Journal of Personalized Medicine

PurposeTo describe the development of - and outcomes from - an institution-level initiative supporting access to innovative genetic medicines information and opportunities. MethodsWe developed and implemented a Genetic Medicines Patient Assessment Pathway for rare genetic conditions at a large public hospital, with multidisciplinary teams collaborating to evaluate a patients molecular and clinical amenability to experimental and/or to-be-developed genetic medicines (primarily nucleic acid therapeutics). A Genetic Medicines Consult Clinic operating in parallel offered no-cost specialized consultations and counseling to families regarding genetic medicines inquiries and Pathway outcomes. We retrospectively reviewed submissions, decisions, and outcomes over a >2-year period. ResultsA total of 63 submissions were reviewed in the Patient Assessment Pathway. Most submissions were classified as eligible or potentially eligible for at least one genetic medicines approach (42/63; 67%). Recommendations generated 87 discrete actions, such as outreach to potential collaborators (n = 28), offering participation in existing research studies (n = 23), or referral to the Consult Clinic (n = 19). Two patients have been approved for therapeutic program initiation or clinical trial enrolment. ConclusionFindings to date support feasibility and high uptake of a structured, multidisciplinary, medical genetics-led model for assessing patient-level opportunities for genetic medicines.

In this work, we investigate the homogeneity of performance in binary classification between the Rotterdam phenotypes and phenotype prediction. For this purpose, a multi-task neural network architecture is designed to improve the prediction accuracy of phenotypes while maintaining the accuracy of binary classification. Using a clinical PCOS dataset which contains unlabeled samples of patients that cannot be attributed to any of the known phenotypes, three models are evaluated: optimized binary Random Forest (RF), six-class weighted class RF, and multi-task neural network (with a common hidden layer and two heads for binary and six-class classifications) optimized by a genetic algorithm. Techniques used for evaluation include ten-fold out-of-fold predictions, paired McNemar tests, bootstrap tests, ablation study, and clustering (Adjusted Rand Index, ARI). Binary RF model reached 90.2% accuracy; however, recall of different phenotypes was significantly unbalanced - from 75.0% of phenotype B to 97.8% of phenotype A. This difference of 22.8 % points was observed (23.3 points) even after excluding phenotype-specific features. While direct phenotype prediction improved recall for common phenotypes, it decreased recall for phenotype B to 43.8% and unclassified cases to 31.5%. Our multi-task model preserved 90.2% binary accuracy and significantly recovered phenotype B recall to 87.5% and unclassified cases to 79.6% (p<0.05). The cluster analysis confirmed the weak correlation between the results and labels (ARI=0.045). The ablation analysis demonstrates that feature selection and class weighting drive this improvement, isolating the specific components responsible for performance gains. We establish that aggregate binary accuracy does not reflect the heterogeneous detection of PCOS phenotypes. Direct phenotype prediction alone redistributes the classification errors, but the multi-task architecture successfully improves the detection of rare phenotypes without compromising binary accuracy. Phenotype-disaggregated evaluations, supported by significance testing and ablation, are essential for clinical classifier research.

Vertical transmission of SARS-CoV-2 is controversial. Owing to the low expression of ACE2 along with TMPRSS2 in placenta, role of secondary receptors becomes significant. In our study we predicted twelve interactors of spike protein expressed in placenta through interactome analysis followed by docking and molecular dynamic simulation. Three interactors of SARS-CoV-2 spike protein were found to be CD147, EGFR and LDLR. Expression at transcriptomic and translational level by real-time PCR and immunohistochemistry respectively was observed in placenta samples obtained from women with COVID exposure risk and compared to control. Elevated protein levels of CD147 (OR=14.667), ACE2 (OR=8.25) and LDLR (OR=1.9) was associated with higher exposure risk. However, the variation in mRNA expression was not statistically significant. Computational study showed that CD147/basigin, EGFR and LDLR stably interact with spike protein outside its primary receptor binding domain. In-vitro binding assay confirmed the physical interaction between spike protein and the placental receptors. In-silico site-directed mutagenesis further identified key potential binding hotspots of spike protein- Tyr28 and Trp64 for CD147, Phe643, Val642, Thr632 for LDLR and Leu8, Phe59, Phe32, Tyr28, Trp64, Trwp152, His245, and Val213 for EGFR. Finally, concluded that CD147, EGFR and LDLR might act as secondary non-canonical cofactors for SARS-CoV-2 spike protein in placenta, thereby increasing its susceptibility and tissue tropism. The study overall gives a better insight into potential placental suscpetibility providing targeted therapeutic opportunities.

Objective: To determine outcomes by referral route (any Advice and Guidance [A&G] versus elective referrals only) for patients with inflammatory bowel disease (IBD), Parkinson's disease, and systemic lupus erythematosus (SLE). Design: Population-based retrospective cohort study. Setting: Linked Clinical Practice Research Datalink (CPRD) Aurum primary care records, 2015-2022. Participants: Patients with incident diagnosis of IBD, Parkinson's disease, or SLE. Main Outcome Measures: Time from the earliest recorded A&G or elective referral to diagnosis, first recorded definitive treatment and first attended outpatient appointment. Secondary outcomes included counts of primary care consultations, prescriptions, referrals, and outpatient appointments. Propensity score weighted flexible parametric survival analyses accounted for differences between exposure groups. Results: Among 71,145 eligible patients, A&G was recorded for 1,137 (3.0%) with IBD, 971 (3.4%) with Parkinson's, and 243 (4.9%) patients with SLE. Compared with elective referral only, A&G was associated with slower time to diagnosis for IBD (adjusted median difference 15.9 weeks; hazard ratio 0.58, 95% confidence interval 0.52 to 0.66), Parkinson's disease (11.4 weeks; 0.57, 0.51 to 0.64), and SLE (6.3 weeks; 0.82, 0.73 to 0.91). However, A&G was not associated with a longer time to treatment or first attended outpatient appointment. An increase in primary care consultations following A&G was observed in patients later diagnosed with IBD and SLE. Conclusion: A&G was associated with a longer diagnostic interval than elective referral only. These findings do not establish that A&G caused diagnostic delay. A&G might be used at an earlier stage of more complex diagnostic pathways.

Background: Clinical decision support (CDS) systems may improve chronic pain management by providing guideline-based recommendations within clinical workflows. However, low clinician use can limit their effectiveness. Understanding the association between CDS use and guideline-recommended care may help distinguish implementation challenges from limitations in CDS functionality. Objective: To estimate the association of OneSheet, a CDS system for chronic pain management, and guideline-recommended care when the system was used during patient encounters. Methods: We conducted a per-protocol secondary data analysis of data from a pragmatic randomized clinical trial conducted from October 2020 to May 2022 across 25 primary care clinics at 2 academic health systems in Indiana and North Carolina. The parent trial enrolled 137 primary care clinicians. This analysis included 145511 eligible chronic pain encounters and 15480 long term opioid therapy (LTOT) encounters that occurred after OneSheet implementation. OneSheet use at a patient encounter was the exposure of interest. Propensity score matching was used to create comparable groups of encounters with and without OneSheet use. Outcomes included documentation of pain-related goals, documentation of pain and function using the Pain, Enjoyment of Life and General Activity (PEG) scale, prescription drug monitoring (PDMP) review, urine drug screening (UDS) orders, and naloxone orders. Results: OneSheet was used in 959 of 145511 chronic pain encounters (0.7%) and 582 of 15480 LTOT encounters (4.0%). In matched analyses, OneSheet use was associated with increased documentation of pain-related goals (relative risk (RR)=11.70 (95% CI 4.25-32.50) and PEG score documentation (RR=9.70 (95% CI 4.14-22.31). Among LTOT encounters, OneSheet use was associated with increased UDS ordering (RR=1.52 (95% CI 1.40-1.65) and PDMP review (RR=1.06 (95% CI 1.03-1.09), but decreased naloxone ordering (RR=0.13 (95% CI, 0.02-0.90). Conclusions: OneSheet use was associated with several guideline-recommended chronic pain management actions, suggesting that they system may support care quality when clinicians use it. However, use was rare, indicating that increasing routine use through better workflow integration may be necessary to achieve population-level improvements in chronic pain care.

Background: Endometriosis is an estrogen-driven, inflammatory disorder affecting ~10% of menstruators, causing severe pain. Current treatments that reduce estrogen or inflammation have inconsistent efficacy and poor tolerability. Therapies identified via drug-repositioning methods, which target patient-specific pathways, offer a promising alternative. Simvastatin and primaquine were identified as potential treatments, strongly reversing endometriosis-associated gene expression pathways, and behavioral testing in an animal model showed that these drugs diminish endometriosis-associated pain. This paper examines their effects in human assembloids to provide proof-of-concept validation and insights into their mechanisms of action relevant to endometriosis. Methods: We established human endometrial assembloids using immortalized epithelial (12Z) and stromal fibroblast (iEc) cell lines, as well as primary tissue from patients. Assembloids were generated in 96-well agarose molds with both cell types. We tested ibuprofen, fenoprofen, primaquine, and simvastatin. Following a 24-hour exposure, assembloids and monolayer cultures were harvested and stranded mRNA-seq libraries were sequenced on an Illumina NovaSeqX Plus System. Results: Gene set enrichment analysis showed key pathway reversals: Primaquine reversed the chemical carcinogenesis ROS pathway in assembloids. Simvastatin reversed cytokine-cytokine receptor interaction in both epithelial and stromal cell lines, and the cytoskeleton in muscle cells pathway in stromal cell lines. Fenoprofen reversed the calcium signaling pathway in stromal cell lines. Conclusion: Simvastatin induced the most significant gene expression changes, notably reversing cytokine-cytokine receptor interactions in both cell lines, mirroring findings from our rat model. Despite the small sample size limitation, these experiments highlight the promise of assembloid models to test therapeutic candidates for endometriosis.

Background: Psychological health is an important aspect of health and well-being among adults with irritable bowel syndrome, yet the interrelationships among individual vulnerabilities, social experiences, perceived stress, and psychological health outcomes remain poorly understood. Objective: To characterize psychological health and examine direct and indirect associations of childhood adversity and adult attention-deficit/hyperactivity disorder-related symptoms within an adapted Stress Process Model. Design: Cross-sectional secondary analysis. Setting: The United States All of Us Research Program. Participants: 2,417 adults with electronic health record-documented irritable bowel syndrome and complete data on the primary analysis variables and covariates. Methods: Separate structural equation models examined childhood adversity and adult attention-deficit/hyperactivity disorder-related symptoms in relation to perceived stress, anxiety and depressive symptoms, and positive psychological well-being, with loneliness and perceived social support as psychosocial pathways. Models adjusted for sociodemographic and social-context factors. Results: The median age was 54.39 years; 80.7% were female and 84.4% were White. Moderate-to-high perceived stress was reported by 56.2%, at least moderate anxiety symptoms by 21.0%, and at least moderate depressive symptoms by 24.3%. Higher ACE-8 scores were associated with greater perceived stress, anxiety symptoms, and depressive symptoms and lower psychological well-being ({beta} = 0.063, 0.089, 0.116, and -0.100, respectively); corresponding associations for higher ASRS-6 scores were {beta} = 0.299, 0.355, 0.390, and -0.260. Loneliness-specific indirect associations were positive for perceived stress, anxiety, and depressive symptoms (ACE-8: {beta} = 0.023-0.034; ASRS-6: {beta} = 0.043-0.075) and negative for psychological well-being (ACE-8: {beta} = -0.039; ASRS-6: {beta} = -0.089; all p < .001). Social support-specific indirect associations were not significant in the ACE-8 model and were small and significant only for anxiety and depression in the ASRS-6 model ({beta} = 0.003-0.004). Conclusions: Psychological health among adults with irritable bowel syndrome was associated with interconnected individual and social factors within an adapted Stress Process Model. Childhood adversity and adult attention-deficit/hyperactivity disorder-related symptoms showed direct and indirect associations with psychological health, with loneliness emerging as the most consistent social factor. These findings support prospective investigation of individual vulnerabilities and social experiences in psychological health. The cross-sectional design does not establish temporal ordering or causal mediation.

Background: Rapid genome sequencing (rGS) is a first-tier test in the neonatal intensive care unit (NICU). Implementation strategies to scale rGS for clinical care may change clinician roles. We analyzed the NICU rGS workflow to understand challenges rGS poses for clinical roles and responsibilities. Methods: The study took a qualitative approach to understanding the rGS workflow in Level III and Level IV NICUs. The five workflow phases studied included: i) identification of a patient with a suspected genetic disorder, ii) subspecialist consultation, iii) test selection and ordering, iv) return of results, and v) disclosure. Data were collected via job task journals, interviews, and workflow diagram construction with clinicians involved in rGS. Analysis included participant-guided workflow diagram refinement, qualitative thematic analysis, and identification of rGS workflow challenges. Results: We documented issues related to decision-making authority and scope of responsibility for clinicians, with the majority relating to complexities of subspecialist consultations. Issues included differences in: criteria for triggering consultations, expectations of consulted subspecialists' roles, test selection preferences, and responsibility for documenting clinical interpretations and disclosure. Conclusion: Subspecialist consultations in clinical rGS involved significant role ambiguity and communication challenges, requiring intentional implementation efforts to ensure clear clinical roles and responsibilities.

Polygenic risk scores (PRS) are rapidly developing, enabling estimates of genetic risk for developing psychiatric disorders. Psychiatric PRS are also increasingly entering consumer and clinical settings. Yet, little is known about how adults with psychiatric disorders perceive their potential use. Here, we conducted semi-structured interviews with 29 adults with psychiatric disorders to examine their perspectives on hypothetically receiving psychiatric PRS for themselves and their current or future children. Key themes emerged around perceived utility, motivations and deterrents to genetic testing, interpretation of PRS, and anticipated responses to results. In particular, participants expressed hope that PRS could support self-understanding, inform better psychiatric care, and enable earlier recognition of difficulties for their children. Participants however raised multiple concerns, including those of privacy, stigma, discrimination, eugenics, and the risk of self-fulling prophecies. Together, these findings offer critical empirical evidence to inform guidance on the responsible use of psychiatric PRS in clinical and consumer settings.

Abstract Polycystic ovarian syndrome and Type 2 diabetes mellitus are complex multivariate diseases that share well-established clinical pathophysiology, yet the molecular basis of their overlap is unknown. Prior bioinformatics studies have identified common differentially expressed genes between these two conditions. However, they have not accounted for the directionality of the gene expression changes observed, potentially obscuring any biological distinctions they may have. This study applied a direction-aware approach to classify molecular signatures between PCOS and T2DM as concordant or discordant. Transcriptomic analysis of GEO datasets GSE138518 (ovarian granulosa tissue, PCOS) and GSE25724 (pancreatic islet tissue, T2DM) identified 225 and 1,302 DEGs, respectively. Venn diagram analysis showed that only three genes (SLC6A8, RGS4, and SORL1) were shared between PCOS and T2DM from the total of 1,527 genes, and all 3 genes were regulated in opposing directions. Disease gene retrieval from the Comparative Toxicogenomics Database, Online Mendelian Inheritance in Man database, and GeneCards showed 214 shared disease-associated genes, with 311 genes unique to PCOS and 496 genes unique to T2DM. Protein-protein interaction construction using STRING (version 12.0) identified 70 interacting nodes. CytoHubba analysis across 6 scoring methods identified 18 high-confidence hub genes, including INS, BCL2, MTOR, LEP, MFN2, and PIK3CD. Functional enrichment analysis identified biological processes including immune activation, apoptosis, and insulin signaling, which were confirmed as the main pathways in KEGG pathway analysis. These findings show that while PCOS and T2DM share limited DEGs, they share common pathogenic pathways.

Background: Cardiovascular, kidney, and metabolic diseases are closely interconnected and may share common pathophysiological mechanisms, including microvascular dysfunction. Although cardiac 82Rb-PET/CT is routinely used for myocardial perfusion imaging, its potential for integrated cardio-renal perfusion assessment and cardiometabolic phenotyping remains underexplored. We recently developed a compartment modelling approach to quantify renal perfusion from routine cardiac 82Rb-PET/CT, enabling simultaneous assessment of cardio-renal perfusion. However, real-world imaging registries integrating these phenotypes with longitudinal clinical outcomes are lacking. Aim: To establish a real-world imaging registry that repurposes routine cardiac 82Rb-PET/CT by integrating PET-derived hemodynamic measures and CT-derived imaging biomarkers with detailed clinical, echocardiographic, laboratory, and clinical outcome data. Methods: The APOLLO registry is a single-centre retrospective registry of consecutive patients undergoing routine cardiac 82Rb-PET/CT at Alrijne Hospital (Leiderdorp, the Netherlands) between 2021-2023. Clinical, laboratory, medication, echocardiographic, and imaging data were collected to enable integrated cardio-renal perfusion assessment and cardiometabolic phenotyping. Inverse probability of selection weighting analysis was performed to account for renal coverage selection criteria. Cardiac perfusion was quantified using myocardial blood flow and myocardial flow reserve, while renal perfusion was derived using our previously developed compartment-model. Additional phenotyping included adiposity and frailty-related biomarkers, great vessel diameters, vascular calcification, diastolic dysfunction grading, H2FPEF score, Cardio-Kidney-Metabolic (CKM) staging, and longitudinal assessment of major adverse cardiovascular events. Conclusion: APOLLO registry extends routine cardiac 82Rb-PET/CT beyond myocardial perfusion imaging by integrating cardio-renal perfusion measurements with detailed cardiometabolic, clinical, and outcome phenotypes. This real-world registry provides a unique platform for future mechanistic and outcome-based research across the CKM disease spectrum.

Large language models (LLMs) are increasingly consulted for health advice, but they can produce fluent statements that are false or unsupported, known as hallucinations, and this risk is poorly characterised in low-resource languages such as Bangla. We measured hallucinations of locally deployable open-weight LLMs in Bangla diabetes question answering and tested whether retrieval-augmented generation (RAG) grounded in Bangladeshs National Guideline on Diabetes Mellitus reduces them. Forty patient questions spanning six clinical sub-domains were each answered twice, under zero-shot prompting, by Qwen3.5-9B, TigerLLM-9B, Qwen3.6-35B-A3B and Gemma-4-26B-A4B, and by BanglaDiaRAG, which adds hybrid dense (BGE-M3) and sparse (BM25) retrieval from a physician-reviewed Bangla guideline knowledge base to Qwen3.5-9B. Two physicians rated the 400 de-identified responses by consensus for medical accuracy, completeness, safety, readability and reliability on a 0-1 scale, and responses with accuracy below 0.70 were classified as hallucinated. Hallucination rates were 2.5% for Gemma-4-26B-A4B, 3.8% for TigerLLM-9B, 22.5% for Qwen3.6-35B-A3B and 77.5% for Qwen3.5-9B. Guideline grounding lowered the rate of Qwen3.5-9B to 11.3% (difference -66.3 percentage points; 95% CI -76.3 to -55.0) and raised every criterion by 0.24 to 0.38 points (Holm-adjusted p < 0.001). BanglaDiaRAG outscored Qwen3.6-35B-A3B on all five criteria and matched or exceeded TigerLLM-9B, but it remained below Gemma-4-26B-A4B in safety, readability and reliability, and its residual errors were specific, confident and potentially harmful. Guideline grounding can turn a weak general-purpose model into a much safer Bangla diabetes assistant, but the choice of base model mattered as much as retrieval and no configuration was free of hallucination, so clinical oversight remains essential before patient-facing use.

ObjectiveTo evaluate usability and workflow implications of Pheno+, an electronic health record- (EHR) embedded natural language processing tool that extracts patient phenotypes and maps them to Human Phenotype Ontology (HPO) terms. Materials and MethodsThis study performed a mixed-methods formative evaluation of Pheno+ in the context of rapid genome sequencing in the neonatal intensive care unit. Two rounds of think-aloud interviews and surveys were conducted with neonatologists, advanced practice providers, medical geneticists, genetic counselors, non-genetics pediatric subspecialists and laboratory molecular geneticists. Usability was assessed using the System Usability Scale (SUS). Structured data were analyzed descriptively. Qualitative data underwent hybrid deductive-inductive thematic analysis. ResultsTwenty-eight interviewees participated in two rounds of data collection. Users retained an average of 24.2 HPO terms from an average of 45.6 terms per patient. Mean time curating terms was 8:59 per patient. Final SUS score was 76 (above scale mean). Qualitative themes included: burden of curating terms; interpretation of phenotypes; adding information to phenotypes; role of genetics expertise; and tool uses beyond the original core use case for Pheno+. DiscussionPheno+ demonstrated positive usability but required curation effort to reduce erroneous terms. Participant responses indicate that effective use may depend on knowledge of HPO structure and laboratory workflows. Automated phenotyping seems likely to reduce net clinician workload, while also reshaping clinical responsibilities, expertise requirements, and communication in genetic testing. ConclusionTools like Pheno+ can support scalable genomic medicine. Design and implementation may benefit from addressing curation burden, phenotype contextualization, expertise requirements, and other workflow needs.

Importance: Conditions that are hard to diagnose, several more common in women, may be missing from electronic health records (EHRs), hiding patients from research cohorts and case finding. Objective: To measure how often the EHR contains a diagnosis code for chronic conditions that participants report, and to compare this with national survey benchmarks. Design, Setting, and Participants: This cross-sectional study used the All of Us Research Program Registered Tier Dataset v9. Participants were adults with EHR visits in both 12-month periods from July 2021 to June 2023 who completed a health history survey. We analyzed the data in October 2026. Exposures: Self-reported clinician diagnosis of 10 conditions with ongoing visits or treatment, as well as sex at birth, race and ethnicity, age, and years of EHR records. Main Outcomes and Measures: Share of participants reporting current care who had a qualifying diagnosis code, alone and relative to hypertension and type 2 diabetes, and the ratio of age-standardized coded shares to national survey prevalence. Results: Of 161,480 respondents, 114,610 (73,870 female [64.5%], median [IQR] age 63 [50-72] years) had at least 5 years of EHR records before the survey. Among those reporting current care, 84.6% (95% CI, 84.2%-85.0%) with hypertension and 87.0% (95% CI, 86.5%-87.6%) with type 2 diabetes had a code, compared with 41.3% (95% CI, 38.9%-43.8%) for endometriosis, 39.4% (95% CI, 34.3%-44.8%) for Lyme disease, and 24.4% (95% CI, 23.2%-25.6%) for chronic fatigue. Counting ICD-9-CM and other mapped codes, 55.3%, 51.5%, and 28.3%, respectively, had any qualifying record. Women had lower coded shares than men for hypertension, type 2 diabetes, obesity, depression, and anxiety (crude ratios 0.93-0.96, within-health-system ratios 0.98-1.02) and higher shares for migraine and fibromyalgia (within health systems, 1.11 [95% CI, 1.07-1.15] and 1.41 [95% CI, 1.29-1.57]). Age-standardized coded shares among active patients were 1.1 to 2.4 times national prevalence of the same self-reported diagnoses. Conclusions and Relevance: In this cross-sectional study, fewer than half of participants reporting ongoing care for chronic fatigue, Lyme disease, or endometriosis had a qualifying ICD-10-CM code. Linking each participant's report to their own record measured this gap directly.

Background Implantable loop recorders (ILRs) provide continuous rhythm monitoring. Professional society guidelines and expert consensus statements recommend ILR use for patients with recurrent syncope and cryptogenic stroke, but recommendations are weaker for other indications. We assessed ILR use over time and concordance between indication and clinical guidance. Methods We conducted a retrospective cohort study using Epic Cosmos data from 1/1/2020-12/31/2025. Among active patients with at least one of 13 diagnoses potentially eligible for ILR placement, we identified ILR placements and classified them by concordance with professional society guidance: concordant, possibly, or non-addressed. Annual incidence was estimated overall and by indication. We also described the proportion of patients who received longer-term (>7 days) rhythm monitoring in the year prior to placement. Results Of 47,046,706 patients with diagnoses potentially eligible for ILR placement, 201,103 (0.4%) had an ILR placed. ILR placements increased from 3.08 ILRs per 100,000 patient-days in 2020 to 4.13 in 2025 (5.9% annual growth). The most common indications were cryptogenic stroke (28.6%) and atrial fibrillation without prior ablation (21.4%). Overall, 43.9% were guidance concordant, 28.5% possibly concordant, and 24.8% non-addressed. Relative annual growth in ILR placements per 100,000 patient-days was significant across all guidance categories: concordant (1.3%, 95% CI, 0.9%-1.7%), possibly concordant (5.5%, 95% CI, 5.0%-6.0%) and non-addressed (7.4%, 95% CI, 6.8%-8.0%). Among 125,631 outpatient placements, 50,181 (39.9%) had any prior long-term rhythm monitoring. Conclusion ILR placements are uncommon but increasing, with faster annual growth for indications that may not be guidance concordant. More than half of patients lacked long-term rhythm monitoring prior to outpatient ILR placement.

Objective: To develop and evaluate a dynamic model that repeatedly estimates the 30-day risk of a first grade [&ge;]2 immune-related adverse event (irAE) during immune checkpoint inhibitor (ICI) therapy. Materials and Methods: Adults initiating ICI therapy during 2015-2022 comprised the development cohort; 2023 initiators formed a nonoverlapping internal temporal evaluation cohort. Every 21 days during the first treatment year, models used available EHR information to predict a first structured phenotype-defined above Grade 2 irAE during the next 30 days. Evaluation included pooled and within-landmark discrimination, precision-recall performance, calibration, and patient-clustered bootstrap confidence intervals. Feature-state ablations and alternative update schedules examined the contribution of dynamic information. Results: Development included 1,522 patients and 18,744 evaluable landmarks; temporal evaluation included 526 patients and 6,263 landmarks, of which 184 were positive (2.94%). The multiscale XGBoost model achieved pooled AUROC 0.716 (95% CI, 0.676-0.755), AUPRC 0.067, within-landmark AUROC 0.672 (95% CI, 0.631-0.716), Brier score 0.0281, and log loss 0.1245. The time-aware baseline achieved AUROC 0.631 and within-landmark AUROC 0.536. Updated treatment exposure and laboratory trajectories accounted for most of the gain. A complete-state extension achieved AUROC 0.719 and AUPRC 0.073. The 21-day schedule had the highest discrimination among tested cadences. Conclusion: Longitudinal EHR updating improved near-term irAE prediction beyond pretreatment characteristics and treatment time. Phenotype adjudication and independent evaluation of calibration, transportability, and clinical utility are needed before implementation

Objective: Autoantibodies are central for pathology of rheumatoid arthritis (RA) and diabetes mellitus (DM) carrying high predictive and diagnostic value. Here, we explore the frequency and functional potential of DM-related antibodies (DMab) in RA. Methods: DMab targeting glutamic acid decarboxylase (GAD65ab), tyrosine phosphatase-like islet antigen 2 (IA2ab) and zinc transporter 8 (ZnT8ab) were measured in 326 DM-free RA patients (260 females, 66 males), using specific ELISAs. The DMab profile was analysed in relation to 30 clinical and serological variables. ZnT8+ cells were detailed by a public single-cell transcriptome in RA synovial tissue. Results: DMab production was more frequent in females, dominated by ZnT8ab (86%), followed by GAD65ab (26.4%) and IA2ab (7.0%). DMab-positive patients, and specifically ZnT8ab-positive women, had higher levels of insulin and HOMA-IR index and lower serum IL-6, IFN{gamma}, and IL-9. Multivariable logistic regression estimating ZnT8ab, IA2ab, GAD65ab production revealed that BDNF, insulin and DAS28 were positive predictors of ZnT8ab. Increasing ZnT8ab levels were inversely related to RAab in the mixed interaction model. CD14+ cell transcriptome identified association between an activated secretory cell type and increasing ZnT8ab levels. Additionally, ZnT8ab levels were in direct proportion with ZnT8 production in RA CD4+ T cells. Single-cell transcriptome of RA synovial tissue revealed ZnT8+ cells among the lubricin producing lining layer fibroblasts programmed for invasive behaviour. Conclusion: This study reveals frequent production of ZnT8ab in non-diabetic RA patients and identifies their antigenic target expressed in lining synovial fibroblasts of RA joints.

Background: Cardiovascular-Kidney-Metabolic Syndrome (CKMS) is defined as a cluster of disease conditions that are highly prevalent in the U.S. population. This study aims to assess psychosocial adversities at different CKMS stages in a large survey of U.S. adults, measured by lack of emotional support, low life satisfaction, and loneliness. Methods: This cross-sectional study used data on 159,511 adults from the 2023 Behavioral Risk Factor Surveillance System (BRFSS) survey. Proxy CKMS stages (0, 1, 2/3, and 4) were determined using self-reported health conditions. Separate multivariable logistic regression models were estimated to obtain the predictive margins of respective psychosocial attributes across proxy CKMS stages. Results: Compared to adults at lower CKMS stages (Stages 0 and 1), adults at advanced CKMS stages (Stages 2/3 and 4) generally reported having higher psychosocial toll. At CKMS stage 4, the predicted probabilities of lack of emotional support, low life satisfaction, and loneliness were 6.96, 3.24, and 10.10 percentage points (pp) higher, respectively, than at stage 0. Compared to stage 1, the corresponding differences were 5.92, 2.89, and 9.65 pp. At CKMS stage 2/3, the corresponding differences were 4.36, 1.66, and 5.69 pp compared to stage 0 and 3.33, 1.32, and 5.25 pp compared to stage 1. The high burden at advanced CKMS stages was generally evident across sex, and different socioeconomic status conditions manifested by income and education. Conclusions: Findings of this study suggest that adults with advanced CKMS stages were more likely to experience a psychosocial toll. Further research is warranted to facilitate strategies for improving psychosocial wellbeing of CKMS patients.

Modern clinical medicine depends on reducing complex human realities into forms that support knowledge, judgment, and action. Such reduction is indispensable to scientific medicine, but necessarily selective. A medical framing may therefore remain well warranted within medicine while becoming insufficient in relation to the reality of a particular patient. What happens clinically when the adequacy of such a framing itself becomes uncertain remains insufficiently understood. We conducted an abductive, theory-generating qualitative study of 44 patients who attended a supplementary Dialogue-Based Outpatient Clinic within a breast oncology service in Japan between 2021 and 2023, comprising 111 consultations. The clinic had no predefined clinical agenda, allowing patients to raise concerns that mattered to them. Through iterative comparison within and across cases, we examined how patients' concerns were understood and responded to clinically. Across cases, a recurrent clinical process became apparent when patient reality called the adequacy of existing medical framing into question. Exploration of patients' concerns could expose a consequential mismatch between their reality and the framing through which medicine understands and represents clinical reality. Such mismatches prompted inquiry into medical framing to identify what required reopening. Reopening occurred when the identified framing, previously treated as provisionally settled, became reconsiderable in relation to the patient's reality. Reconsideration involved examining what had been reopened and exploring clinical responses through dialogue between clinician and patient, followed by a clinical response and provisional closure. We describe this recurrent process as Clinical Epistemic Reopening (CER). CER identifies a clinical process through which the framing produced by medicine's necessary selectivity in making complex reality clinically knowable and actionable can itself become reconsiderable when patient reality reveals its limits. CER can thereby reverse the usual direction of clinical scrutiny: aspects of medicine that ordinarily function as means of understanding and acting upon the patient can themselves become objects of clinical inquiry. CER thus allows medicine to remain open to patient reality beyond the limits of its existing framings.

Objectives: Patients and clinicians increasingly ask large language models (LLMs) about Kampo, Japan's traditional medicine. Yet evaluations of LLMs have measured accuracy on examination questions, which ask what a model knows; a consultation asks whether it can apply that knowledge to the patient at hand. No benchmark had measured that. Materials and Methods: KampoBench comprises 74 consultation scenarios and 310 conversation-specific rubric criteria, following the design of HealthBench. Scenarios, criteria and reference answers were drafted by an LLM and revised by board-certified Kampo physicians. Ten current models from three vendors were evaluated. Because LLM graders are known to favor their own family, each response was graded by a model from each vendor. Results: The best model reached 74.8-86.3% across graders, the physician-revised reference answers 87.9-92.4%. Rankings were stable across graders (Spearman's rho 0.952-0.976), and the family-favoring deviation was 0.4 to 0.6 percentage points, below the bootstrap standard deviation of one measurement; grader leniency varied by 14.3 points. Models were most reliable on criteria about advising that care be sought (83.6%) and least reliable on those requiring a known crude-drug risk to be tied to the case (17.5%), though 79.2% of those responses named the drug. Discussion: The shortfall lay in applying knowledge to the case rather than in holding it - a distinction examination-format evaluations cannot make. Conclusion: Evaluation in traditional medicine should measure the judgments a consultation requires, not recall alone. Quoted alongside the grader that produced it, a KampoBench score is a usable measure of those judgments.