Category: Statistics

Phys Rev Lett. 2026 Jun 19;136(24):244001. doi: 10.1103/qf5l-xnln.

ABSTRACT

We adapt the microcanonical framework of equilibrium statistical mechanics to predict the statistics of short linear waves in inhomogeneous moving media. For steady inhomogeneities and background flow, we compute the wave spectrum at any location in the domain based on an ergodic prescription for the action density in phase space, constrained by conservation of absolute frequency. We illustrate the method for shallow-water waves subject to a background flow or to topographic inhomogeneities, and for deep-water surface capillary waves over a background flow, validating the predicted maps of root-mean-square surface elevation and interfacial slope against numerical simulations.

PMID:42412444 | DOI:10.1103/qf5l-xnln

JAMA Netw Open. 2026 Jul 1;9(7):e2621797. doi: 10.1001/jamanetworkopen.2026.21797.

ABSTRACT

IMPORTANCE: Recurrent invasive pneumococcal disease (rIPD) constitutes a clinically relevant proportion of all IPD cases. Improved understanding of these cases can inform priorities for prevention through vaccination.

OBJECTIVE: To describe the incidence of rIPD and associated risk factors in adults with a primary episode of IPD.

DESIGN, SETTING, AND PARTICIPANTS: This population-based, multicenter cohort study was performed during active surveillance for IPD in adults in Calgary and the Toronto-Peel regions of Canada from January 1, 2004, to December 31, 2022. rIPD was defined as IPD occurring 30 days or longer after a primary episode. Canadian reference laboratories performed serotyping; population data were obtained from Statistics Canada and the Alberta Interactive Health Data Application. Data were analyzed from September 3, 2024, to November 28, 2025.

MAIN OUTCOMES AND MEASURES: Incidence of rIPD over time. Risk factors for rIPD were assessed using multivariable logistic regression.

RESULTS: From 2004 to 2022, 7006 adult patients survived a primary episode of IPD, 274 (3.9%) of whom had rIPD. The median age at primary infection in patients with rIPD was 53.6 (IQR, 41.4-66.0) years; 168 patients (61.3%) were male. The incidence rate ratio (IRR) of rIPD compared with primary IPD rate in surveillance populations was highest in the first year after primary IPD (IRR, 152; 95% CI, 124-185). From 5 to 17 years after primary IPD, the IRR was 15 (95% CI, 11-20). Factors associated with recurrent disease included history of stem cell transplant or hematologic cancer (odds ratio [OR], 5.17; 95% CI, 3.35-7.98), HIV infection (OR, 4.47; 95% CI, 2.84-7.04), experiencing homelessness (OR, 1.87; 95% CI, 1.30-2.69), and alcohol use disorder (OR, 1.50; 95% CI, 1.07-2.11). Primary infection with serotype 3 (OR, 0.33; 95%, 0.16-0.67) or serotype 7F (OR, 0.42; 95% CI, 0.21-0.87), and being 65 years or older (OR, 0.55; 95% CI, 0.34-0.90) were associated with reduced odds of rIPD. At the primary episode, 4812 of 5470 patients (88.0%) were eligible for pneumococcal vaccine, and 1344 of 4812 (27.9%) had been vaccinated. Of patients with known vaccine status between the first and second episodes, 167 of 229 (72.9%) were eligible for vaccine and only 37 of 167 (22.2%) received one.

CONCLUSIONS AND RELEVANCE: In this cohort study, the risk of rIPD was higher than the risk of primary IPD throughout 17 years of follow-up. Most patients with primary IPD had indications for pneumococcal vaccine but were unvaccinated. These findings suggest that patients with IPD should be prioritized to receive recommended vaccination doses.

PMID:42412432 | DOI:10.1001/jamanetworkopen.2026.21797

JAMA Netw Open. 2026 Jul 1;9(7):e2622016. doi: 10.1001/jamanetworkopen.2026.22016.

ABSTRACT

IMPORTANCE: Opioid prescribing has decreased in the US for more than a decade. However, less is known about how prescribing trends differ by prescriber specialty and separately for short-term and long-term opioid prescribing for which the indications, clinical decision-making, and potential for harm vary substantially.

OBJECTIVE: To characterize opioid analgesic prescribing trends in the US between January 1, 2010, and December 31, 2024, by prescriber specialty, analyzing short-term and long-term opioid use episodes separately.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used administrative claims data for commercially insured and Medicare Advantage patients (aged ≥65 years and <65 years with long-term disability) with at least 90 days of enrollment in medical and prescription coverage. Statistical analysis was performed from May 2025 to September 2025.

MAIN OUTCOMES AND MEASURES: Prescribing volume, daily dose, and prescription duration.

RESULTS: The study identified 110 288 218 opioid fills by 14 959 612 patients during the 15-year study period. Among opioid fills, 59.4% were attributed to female patients; the median (IQR) age at opioid fill was 61 (50-71) years. From 2010 to 2024, decreases in opioid prescribing were greater for long-term than short-term opioid use episodes (eg, commercial cohort: 81.3% reduction [from 33.2 fills per 100-person years in 2010 to 6.2 in 2024] and 74.6% reduction [from 36.2 fills per 100-person years in 2010 to 9.2 in 2024]), respectively. The proportion of all opioid fills written by primary care clinicians decreased (eg, Medicare Advantage with disability cohort: from 52.2% to 47.2%), whereas those written by pain medicine specialists increased (eg, Medicare Advantage with disability cohort: from 17.1% to 25.7%). Distinct trends for short-term and long-term opioid use episodes were observed in prescription characteristics, such as daily dose and duration.

CONCLUSIONS AND RELEVANCE: In this cross-sectional study of opioid prescribing trends in the US between 2010 and 2024, decreases in prescribing were greatest in long-term opioid use episodes, and prescribing was increasingly concentrated among pain medicine specialists. These findings suggest the need to balance reductions in opioid prescribing with provision of nonopioid pain treatments and raise concerns about access to care for patients taking opioids for chronic pain management.

PMID:42412429 | DOI:10.1001/jamanetworkopen.2026.22016

NEJM Catal Innov Care Deliv. 2026 Jan;7(1):CAT240478. doi: 10.1056/CAT.24.0478. Epub 2025 Dec 17.

ABSTRACT

Heart failure remains a leading cause of potentially avoidable hospital admissions throughout the United States and a significant driver of unnecessary, avoidable costs within value-based care programs. In a baseline population of 3233 hospital emergency department (ED) visits for heart failure, which occurred over 12 months ending in June 2023 across six WellSpan Health acute care hospitals, 2868 (88.7%) resulted in inpatient admissions. Among those admissions, 2535 (96.0%) were deemed potentially avoidable by the U.S. Centers for Medicare and Medicaid Services (CMS) Prevention Quality Indicator (PQI) 08 heart failure admission quality indicator. Collectively, these admissions totaled US$27,618,825 in potentially avoidable total costs of care. Through process improvements that modified triaging algorithms related to heart failure exacerbations where shortness of breath or lower extremity edema were present, 92.2% of triaged patients with heart failure were managed in an ambulatory setting, with 84.7% avoiding an ED visit within 24 hours. The 12% cost reduction goal was almost achieved just 1 year into the intervention, with an 11.2% reduction in potentially avoidable admissions (CMS PQI 08, a core quality measure) and a US$3,352,248 reduction in total costs of care. This novel intervention executed with Lean management principles was a pragmatic process improvement that can be readily replicated by other systems to reduce unnecessary, avoidable referrals of mild to moderate heart failure exacerbations to hospital EDs.

PMID:42412420 | DOI:10.1056/CAT.24.0478

Transbound Emerg Dis. 2026;2026(1):e5747471. doi: 10.1155/tbed/5747471.

ABSTRACT

Highly pathogenic avian influenza (HPAI) is a devastating viral disease causing substantial economic losses in the poultry industry and posing potential zoonotic risks. Located along the East Asian-Australasian Flyway (EAAF), South Korea has experienced recurrent outbreaks of HPAI since 2003. Following the severe 2016-2017 epidemic, the government implemented strengthened control measures, including restrictions on duck farming and organizational restructuring. This study quantitatively evaluated structural changes in the spatiotemporal patterns and transmission dynamics of HPAI before and after the 2017 policy reinforcement, utilizing a complete dataset covering 12 epidemic waves between 2003 and 2025. Our analysis suggests a distinct shift in HPAI occurrence patterns from large-scale, clustered epidemics to more sporadic occurrences in the post-2017 period. Pre-2017 epidemics, particularly the 5th and 6th waves, exhibited intense spatiotemporal clustering and high transmission potential. Conversely, post-2017 epidemics showed a significant reduction in outbreak density and the disappearance of large-scale clusters. Notably, the 12th wave displayed a more circular diffusion pattern with outbreaks confined to specific regions, suggesting relatively more geographically contained spread. However, despite the overall reduction in scale, high spatiotemporal interaction intensity was intermittently observed, such as in the 11th wave, indicating that residual risks of explosive local transmission persist even during smaller epidemics. These findings suggest that the post-2017 pattern was temporally consistent with strengthened control policies aimed at reducing mechanical connectivity between farms, although this ecological analysis cannot separate policy effects from other time-varying epidemiological and surveillance-related factors. Nevertheless, a decline in case numbers does not necessarily imply the elimination of local transmission risk, highlighting the need to advance precise and risk-based surveillance and response strategies to effectively manage residual risks.

PMID:42412408 | DOI:10.1155/tbed/5747471

JMIR Form Res. 2026 Jul 7;10:e96755. doi: 10.2196/96755.

ABSTRACT

BACKGROUND: Manual chart abstraction from electronic health records is a critical step in clinical outcomes research but is time-intensive and prone to human error. Advances in artificial intelligence (AI), particularly large language models, offer the potential to automate the extraction of structured data from unstructured clinical documentation with improved efficiency and consistency.

OBJECTIVE: This study aimed to evaluate the accuracy and efficiency of an AI-assisted approach for extracting patient-reported outcomes from clinical notes compared with traditional human abstraction.

METHODS: We conducted a retrospective study of 26 patients treated with low-dose radiation therapy for osteoarthritis. Human reviewers abstracted numeric rating scale (NRS; 0-10) pain scores at baseline, the end of treatment, and the first follow-up, and von Pannewitz score (VPS; 0-4) improvement scores at posttreatment time points. A HIPAA (Health Insurance Portability and Accountability Act)-compliant generative pretrained transformer-based AI system was prompted to extract the same end points from clinical notes. Concordance was assessed using exact match rates, the intraclass correlation coefficient for the NRS, and weighted Cohen κ for the VPS. The time required for AI vs manual abstraction was recorded. The AI system was not trained or fine-tuned on study data, and performance was evaluated directly against human abstraction to reflect real-world deployment.

RESULTS: The AI system demonstrated high concordance with human abstraction, achieving an exact match rate of 92% for the NRS (95% CI 84-96; intraclass correlation coefficient=0.96) and 94% for the VPS (95% CI 84-98; κ=0.91). All discrepancies were minor, and no spurious values were generated. The AI system identified 1 clinically relevant data point missed during manual review. Average abstraction time per patient decreased from approximately 30 minutes to 2 minutes, representing time savings of >90%. The system also captured trends in analgesic use, but these results were not statistically significant, including reductions without escalation.

CONCLUSIONS: AI-assisted data abstraction demonstrated high concordance with human review in this single-institution cohort while substantially reducing the time requirements. These findings support the feasibility of AI-assisted abstraction workflows, although further validation across larger and more diverse datasets is needed.

PMID:42412398 | DOI:10.2196/96755

Neurol Ther. 2026 Jul 7. doi: 10.1007/s40120-026-00991-3. Online ahead of print.

ABSTRACT

INTRODUCTION: In the course of their disease, most patients with Parkinson’s disease (PD) will experience OFF episodes, during which symptoms worsen despite symptomatic treatment. Current on-demand treatments for OFF episodes include inhaled levodopa and subcutaneous and sublingual apomorphine, however no head-to-head comparison of these treatments is available. We performed a network meta-analysis (NMA) to provide robust comparative evidence for on-demand OFF episode treatments.

METHODS: Randomized controlled trials assessing OFF episode treatments in patients with PD were identified in a systematic literature review. A feasibility assessment was conducted considering OFF time, Unified Parkinson’s Disease Rating Scale (UPDRS) Part III scores, Patient Global Impression of Change score (PGI-C), and safety outcomes. An NMA was carried out using a random effects model.

RESULTS: Twenty-one trials were identified in the systematic literature review, 11 of which were included in the feasibility assessment and deemed suitable to be included in the NMA. No statistically significant difference in OFF time was observed between patients receiving inhaled levodopa and those receiving subcutaneous apomorphine, and no statistically significant difference in UPDRS Part III scores or probability of PGI-C score improvements, all-cause discontinuation, or adverse events (AEs) were observed between patients receiving inhaled levodopa, subcutaneous apomorphine, or sublingual apomorphine. Subcutaneous apomorphine had significantly higher probability of treatment discontinuation due to adverse events compared to inhaled levodopa (Log odds ratio 20.712; 95% credible interval 1.855, 55.991).

CONCLUSION: Inhaled levodopa demonstrated no statistically significant difference in efficacy with subcutaneous or sublingual apomorphine, however inhaled levodopa had a lower probability of treatment discontinuation due to AEs than subcutaneous apomorphine. These data highlight that inhaled levodopa is a suitable non-invasive and well-tolerated treatment for OFF episodes.

PMID:42412388 | DOI:10.1007/s40120-026-00991-3

Odontology. 2026 Jul 7. doi: 10.1007/s10266-026-01498-x. Online ahead of print.

ABSTRACT

This study aimed to evaluate the clinical safety, informational completeness, and patient-centered language of responses generated by four large language model (LLM)-based systems to standardized periodontal complaint-based queries. Seven standardized symptom-based periodontal queries were developed based on commonly reported patient complaints and submitted in Turkish to Copilot, Gemini, Claude, and ChatGPT. Responses were evaluated using a structured rule-based framework consisting of a Content Coverage Score (CCS), Risk of Harm Score (RHS), and Patient Language Score (PLS). Assessments were performed by two blinded human reviewers and one blinded AI-based evaluator. Human consensus, AI consensus, and combined evaluator scores were calculated. Agreement between evaluators was assessed using intraclass correlation coefficients (ICC), while human-AI differences and inter-model comparisons were analyzed using non-parametric statistical tests. Excellent agreement was observed between human reviewers, repeated AI evaluations, and human-AI consensus scores (ICC range: 0.911-0.925; p < 0.001). No significant difference was found between overall human and AI consensus scores (p = 0.985). Across the four AI systems, no statistically significant differences were observed in CCS or PLS scores in the human, AI, or combined evaluator analyses (all p > 0.05). PLS scores were generally high across models, indicating good linguistic accessibility for patients. No clearly harmful guidance was identified by the human reviewers. Overall, LLM-based systems generated clinically safe, reasonably comprehensive, and generally patient-accessible responses to common periodontal complaint-based queries. Although these systems may serve as supplementary sources of periodontal health information, they cannot replace individualized clinical evaluation and professional dental consultation.

PMID:42412385 | DOI:10.1007/s10266-026-01498-x

Ther Innov Regul Sci. 2026 Jul 7. doi: 10.1007/s43441-026-01012-z. Online ahead of print.

ABSTRACT

The ICH E9(R1) estimands framework requires precise specification of the treatment effects (estimands) a trial is designed to estimate. A recent article by Troxel et al. [1] has advanced a narrow view that only estimands using the treatment-policy strategy are scientifically defensible. In particular, the article recommends that journals adopt a new policy with regard to reporting results from clinical trials, advocating that only results based on the treatment policy strategy should appear in the main body of the paper with estimates based on other strategies relegated to supplementary materials. Treatment-policy estimands target the effect of assignment to treatment and are defined to include outcomes after non-terminal post-randomization events, such as treatment discontinuation or initiation of alternative or rescue medications. Use of this estimand requires that outcome collection continues following these intercurrent events. In the presence of missing data, estimation of effects using the treatment policy strategy typically relies on strong, unverifiable assumptions [2]. While using treatment policy strategies to address all intercurrent events is appropriate for certain scientific objectives, these estimands do not address all clinically relevant questions. Results based on estimands using alternative strategies for primary and key secondary objectives should therefore also be presented in the main body of the published paper when they address important clinical questions that are relevant to patient care or decision-making.

PMID:42412376 | DOI:10.1007/s43441-026-01012-z

Anal Sci. 2026 Jul 7. doi: 10.1007/s44211-026-00940-y. Online ahead of print.

ABSTRACT

Lysine methylation is an important epigenetic modification that regulates chromatin structure and gene expression. However, it is still difficult to distinguish its methylated states without labels at the single-molecule level. In this study, we investigate the discrimination of lysine methylation states using single-molecule tunneling measurements with gold nano-gap electrodes. The conductance decreases stepwise as the number of methyl groups increases, even though density functional theory (DFT) shows that all molecules have almost the same HOMO energy levels. This result suggests that conductance is not determined only by the electronic structure, but also by how the molecule is arranged between the electrodes. Statistical analysis of current signals shows that high-conductance events become less frequent after methylation, indicating fewer strongly coupled configurations. The relationship between current and molecular length also supports that transport depends on variations in molecular configurations. Machine learning analysis achieved an F-score of 0.76 for distinguishing methylated from unmethylated lysine. In contrast, distinguishing between mono-, di-, and trimethylated forms gave a lower F-score of 0.49, reflecting overlap in the signals. These results suggest that single-molecule tunneling currents are sensitive to stepwise lysine methylation states through differences in transient molecular configurations. This work demonstrates the potential of single-molecule tunneling measurements for label-free analysis of epigenetic modifications.

PMID:42412374 | DOI:10.1007/s44211-026-00940-y