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Obstructive sleep apnea (OSA) is associated with cognitive decline, but short-term studies show limited cognitive benefits of its treatment with continuous positive airway pressure (CPAP). We examined whether longer follow-up exhibits greater cognitive differences associated with CPAP use. We analyzed 777 participants from the 2011 National Health and Aging Trends Study (NHATS) with linked Medicare claims, with one or more claims for OSA and no baseline cognitive impairment. CPAP treatment was defined by one or more CPAP claims. Cognitive trajectories from 2011 to 2021 were estimated using a factor score derived from annual cognitive performance assessments and compared by CPAP treatment status using adjusted generalized linear mixed models. Cognitive performance declined over follow-up. CPAP-treated participants declined by -0.03 standard deviation (SD) units per year (95% confidence interval [CI]: -0.04, -0.02). Untreated participants experienced a 69% faster decline (CPAP-by-time interaction: -0.02; 95% CI: -0.04, -0.001). CPAP therapy may slow cognitive decline in older adults with OSA.

Cancer remains the leading cause of mortality in Japan, creating significant demand for high-quality real-world evidence to support clinical research and decision making. This study aims to provide a comprehensive overview of oncology studies using real-world data (RWD) in Japan, assessing the suitability of these data sources for oncology research. Searches were conducted in PubMed, Ichushi-Web, and Google Scholar for studies published from 1 January 2020 to 28 February 2025. Eligibility criteria focused on retrospective observational studies utilizing readily available RWD databases. The availability of information on patient demographics, clinical characteristics, genomic information, treatment patterns, and clinical outcomes, as well as data source limitations reported by authors, was extracted and analyzed. Of 484 studies screened, 121 met the eligibility criteria. The majority utilized administrative claims data (52%), followed by registries (44%) and electronic health record (EHR)-derived data (6%). Limitations varied by data source. Claims data lacked clinical detail, resulting in challenges in accurate study cohort identification and outcomes research; registries contained deep genomic information but had high clinical data missingness and restricted cohorts; EHR-derived data provided detailed clinical insights but were less established in scale. This scoping review highlights the strengths and limitations of Japanese RWD sources, revealing the frequent use of claims data in oncology research despite their limited clinical granularity. Future research should increasingly leverage clinically rich and longitudinal data sources, particularly EHR-derived datasets, to enable more precise cohort identification and capture meaningful clinical outcomes, better supporting clinical and research needs in Japanese oncology.

Dual antiplatelet therapy (DAPT) after percutaneous coronary intervention (PCI) reduces thrombotic risk in acute coronary syndrome (ACS) but may increase bleeding, especially in chronic kidney disease (CKD). This study evaluated the impact of different DAPT durations on cardiovascular and bleeding outcomes in ACS patients with and without CKD. Using the Taiwan National Health Insurance Research Database (2001-2018), patients ≥20 years with ACS who underwent PCI and received clopidogrel plus aspirin for ≥1 month were analyzed. Primary outcomes were cardiovascular events and bleeding events. Subgroup analysis was conducted by CKD status, which was defined using claims-based International Classification of Diseases, Ninth and Tenth Revision (ICD-9/ICD-10) diagnostic codes. Among 4,800 patients with ACS identified (median age: 62 years; 77% male), there were no significant differences in cardiovascular events across DAPT duration groups. No associations between DAPT duration and cardiovascular outcomes were identified in patients with or without CKD. However, DAPT duration ≥7 months was associated with a higher incidence of other major bleeding in patients with CKD (adjusted odds ratio [aOR] = 29.7, 95% confidence interval [CI]: 1.80-491.05, p = 0.018). In patients undergoing PCI for ACS, no clear association was observed between longer DAPT duration and reduced cardiovascular events. In prespecified subgroup analyses, prolonged DAPT was associated with a higher incidence of bleeding events among patients with claims-defined CKD; however, this finding should be interpreted as exploratory given the observational design and low event rates. These results highlight the importance of individualized decision-making regarding DAPT duration, particularly in patients with increased bleeding susceptibility.

Patient narratives are foundational to diagnosis, yet clinicians frequently and unintentionally distort, minimize, or reinterpret these narratives during clinical encounters. These distortions - termed patient narrative distortion - are unmeasured contributors to diagnostic error [G.D. Schiff, O. Hasan, S. Kim, R. Abrams, K. Cosby, B.L. Lambert et al., Diagnostic error in medicine: analysis of 583 physician-reported errors, Arch Intern Med 169 (2009) 1881-1887; P. Croskerry, The importance of cognitive errors in diagnosis and strategies to minimize them, Acad Med 78 (2003) 775-780; H. Singh, A.N.D. Meyer, E.J. Thomas, The frequency of diagnostic errors in outpatient care, BMJ Qual Saf 23 (2014) 727-731; and M.L. Graber, N. Franklin, R. Gordon, Diagnostic error in internal medicine, Arch Intern Med 165 (2005) 1493-1499], emotional harm [J. Conway, F. Federico, K. Stewart, M.J. Campbell, Respectful Management of Serious Clinical Adverse Events, IHI Innovation Series White Paper, IHI, Cambridge, MA, 2011], and inequity [E.N. Chapman, A. Kaatz, M. Carnes, Physicians and implicit bias: how it affects clinical decision making, Acad Med 88 (2013) 354-360; and M. Marmot, R.G. Wilkinson (Eds.), Social Determinants of Health, 2nd ed., Oxford University Press, Oxford, 2005]. No existing safety tool captures the fidelity with which clinicians preserve patient stories [T. Greenhalgh, B. Hurwitz (Eds.), Narrative Based Medicine: Dialogue and Discourse in Clinical Practice, BMJ Books, London, 1998; and W. Levinson, D.L. Roter, J.P. Mullooly, V.T. Dull, R.M. Frankel, Physician-patient communication: the relationship with malpractice claims, JAMA 277 (1997) 553-559]. The stages at which narrative distortion emerges are illustrated in Figure 1. The objective of this article was to define patient narrative distortion as a measurable construct, develop a five-domain taxonomy, propose a scoring system (PNDI), and outline a workflow and validation strategy for clinical use. We conducted iterative conceptual modeling and structured synthesis of the diagnostic-safety and narrative-medicine literatures [G.D. Schiff, O. Hasan, S. Kim, R. Abrams, K. Cosby, B.L. Lambert et al., Diagnostic error in medicine: analysis of 583 physician-reported errors, Arch Intern Med 169 (2009) 1881-1887; P. Croskerry, The importance of cognitive errors in diagnosis and strategies to minimize them, Acad Med 78 (2003) 775-780; H. Singh, A.N.D. Meyer, E.J. Thomas, The frequency of diagnostic errors in outpatient care, BMJ Qual Saf 23 (2014) 727-731; and M.L. Graber, N. Franklin, R. Gordon, Diagnostic error in internal medicine, Arch Intern Med 165 (2005) 1493-1499] to identify core distortion modes, develop domain definitions, item-level anchors, and scoring thresholds. We propose a multi-phase validation plan including content validity, inter-rater reliability, construct validity, criterion validity, and responsiveness. The PNDI taxonomy includes five domains: Narrative Completeness Distortion, Meaning Substitution Distortion, Salience Distortion, Context Stripping Distortion, and Bias-Driven Distortion [E.N. Chapman, A. Kaatz, M. Carnes, Physicians and implicit bias: how it affects clinical decision making, Acad Med 88 (2013) 354-360]. Each domain includes 0-3 severity anchors and real-world clinical examples. The total PNDI score ranges from 0-15, with interpretation bands for narrative integrity and safety risk. Encounter-level, unit-level, and organizational-level workflows for implementation are outlined. The five-domain PNDI taxonomy is shown in Figure 2. PNDI operationalizes narrative integrity as a measurable dimension of diagnostic safety [The Joint Commission, National Patient Safety Goals: Improving Diagnosis in Health Care 2024-2026, The Joint Commission, Oakbrook Terrace, IL, 2024]. It provides clinicians, educators, and safety teams with a practical tool to detect narrative loss, reduce diagnostic error [G.D. Schiff, O. Hasan, S. Kim, R. Abrams, K. Cosby, B.L. Lambert et al., Diagnostic error in medicine: analysis of 583 physician-reported errors, Arch Intern Med 169 (2009) 1881-1887; P. Croskerry, The importance of cognitive errors in diagnosis and strategies to minimize them, Acad Med 78 (2003) 775-780; H. Singh, A.N.D. Meyer, E.J. Thomas, The frequency of diagnostic errors in outpatient care, BMJ Qual Saf 23 (2014) 727-731; and M.L. Graber, N. Franklin, R. Gordon, Diagnostic error in internal medicine, Arch Intern Med 165 (2005) 1493-1499], and strengthen patient trust [W. Levinson, D.L. Roter, J.P. Mullooly, V.T. Dull, R.M. Frankel, Physician-patient communication: the relationship with malpractice claims, JAMA 277 (1997) 553-559].

This study aimed to identify demographic and clinical factors associated with advanced-stage pressure injury (PI) classification among hospitalised patients diagnosed with PIs using the Health Insurance Review and Assessment Service (HIRA) patient sample database. This secondary data analysis was approved by the Institutional Review Board of K University (IRB No. 2020-0266). Public data were analysed using SAS Enterprise Guide on a designated computer, and all procedures complied with data security and confidentiality requirements. A secondary analysis was conducted using the HIRA patient sample database from 2017 to 2019. Patients diagnosed with pressure injuries were classified into a mild-stage group (Stages 1-2) and an advanced-stage group (Stages 3-4). Multivariable logistic regression analysis was performed to identify factors associated with advanced-stage pressure injury classification (Stage 3-4 vs. Stage 1-2), and odds ratios (ORs) with 95% confidence intervals (CIs) were estimated. Male patients had higher odds of being classified as having advanced-stage pressure injuries than female patients (OR&#x2009;=&#x2009;1.25). The odds of advanced-stage pressure injury classification increased by 1.02 for each one-year increase in age and by 1.02 for each additional day of hospitalisation. Patients with urinary incontinence and malnutrition had 3.32-fold and 2.76-fold higher odds, respectively, of being classified as having advanced-stage pressure injuries than those without these conditions (p&#x2009;<&#x2009;0.001). Sex, age, length of hospital stay and specific comorbidities were significantly associated with advanced-stage pressure injury classification among hospitalised patients with pressure injuries. Urinary incontinence and malnutrition showed particularly strong associations with advanced-stage classification. These findings may support the early identification of patients who are more likely to present with advanced-stage pressure injuries and inform targeted assessment and management strategies in clinical practice. Because this study was based on cross-sectional administrative claims data, the findings should be interpreted as associations with advanced-stage classification rather than evidence of temporal progression or causation. This study utilised secondary administrative data from a nationally representative sample provided by the Health Insurance Review and Assessment Service (2017-2019). No patients or members of the public were directly involved in the design or conduct of this study because the analyses were based on de-identified administrative claims data.

Altered-state phenomenology around ketamine may relate to longer-term changes in imaginal processes, but observations across routine care are scarce. We report an educational case focusing on pre-defined dream motifs over time, without making treatment efficacy claims. A 48-year-old Japanese man with severe chronic primary low back pain reported dreams during insight-oriented psychotherapy from 2009 to 2025; over 360 narratives were contemporaneously documented. In 2014, he received five low-dose outpatient intravenous ketamine infusions (15 mg; 0.23 mg/kg; first 20 min, then 30 min; no premedication) and described a void-like dissociative state during the first session. Using a pre-specified codebook, two raters (treating clinician and external psychiatrist) independently coded an ID-based, period-stratified random subset of 50 dreams after re-ordering and masking of period labels for three primary motifs (obstruction, fear, anger) plus a descriptive social-interaction/role-completion motif. Obstruction decreased from pre- to post-ketamine periods in both raters (treating clinician: 6/9 vs 4/30; external psychiatrist: 6/9 vs 7/30). In the double-labelled subset, the social-interaction/role-completion motif was labelled more often post- than pre-ketamine by both raters (2/9 pre; 10/30 and 11/30 post). Across the observation window that included outpatient ketamine infusions in 2014, dream content shifted from recurrent obstruction toward imagery of movement, interpersonal engagement, and everyday role completion (illustrated by selected de-identified dream narratives; Table&#xa0;5). These single-patient, hypothesis-generating observations describe ketamine-associated void-like phenomenology and longitudinal dream-content change without making efficacy claims. In insight-oriented outpatient ketamine care, clinicians may prepare patients for possible dissociative/dream-like experiences, invite brief narrative documentation, and offer post-session integration while maintaining standard physiological monitoring.

Antimicrobial resistance (AMR) is a global health crisis shaped by complex ecological and evolutionary processes that often occur in polymicrobial communities. Metagenomics enables culture-independent profiling of microbial DNA directly from clinical or environmental samples, providing an unparalleled view of community composition, resistome content, and the mobile genetic elements that drive horizontal gene transfer (HGT). Yet, a recurring challenge is that metagenomic detection of antibiotic-resistance genes does not automatically translate into a mechanistic understanding of resistance phenotypes, nor does it replace culture-based functional validation. Here, we synthesize how modern metagenomics supports AMR research across three linked questions: (i) what resistance determinants are present and how do they change across time and space, (ii) which hosts and mobile genetic elements carry these determinants, and how gene flow can be inferred, and (iii) what evidence is required to move from "resistance potential" to robust mechanistic claims. We emphasize practical design principles (sampling, controls, and contamination management), analytical choices (database and parameter effects), and recent advances, including long-read sequencing for resolving antibiotic-resistance genes context, and rapid clinical metagenomic sequencing for time-sensitive decision support. We propose an evidence ladder for mechanistic inference that integrates metagenomics with targeted assays and culture-dependent experiments. Beyond synthesizing recent advances, this review provides operational tools for critical appraisal and study design: an evidence ladder for mechanistic inference, a decision-gated workflow that ties metagenomic outputs to allowable claim language, a minimum reporting checklist aligned to evidence strength, and a "pitfall &#x2192; consequence &#x2192; fix" guide to reduce over-interpretation. To support a more comprehensive, forward-looking view, we also summarize emerging directions that are rapidly reshaping AMR metagenomics-multi-omics integration, single-cell, and epigenetic linkage strategies, CRISPR-enabled enrichment/depletion, and AI-assisted discovery/mining-and clarify where these advances strengthen (or do not strengthen) mechanistic claims within the same evidence ladder.

Electronic health record (EHR) data discontinuity, defined as receiving care outside of a particular EHR system, may cause misclassification of study variables. We aimed to: (1) quantify misclassification across levels of EHR data discontinuity and identify an optimal continuity threshold, (2) develop a machine learning (ML) model to predict EHR continuity and optimize fairness across racial and ethnic groups, and (3) externally validate the EHR continuity prediction model using an independent dataset. We used linked OneFlorida+ EHR-Medicaid claims data for model development and Research Action for Health Network (REACHnet) EHR-Louisiana Blue Cross Blue Shield (LABlue) claims data for external validation. A Harmonized Encounter Proportion Score (HEPS), adapted from prior continuity metrics, was applied to quantify patient-level EHR data continuity and the impact on misclassification of 42 clinical variables. Machine learning models were trained using routinely available demographic, clinical, and healthcare utilization features derived from structured EHR data. Higher EHR data continuity was associated with lower rates of misclassification. A HEPS threshold of approximately 30% effectively distinguished patients with sufficient data continuity. Machine learning models demonstrated strong performance in predicting high continuity (area under the receiver operating characteristic curve [AUROC]&#x2009;=&#x2009;0.77). Fairness assessments showed bias against Hispanic group, which was substantially improved following bias mitigation procedures. Model performance remained robust and fair in the external validation. Our study offers a practical metric for quantifying data continuity in EHR networks. The current ML model incorporating EHR-routinely collected information can accurately identify patients with high care continuity. We developed a generalizable data-continuity classification tool that can be easily applied across EHR systems, strengthening the rigor of EHR-based research.

The proportion of mothers older than 35 years is increasing; however, research examining the age at which pregnancy is considered high risk across different races and countries is limited. Therefore, this study aimed to determine the cut-off age at which adverse obstetric outcomes significantly increase by investigating age-specific incidence rates of major adverse obstetric outcomes in Republic of Korea (South Korea). We analyzed the Korean National Health Insurance claims database between 2015 and 2021, focusing on women with obstetric complications classified using the International Classification of Diseases, Tenth Edition. The maternal cut-off age was defined as the age at which the outcome was most predictive in receiver operating characteristic curve analysis. Multivariate logistic regression was used to estimate the adjusted odds ratio (OR) and 95% confidence interval (CI) for the association between maternal age and adverse obstetric outcomes. The study included 1,862,393 women with singleton pregnancies. Of these, 33.67% were aged &#x2265; 35 years and 5.07% were aged &#x2265; 40 years. The incidence of adverse obstetric outcomes increased linearly and positively with maternal age. The maternal cut-off age, determined using receiver operating characteristics analysis, was 35 years for pregnancy-induced hypertension (PIH), 33 for gestational diabetes mellitus (GDM), 33 for placenta previa, 32 for placental abruption, 34 for preterm delivery, and 34 for low birth weight (LBW). In multivariate analyses, adjusted OR revealed adverse obstetric outcomes: PIH (OR, 1.29; 95% CI, 1.27-1.32), GDM (OR, 1.73; 95% CI, 1.72-1.75), placenta previa (OR, 1.81; 95% CI, 1.78-1.85), placental abruption (OR, 1.30; 95% CI, 1.24-1.36), preterm delivery (OR, 1.32; 95% CI, 1.29-1.34), and LBW (OR, 1.33; 95% CI, 1.31-1.35). For the composite outcome, maternal cut-off age was found to be 33 years (OR, 1.57; 95% CI, 1.56-1.59), with an area under the curve of 0.573. This nationwide study defined the cut-off age for advanced maternal age in Korean women, showing that obstetric risks begin to increase in the early 30s. These population-specific thresholds may help guide clinical practice and improve maternal and perinatal outcomes.

Since the 1970s, the World Health Organization (WHO) has advanced "traditional medicine" as a global policy category for culturally grounded health care. In South America, this framework has encountered a distinct political landscape in which traditional peoples have emerged as collective subjects mobilizing around rights, territorial claims, and expanding conceptions of citizenship. This paper examines how the codification of "tradition" from an identity category into a health regulatory term reconfigures the conditions under which difference can be expressed, claimed, and sustained. Drawing on archival research across 10 South American countries, as well as WHO and United Nations documentation, the study traces how the global framework has been incorporated, requalified, or displaced across distinct national contexts. The analysis reveals a spectrum of regulatory arrangements in which institutional incorporation and the political force of collective difference are not commensurate, ranging from frameworks that engage with the political projects through which traditional peoples have sought to reshape citizenship to those in which "tradition" operates as a market authorization criterion detached from the subjects who sustain it. The codification of tradition into governable categories does not simply extend recognition to those who bear it; it reconfigures the terms under which they can act as political subjects.

Inflammatory bowel disease (IBD) is associated with renal complications, but population-based data on end-stage renal disease (ESRD) are limited. To evaluate the incidence of ESRD and renal transplantation in IBD compared with the general population and to identify predictive factors associated with ESRD in the IBD population. This was a retrospective population-based cohort study using the University of Manitoba IBD Epidemiology Database linked to administrative healthcare data from 1984 to 2023 (12,639 IBD patients matched with 126,180 controls). ESRD was defined as requiring any two claims for outpatient dialysis within a 1-year period. Predictive factors were identified using proportional hazard regression and nested case-control logistic regression analyses. IBD patients had a significantly higher incidence of dialysis (1.48% vs. 0.82%, p&#x2009;<&#x2009;0.0001) and kidney transplantation (0.25% vs. 0.10%, p&#x2009;<&#x2009;0.0001) than controls. IBD was an independent predictor of ESRD (HR&#x2009;=&#x2009;1.53, 95% CI 1.23-1.90), with stronger associations in CD (HR&#x2009;=&#x2009;1.93, 95% CI 1.39-2.68) than UC (HR&#x2009;=&#x2009;1.28, 95% CI 0.96-1.72). Traditional risk factors including diabetes (HR&#x2009;=&#x2009;3.82, 95% CI 3.22-4.53), hypertension (HR&#x2009;=&#x2009;1.91, 95% CI 1.58-2.30), and congestive heart failure (HR&#x2009;=&#x2009;6.37, 95% CI 5.25-7.72) remained strongly predictive. Within the IBD population, oral steroid treatment (OR&#x2009;=&#x2009;2.0, 95% CI 1.06-3.81), allopurinol use (OR&#x2009;=&#x2009;4.06, 95% CI 1.49-11.1) and bowel surgery (OR&#x2009;=&#x2009;2.77, 95% CI 1.51-5.09) significantly predicted dialysis initiation. Persons with IBD have an increased risk of ESRD by nearly 50%, with CD showing a greater risk than UC. Bowel surgery, allopurinol use and oral steroid therapy are important predictors, emphasising the necessity of careful renal monitoring in IBD patients.