms.

PMID:42663547 | DOI:10.37765/ajmc.2026.90000

J Vector Borne Dis. 2026 Aug 28. doi: 10.4103/jvbd.jvbd_105_26. Online ahead of print.

ABSTRACT

BACKGROUND OBJECTIVES: Dengue is a major vector-borne disease in tropical and subtropical regions, including Indonesia, where recurrent outbreaks remain a significant public health concern. Understanding the spatial and temporal distribution of dengue transmission is essential for effective surveillance and targeted control strategies. This study aimed to map the spatio-temporal hotspots of dengue transmission in Tasikmalaya City, West Java, Indonesia, using Geographic Information Systems (GIS) and spatial statistical analysis.

METHODS: Village-level spatial analyses were conducted using reported dengue cases from the complete calendar year of 2022 and 279 cases reported between January and September 2023. Of the 279 cases reported in 2023, 275 had valid residential coordinates and were included in the space-time cluster analysis. The space-time analysis was based on symptom onset dates ranging from 27 December 2022 to 30 September 2023. Global Moran’s I, Local Indicators of Spatial Association (LISA), bivariate LISA, and the spatial scan statistic implemented in SaTScan were used to assess the spatial distribution and spatio-temporal clustering of dengue cases.

RESULTS: Spatial clustering of dengue cases was identified in several urban villages, particularly around Cipedes and Tugujaya. Bivariate LISA revealed significant spatial co-occurrence between high dengue incidence and high population density. Spatio-temporal analysis detected three statistically significant clusters during 2023, indicating that dengue transmission was concentrated in specific geographic areas during distinct periods rather than being uniformly distributed over time.

INTERPRETATION CONCLUSION: The findings highlight distinct spatio-temporal hotspots of dengue transmission and emphasize the role of population density and seasonal factors in shaping dengue risk. Spatial mapping and cluster detection can support targeted vector control and public health interventions.

PMID:42663540 | DOI:10.4103/jvbd.jvbd_105_26

Traffic Inj Prev. 2026 Aug 28:1-7. doi: 10.1080/15389588.2026.2709024. Online ahead of print.

ABSTRACT

OBJECTIVE: The Veterinary Abbreviated Injury Scale (V-AIS) was created to mirror the human AIS and address a critical gap in retrospective veterinary trauma analysis. Dogs struck by a vehicle or injured inside a vehicle have the highest mortality rates among cases presenting to Veterinary Trauma Centers (VTC). Improved understanding of injury mechanisms, patterns, and severity in canine vehicular trauma is necessary to inform development of scientifically validated restraint systems and other vehicle safety features for canine occupants.

METHODS: The Veterinary Committee on Trauma (VetCOT) Registry was queried for canine patients injured while inside a vehicle between 2013 and 2024, yielding 268 cases. Descriptive statistics for patient demographics were performed on all registry cases. Available medical records were further abstracted for a subset of 19 cases, in which all injuries were coded using V-AIS v1.0. Case details were extracted when available, noting canine position in the vehicle and crash specifics. Additional descriptive statistics for injury characteristics, anatomic region, severity, and outcome were performed for the subset.

RESULTS: Among 268 registry cases, 91% of dogs (n = 244) survived to hospital discharge, with euthanasia accounting for 83.3% of the 24 non-survivors. Patient weight class was not significantly associated with overall survival (p = 0.48). Non-survivors presented with significantly higher median Animal Trauma Triage (ATT) scores (6.0) compared to survivors (1.0) (p < 0.001). In a 19-case subset coded with V-AIS (63 total injuries), anatomical injury distribution varied significantly by weight class (p < 0.001). Large dogs (>30kg) sustained primarily appendicular trauma (75.8%), medium dogs (10.1-30kg) sustained predominantly central body trauma (61.5%), and small dogs (≤10kg) sustained a mixture of central (47.1%) and axial (47.1%) trauma. Clinically significant injuries (V-AIS Severity ≥3) were exclusively confined to the abdomen (p = 0.02), and all fatalities occurred in dogs with internal organ trauma.

CONCLUSIONS: Application of V-AIS enables detailed characterization of canine injury severity, anatomic distribution, and mechanism of injury in vehicle crashes. Preliminary findings suggest that dog size influences injury pattern, while internal organ injury is strongly associated with adverse outcomes. Expanded application of V-AIS within veterinary trauma registries will provide the automotive industry with actionable, severity-stratified data necessary to support development of evidence-based canine restraint systems and vehicle safety measures, improving injury prevention for canine occupants.

PMID:42663521 | DOI:10.1080/15389588.2026.2709024

Chaos. 2026 Aug 1;36(8):083153. doi: 10.1063/5.0304782.

ABSTRACT

In this work, we focus on different statistical measures to uncover the complexity of extreme events in various nonlinear dynamical systems. Notably, the effectiveness of the variance-based measure, estimated from the mean recurrence time and entropy, reveals a clear distinction between extreme and non-extreme events. Additionally, the variance measure clearly highlights the critical transition point of unforeseen, rare, large-amplitude dynamics. Our investigation involved models from various disciplines, including the Brusselator chemical oscillator, CO2 laser, superconducting quantum interference devices, and a coupled neuron model. Deeper insights into the complexity of extreme events offer significant value for advancing early prediction methods.

PMID:42663518 | DOI:10.1063/5.0304782

Rev Sci Instrum. 2026 Aug 1;97(8):081305. doi: 10.1063/5.0332420.

ABSTRACT

Time-lapse scanning tunneling microscopy (STM) captures how surface structures evolve in real time, but extracting quantitative kinetics from the resulting image series is hampered by drifts and the labor of frame-by-frame processing. We present AutoSPy, a modular software package that automates the conversion of raw time-lapse STM image stacks into analyzable time-series measurements. AutoSPy aligns consecutive frames using scale-invariant feature transform feature matching with RANSAC-based outlier rejection and an affine registration model, correcting not only translational drift but also drift-induced rotation and anisotropic distortion. An adaptive flattening routine combining Sobel gradient detection, Otsu thresholding, region growing, and least-squares plane fitting standardizes background subtraction across large datasets. For analysis, it integrates the Segment Anything Model 2 to segment and track user-selected features across registered frames, yielding trajectories, displacement statistics, and time-dependent area changes for clusters and vacancies with minimal manual input. AutoSPy, thus, provides a generalizable toolkit for quantitative studies of dynamic surface evolution and kinetics under working conditions.

PMID:42663515 | DOI:10.1063/5.0332420