Annals of Internal Medicine

Background Six years after its emergence, SARS-CoV-2 continues to have a substantial burden. The impact of vaccination and the optimal timing of its rollout remain uncertain given existing population immunity and variability in outbreak timing between summer and winter. Methods The US Scenario Modeling Hub convened its 19th round of ensemble projections for COVID-19 hospitalizations and deaths in the United States, where eight teams projected trajectories in each US state and nationally from April 2025 to April 2026 under five scenarios regarding vaccine recommendations and timing. Recommendations had two eligibility scenarios (high-risk individuals only and all-eligible) and two timing scenarios (classic start: mid-August, earlier start: late June). These were crossed to create four scenarios and were compared against a counterfactual scenario with no vaccination. Findings Compared to no vaccination, our ensemble projections estimated 90,000 (95% PI 53,000-126,000) hospitalizations averted in the high-risk and classic timing scenario across the US. Expanding to all-eligible age-groups averted an additional 26,000 (95% PI 14,000-39,000) hospitalizations, which when coupled with the early vaccination timing, was projected to further reduce national hospitalizations by 15,000 (95% PI -3,000-33,000). The majority of teams projected both summer and winter waves. Implications We project COVID-19 will cause significant hospitalizations and deaths in the US in the 2025-26 season and estimate significant benefits from a broad all-eligible vaccination recommendation. The results also suggest an additional benefit is likely to be gained from an earlier vaccination campaign. Funding Centers for Disease Control and Prevention; National Institute of Health (US), National Science Foundation (US)

BackgroundIn clinical contexts where disease burden differs across demographic groups, enforcing demographic parity -- equal prediction rates regardless of group -- may reduce screening for the populations that need it most. We demonstrate this using HIV testing prediction as a case study. MethodsUsing the Behavioral Risk Factor Surveillance System (BRFSS) 2024 dataset (N=386,775), we trained four classifiers to predict HIV testing uptake and evaluated disparities using demographic parity difference (DPD), equalized odds difference (EOD), and calibration across eight racial/ethnic groups. We applied threshold optimization and exponentiated gradient mitigation and quantified their impact on high-burden populations, including intersectional effects across race and sex. ResultsBaseline selection rates ranged from 12.1% (Asian) to 66.0% (Black), mirroring differential HIV burden (DPD 0.519-0.634). Race-blind models retained 70% of baseline disparity through correlated social determinants. Enforcing demographic parity reduced Black true positive rates from 78.2% to 30.0% (61.6% relative decrease), causing 1,610 additional missed individuals. Race-only optimization worsened sex-based disparity by 71%; multi-objective optimization reduced intersectional DPD from 0.609 to 0.076 but at the same cost to high-burden groups. Exponentiated gradient AUC fell from 0.671 to 0.592 (11.8% relative decrease). Survey-weighted sensitivity analysis confirmed unweighted estimates underestimated disparities. ConclusionsDemographic parity is an inappropriate fairness criterion in differential-burden clinical contexts because it reduces screening access for high-risk populations. Fairness audits in healthcare should use need-appropriate metrics (equalized odds, calibration) rather than defaulting to demographic parity, and metric selection should involve clinician and community stakeholder deliberation.

ImportanceDonor hospitals in the United States are assigned to a designated organ procurement organization (OPO) responsible for managing deceased donors in the designated donation service area (DSA). Donor hospitals can apply for waivers to work with a different OPO with appropriate justification, and beginning with the 2026 OPO certification cycle, the highest-performing OPOs can bid to work with donor hospitals managed by intermediate- and low-performing OPOs. ObjectiveWe sought to evaluate the impact of donor hospital waivers on organ donation activity. DesignRetrospective cohort study. SettingWe evaluated Organ Procurement and Transplantation Network (OPTN) data from two OPOs (Donor Network West and Honor Bridge), each with a donor hospital (Renown Regional Medical Center and North Carolina Baptist Hospital) in its DSA granted a waiver to work with a different OPO beginning in April 2025. Main OutcomeWe assessed changes in the number of organ donors and organs transplanted pre- and post-granting of a waiver using a difference-in-differences approach based on multilevel mixed-effects models. ResultsAfter switching OPO affiliations, these two donor hospitals had marked and statistically significant increases in the number of donors recovered and organs transplanted, despite stable numbers of reported deaths at each hospital. In multivariable models, switching OPO affiliations was associated with a statistically significant increase in donors recovered and organs transplanted. Conclusion: With eight months of post-waiver data, donor hospitals with granted waivers had significant increases in donation activity driven by improved donor conversion rather than changes in referral patterns or organ yield per donor. Although longer-term data are needed to confirm these findings, CMS and the organ transplant community should feel confident that changing donor hospital-OPO affiliations will not negatively impact donation and may lead to significant increases in donation. These data also counter unfounded concerns that the continued granting of waivers and realignments of donor hospital-OPO affiliations during the 2026 recertification cycle will lead to a collapse of the system of organ donation. KEY POINTSO_ST_ABSQuestionC_ST_ABSDo donor hospitals who request a waiver to change OPO affiliations have changes in organ donation rates? FindingsUsing a difference-in-difference approach, the two donor hospitals who changed OPO affiliations had a significant increase in organ donors and organs transplanted after being granted a waiver. MeaningDonor hospitals that change OPO affiliations have an immediate increase in organ donation activity.

BackgroundThe effects of Banff histological diagnoses on kidney transplant outcome have been well characterized. However, repeated observation of such histological injury across multiple biopsies in kidney transplant recipients remains insufficiently explored. MethodsIn an observational cohort (N=1819 transplantations with 5736 post-transplant biopsies, recurrent event survival models quantified transitions between diagnoses of T-cell mediated rejection (TCMR), antibody-mediated rejection (AMR), DSA-negative C4d-negative microvascular inflammation (MVIDSA-/C4d-), BK polyomavirus nephropathy (BKPyVAN), borderline TCMR (bTCMR), and probable AMR (pAMR), revealing patterns in the disease trajectories. In two observational cohorts (N=1818 transplantations with 5732 biopsies, N=853 transplantations with 975 biopsies), time-dependent cumulative covariates were constructed for TCMR, AMR, MVIDSA-/C4d- and BKPyVAN, enabling estimation of associations of repeated diagnoses with graft failure using multivariable cause-specific Cox models. ResultsThe incidence rate of a diagnosis was most strongly associated with earlier diagnosis of the same type, but associations between different types of diagnoses also occurred. The hazard of kidney graft failure was significantly increased by repeated observation of TCMR in multiple biopsies (HR 7.97, 95% CI 4.94 - 12.86), as well as by repeated AMR (HR 6.19, 95% CI 3.15 - 12.17), repeated MVIDSA-/C4d- (HR 4.53, 95% CI 2.15-9.54) and repeated BKPyVAN (HR 10.90, 95% CI 5.83 - 20.35). The hazard of graft failure was increased more after repeated diagnoses in transplants than after first diagnoses. The effects of repeated TCMR and repeated AMR remained significant even when observed in protocol biopsies in the absence of graft dysfunction. Repeated observation of BKPyVAN was the most detrimental of all diagnoses when observed in indication biopsies, but it was the least harmful when observed in protocol biopsies. ConclusionIncidence of Banff histological diagnoses appears to be affected by earlier diagnoses, especially those of the same type. These repeated observations of a specific diagnosis have an additional effect on the hazard of graft failure, underscoring a critical unmet need for adequate treatment strategies for these recurrent or persistent injury processes. Lay summaryIn two observational cohorts of 1819 and 750 kidney transplant recipients, kidney transplant biopsies were taken at multiple time points after transplantation. Based on the Banff classification for transplant pathology, various post-transplant diseases were diagnosed, often at more than one time point during follow-up. We assessed patterns in the occurrence of diagnoses over time, and related these diagnoses to survival of the kidney grafts using survival models with time-dependent cumulative diagnoses. We found that repeated observation of the same diagnosis was much more common than consecutive observations of different diagnoses. Repeated diagnoses of tissue injury also decreased kidney graft survival more compared to single diagnoses. This indicates that treatment options for patients with repeated or persistent diagnoses are currently inadequate and novel strategies are needed.

BackgroundHeartland virus (HRTV) is an emerging tick-borne virus capable of causing severe illness and death. The burden of disease is likely underestimated due to limited seroprevalence studies, lack of commercially available diagnostic tests, and an overlapping clinical syndrome with more commonly diagnosed bacterial diseases such as spotted fever group rickettsiosis or ehrlichiosis. MethodsActive surveillance for Heartland virus disease was conducted at a large academic center from March to September 2024. Enrolled subjects included those who had testing sent for Ehrlichia polymerase chain reaction (PCR) along with fever and 2 of the 3 criteria: leukopenia, thrombocytopenia, and/or elevated liver function tests. Specimens with detectable RNA underwent whole genome sequencing and analysis. FindingsOver 800 specimens were received with 53 individuals meeting enrollment criteria. Among these 53, two (3.8%) had detectable HRTV RNA in whole blood during the time of Ehrlichia PCR testing. The two cases had disparate clinical manifestations: one with mild disease which was identified in an outpatient setting, while a second case required intensive care unit-level support. Heartland virus genome sequences from the two cases were more similar to viruses from other states than they were to one another. InterpretationDespite only two prior reported cases of Heartland virus disease in North Carolina, we identified two individuals with acute HRTV viremia. Further surveillance for HRTV disease is necessary to understand the burden of disease and to facilitate further studies of virus pathogenesis and host responses. FundingFunding for the study was provided by a Creativity Hub Award to Dr. Boyce from the UNC Office of the Vice Chancellor for Research. Dr. Zychowskis effort was supported by the T32 NIAD grant AI070114.

Background & AimsLiver cancer primarily develops in patients with chronic liver disease (CLD), yet most cases are diagnosed at an advanced stage with poor prognosis. While clinical surveillance of patients with CLD generates extensive longitudinal data, its unstructured free-text nature hinders large-scale research. To unlock this real-world evidence, we developed a scalable framework using open-source Large Language Models (LLMs) to transform unstructured clinical text into structured data. MethodsWe conducted a multi-stage evaluation of LLM-based extraction from multi-source clinical documentation of liver transplant recipients. A calibration set comprising 507 reports (414 radiology, 65 pathology, and 28 liver transplant assessment reports) from 30 patients was manually annotated to benchmark four open-source LLMs (Llama 3.1 8B, Llama 3.3 70B, Open-BioLLM 70B, DeepSeek R1 8B) against a regular expression baseline across 73 tasks. To ensure structured outputs, we compared constrained decoding (Guidance and Ollama packages) against unconstrained prompting across 5,590 prompt-output pairs. The finalised pipeline was then applied to the full cohort of 835 patients transplanted in our centre over the past decade. ResultsAmong the models tested, Llama 3.3 70B performed best, exceeding 90% accuracy on 59/73 tasks, outperforming both a medically fine-tuned model (OpenBioLLM 70B) and a smaller variant (Llama 3.1 8B). Constrained decoding achieved >99.9% format adherence, far surpassing unconstrained prompting (87.4%). Applied to the full cohort, the pipeline successfully analysed 22,493 reports to generate 37,125 datapoints (45 variables, 835 patients) without manual annotation. Further analysis confirmed known liver cancer risk factors (male sex, viral hepatitis, smoking, diabetes), and allowed for reconstruction of longitudinal disease timelines. ConclusionsThis work provides a scalable blueprint for transforming real-world clinical free-text into structured formats, paving the way for accelerated, data-driven research into complex pre-cancerous diseases like CLD.

Background & AimsPerihilar cholangiocarcinoma is an aggressive malignancy with clinical heterogeneity and poor long-term outcomes after resection. Current prognostic assessment relies mainly on anatomical staging and pathological features, which incompletely capture the entire postoperative risk. We aimed to determine whether integrative analysis of clinical, surgical, pathological and tumor genomic data could improve time-resolved, individualized recurrence-risk prediction after curative-intent resection. MethodsWe performed a multicenter retrospective study including patients undergoing curative-intent resection for perihilar cholangiocarcinoma in ten Spanish hospitals (2003-2023). Overall and disease-free survival were analyzed using Cox models. Outcome-agnostic clinical phenotypes were derived by unsupervised clustering of clinical and surgical features. Targeted tumor sequencing of cancer-associated hotspot regions and selected genes was performed. Prognostic models integrating clinical and genomic data were trained and evaluated in independent training/test sets using penalized and latent-component Cox frameworks, with time dependent discrimination. ResultsThe final cohort comprised 142 patients, with a median follow-up of 26.4 months. Recurrence occurred in 61.3% of patients, and 53.5% died during follow-up. Classical pathological factors were strongly associated with survival and recurrence. Unsupervised outcome-agnostic clustering identified three reproducible clinical phenotypes with markedly different recurrence patterns and survival, only partially explained by anatomical staging. Integrative clinical-genomic modelling further improved recurrence-risk prediction, achieving high discrimination in independent validation (time-dependent AUC [~]0.8). Moreover, the integrative model assigned higher risk over time to patients who relapsed. Patients combining unfavorable clinical phenotype with high genomic-derived risk exhibited a high probability of early recurrence. ConclusionsIntegrated clinical phenotyping and targeted genomic profiling substantially refine recurrence-risk stratification after resection of perihilar cholangiocarcinoma beyond anatomical staging alone. This provides a pragmatic framework for risk-adapted postoperative surveillance and therapeutic decision-making. Impact and ImplicationsThis study provides a data-driven framework integrating clinical, surgical and targeted genomic information to refine prognostic stratification after resection of perihilar cholangiocarcinoma, addressing the limitations of anatomy-based staging in capturing biological heterogeneity. The results are particularly relevant for clinicians managing postoperative surveillance and adjuvant strategies, as they identify patient subgroups with markedly different risks of early recurrence despite similar conventional staging. In practical terms, the combination of unsupervised clinical phenotyping and a targeted, biologically informed genomic panel could support risk-adapted follow-up intensity, selection for adjuvant or experimental therapies, and enrolment into clinical trials. While prospective validation is required before routine implementation, this approach offers a feasible and interpretable pathway toward precision postoperative management in a highly aggressive malignancy.

Background: COVID vaccination with periodically updated compositions remains important as SARS-CoV-2 continues to circulate, cause disease, and evolve. Available COVID-19 vaccines in the 2024-2025 season differed by platform, including mRNA-1273, an mRNA-based vaccine, and NVX-CoV2705, a recombinant protein-based vaccine and antigen composition (KP.2-targeted and JN.1-targeted, respectively). There is limited head-to-head real-world evidence comparing the effectiveness of these different approaches to prevention of severe outcomes with COVID-19. We compared mRNA-1273 with protein-based NVX-CoV2705 in insured US adults vaccinated during the 2024-2025 season. Methods: We conducted a retrospective matched cohort study in a large US claims database. Adults aged 18 years or older who received mRNA-1273 or NVX-CoV2705 between Aug 31, 2024 and Feb 28, 2025 were eligible. Recipients were exactly matched 2:1 on key demographic and clinical factors and then weighted with stabilized inverse probability of treatment weights. Outcomes were medically-attended COVID-19 and hospitalization with COVID-19 from day 7 after vaccination through up to 180 days of follow-up. We calculated comparative vaccine effectiveness (cVE) as 100 x (1-- hazard ratio). Results: Of 858,138 eligible mRNA-1273 recipients and 34,667 eligible NVX-CoV2705 recipients, 69,140 and 34,570, respectively, entered the matched cohort. Median (Q1, Q3) follow-up was 180 (163, 180) days for mRNA-1273 and 180 (162,180) for NVX-CoV2705. Medically attended COVID-19 occurred in 706 (1.02%) mRNA-1273 recipients and 512 (1.48%) NVX-CoV2705 recipients; adjusted cVE (95% CI) was 31.7% (23.4%, 39.1%). Hospitalization with COVID-19 occurred in 61 (0.09%) and 49 (0.14%) recipients, respectively; adjusted cVE (95% CI) was 40.7% (13.5%, 59.4%). In the 47,754 mRNA-1273 recipients matched to 23,877 NVX-CoV2705 recipients aged [≥]65, adjusted cVE (95% CI) was 25.7% (15.4%, 34.8%) against medically-attended COVID-19 and 41.7% (14.3%, 60.4%) against hospitalization with COVID-19. Conclusions: In this insured US adult population, mRNA-1273 demonstrated greater effectiveness against medically attended COVID-19 and hospitalization with COVID-19 than the protein-based NVX-CoV2705. These findings highlight the potential public-health importance of considering vaccine platform and variant selection when planning for upcoming seasons.

Background: Long COVID presents with one or multiple symptoms or diagnosable conditions after SARS-CoV-2 infection. To study whether use of the antiviral remdesivir in persons hospitalized with acute COVID-19 is associated with reduced Long COVID, we created a computational phenotype for Long COVID. Methods: In electronic health records (EHR) from a multistate healthcare system (US), hospital admissions from 5/1/20 - 9/30/22 were reviewed. The study group was hospitalized with acute COVID-19 and the control group was hospitalized for other reasons without prior SARS-CoV-2 infection. The populations were balanced with overlap weights based on a high-dimensional propensity score of pre-specified variables and the top 100 comorbidities differing between the groups. Hazard ratios (HR) were calculated for the combined primary outcome: U09.9 (Post-Covid Conditions) or any incident secondary outcome from 90 to 365 days after admission. Secondary outcomes included 27 individual incident diagnoses, corrected for multiplicity with Holm-Bonferroni. Results: Admissions included 45,540 with, and 409,186 without COVID-19 during the study period, evaluable for the primary outcome. After weighting, standardized difference was < 0.01 for all measured confounders including demographic and clinical features. In the COVID+ and non-COVID groups 38.0% and 29.3% met the combined primary outcome, respectively. Weighted HR (95%CI) for the primary outcome was 1.37 (1.35, 1.40), p < 0.0001. All secondary outcomes were associated with the COVID+ group, when adjusted for multiplicity. Incident diagnoses with strong associations (HR > 2) included thromboembolism, hair loss, diabetes mellitus, obesity, and hypoxia. Anosmia/dysgeusia was associated with COVID, but wide confidence intervals reflected few charted diagnoses. Conclusions: Manifestations of Long COVID at population scale are detectable as part of routine symptoms and clinical diagnoses in the EHR after admissions for COVID-19, compared with all other hospital admissions. This a prior computational phenotype for Long COVID will be used to assess whether remdesivir use is associated with decreased Long COVID.

Background: We aimed to identify data-driven FEV1 trajectory phenotypes post-chronic lung allograft dysfunction (CLAD), relate these phenotypes to patient factors and future graft loss, and develop a classification approach for prospective patients. Methods: We studied adult first lung recipients with probable CLAD from two prospective multicenter cohorts: CTOT-20 (n=206) and LTOG (n=1418). FEV1 trajectories over the first nine months post-CLAD were characterized using joint latent class mixed models, jointly modelling time-to-graft loss to account for informative censoring. Models were fit independently in both cohorts and also only among LTOG bilateral recipients. A classification and regression tree (CART) model was derived in LTOG bilateral recipients and applied to CTOT-20 bilateral recipients. Findings: Four distinct early FEV1 trajectory classes were identified in CTOT-20, with large differences in nine month graft loss (72.3%, 31.1%, 2.2%, 0%). In LTOG, similar trajectory patterns were reproduced, with an additional class demonstrating early post-CLAD FEV1 improvement. Among bilateral recipients, trajectory classes showed a clear risk gradient, including a high-risk class with 100% graft loss and a low-risk class with no early graft loss. A CART model incorporating clinical and spirometric variables demonstrated good discrimination in LTOG bilateral recipients (multiclass AUC 0.85) and consistent class assignment and trajectory patterns when applied to CTOT-20. Interpretation: We identified reproducible, clinically meaningful early post-CLAD FEV1 trajectory phenotypes with differential graft loss risk. These phenotypes and a pragmatic classification tool may support risk stratification, trial enrichment, and improved prognostication for patients and clinicians.

Background: The observational literature on comparative effectiveness is expanding rapidly but remains difficult to synthesize. Discordant findings often stem from structural differences in cohort definitions, inclusion criteria, and follow up windows, leaving stakeholders without a cohesive evidence base. Furthermore, studies typically focus on a narrow subset of outcomes, neglecting the broader needs of diverse healthcare stakeholders 1,2,3,4. Methods We developed a high throughput evidence generation workflow using linked EHR and administrative claims data. The cornerstone is a prespecified measurement architecture applied uniformly across clinical scenarios: six post index windows (acute to two year follow.up); 28 Elixhauser comorbidities; 14 healthcare resource utilization (HCRU) categories; 29 laboratory measures with 52 binary thresholds; and 42 adverse event categories. We generated unadjusted treatment comparisons across ~1,038 outcomes per scenario, including effect-measure modification (EMM) assessments across 130 baseline features. Results Across 40 clinical domains, the workflow produced approximately 32,982,552 outcome evaluations. An evaluation included a treatment comparison outcome population effect estimate with uncertainty bounds and supporting diagnostics. Approximately 5,000 narrative summaries underwent structured clinical and statistical quality control before dissemination. Conclusions Standardized, high throughput workflows can shift evidence generation away from fragmented studies toward comprehensive evidence packages. This shared evidence base supports precision medicine by making treatment effect heterogeneity visible across clinically meaningful subpopulations, reducing the need for redundant, stakeholder-specific studies.

Introduction: COVID-19 transmission has not been evenly distributed across racial groups, with exposure being shaped by social and structural factors. The emergence of highly transmissible variants (i.e., Omicron) dramatically increased infection rates. However, it remains unclear whether racial disparities in transmission disappeared or persisted over the course of the pandemic. Objective: To understand how SARS-CoV-2 transmission differed by race in Canada and whether those disparities changed with the Omicron variant. Methods: We analyzed cross-sectional SARS-CoV-2 seroprevalence data from the Canadian Blood Services serosurveillance program (June 2020 to April 2023) using a previously described dynamic susceptible-infection model, while accounting for seroreversion. Race-specific force of infection was estimated for the pre-Omicron and Omicron periods (with the emergence of Omicron defined as beginning December 26, 2021). Results: Prior to Omicron, racialized individuals had a 74% higher force of infection (IRR = 2.205; 95% CI: 2.115-2.299). During the Omicron period, infection rates rose significantly within each racial group relative to the pre-Omicron period, with a 55.52-fold increase among White individuals and a 31.27-fold increase among racialized individuals. Despite this, racialized individuals remained disproportionately affected following the emergence of Omicron, with 24% higher infection rates than those of their White counterparts (IRR = 1.242; 95% CI: 1.231-1.253). Conclusion: Widespread transmission during Omicron did not result in epidemiologic equity, as racialized populations continued to experience higher infection risk despite crude seroprevalence depicting convergence.

1.BackgroundVision-language models (VLMs) are increasingly proposed for radiologic decision support, yet the security implications of deploying general-domain, OCR-capable models in diagnostic workflows remain poorly characterized. When image-embedded text is not treated as untrusted input, the visual channel becomes vulnerable to adversarial manipulation through OCR-readable overlays. MethodsNine commercial VLMs, none intended or validated for clinical diagnosis, were evaluated on 600 brain MRI studies (300 tumor-positive, 300 tumor-negative) for binary tumor detection across four conditions: clean input, visible radiology-report injection, human-imperceptible stealth OCR injection, and a multi-stage immune-prompt defense combining both attack types with enforced visual-priority reasoning. Approximately 27,000 inference calls were analyzed. Primary outcomes included accuracy, attack success rate (ASR), false positive rate (FPR), and masking rate. ResultsAt baseline, performance was heterogeneous (median accuracy 0.69, sensitivity 0.79, specificity 0.59). Visible injection caused universal specificity collapse (0.00 across all models; FPR 1.00), with a median ASR of 0.97; every model unconditionally privileged the injected text over its own visual analysis. Stealth injection, despite being imperceptible to human reviewers, still drove substantial degradation (median accuracy 0.43; ASR 0.57; FPR 0.84). Immune prompting achieved only partial and inconsistent mitigation: under stealth injection, median ASR decreased to 0.44, and accuracy improved to 0.56, yet residual overcalling persisted (median FPR 0.67), and three models maintained an FPR of 1.00. ConclusionsCommercial VLMs exhibit a deployment-critical failure mode in radiology-like scenarios: OCR-readable text embedded in images can dominate the decision pathway and override pixel-level evidence, even under stealth conditions that evade human inspection. Prompt-level defenses provide insufficient protection. These findings underscore that any clinical integration of VLMs must be gated by system-level safeguards, including OCR-aware input handling, provenance controls, and enforced human verification, before such tools can be considered for safety-sensitive environments.

ImportanceMetastatic prostate cancer (PCa) incidence has increased in U.S. men, partly due to changes in prostate-specific antigen (PSA) screening recommendations. However, few studies have examined contemporary PSA screening practices in large U.S. healthcare systems. ObjectiveDescribe and examine contemporary PSA testing practices associated with metastatic PCa incidence. DesignCohort study. SettingVeterans Health Administration. ParticipantsVeterans diagnosed with prostate needle biopsy (PNBx) between 2015 and 2023 with follow-up through 2024, excluding those with a history of PCa. ExposuresPSA tests were retrieved from the VA corporate data warehouse and categorized by age at first VA PSA (<50, 50-59, [&ge;]60 years) and by longest interval between consecutive VA PSA tests in the 5 years before PNBx ([&le;]24 , >24 months). Clinical, laboratory, pathological, demographic, and Census Block Group-level socioeconomic status data were obtained from the VA Multi-OMICS Analysis Platform for Prostate Cancer (VA-MAPP) database. Main Outcomes and MeasuresMultivariable Cox models estimated hazard ratios (HR) from time of first VA PSA to first PNBx, evaluated risk of metastatic (regional or distant) versus localized PCa, or benign diagnosis, adjusted for sociodemographic and clinical covariates. Data were analyzed between July 1, 2023 and November 6, 2025. ResultsThere were 103,067 participants of whom 20% were <50 years old at first PSA, 31% non-Hispanic Black, 57% non-Hispanic White, and 13% other racial and ethnic groups. Of these, 22% had first PSA value [&le;]1, 51% had a screening interval [&le;]24 months, and 4% were diagnosed with metastatic PCa at time of PNBx. Compared to men aged <50 years at first PSA, those 50-59 (aHR 1.08, 95% CI: 1.06-1.11) and [&ge;]60 years (aHR 1.79, 95% CI: 1.74-1.84) had higher metastatic PCa. Men with longer screening intervals had higher metastatic PCa (aHR 1.09, 95% CI: 1.07-1.11). Men aged <50 years with shorter screening intervals had lower metastatic PCa (aHR: 0.10, 95% CI: 0.09-0.12) compared to men aged [&ge;]60 years with longer screening intervals. Conclusions and RelevanceFew male veterans were observed to have the most favorable combinations of age, PSA value, and PSA screening interval in relation to metastatic PCa, suggesting potential for further screening optimization.

Background: Each year around 4,500 people in the UK receive an organ transplant. These surgeries can be life changing and life extending for patients but are also associated with significant costs for the health service. However, by reducing the need for other expensive interventions involved in non-transplant care for organ failure, such as dialysis, some of these costs may be recovered. Methods: We assessed the lifetime costs and benefits associated with transplantation focussing on deceased donor adult transplants for kidneys, livers, hearts, and lungs. We incorporated costs of organ retrieval, surgery, post-transplant secondary care, and medications, as well as impacts on quality and duration of life. These were compared to the cost of managing patients with end-stage organ failure for whom no transplant occurs. Results: Kidney transplants were found to be cost saving with lifetime costs approximately 220,000 GBP lower than alternative treatment. Heart transplants and liver transplants were found to be more cost-effective than thresholds used by NICE for new medicines at approximately 17,000 GBP to 18,000 GBP per quality adjusted life year gained. Lung transplants were the least cost-effective organ transplant with a cost per quality adjusted life year gained of over 50,000 GBP. Conclusions: Although transplants can be costly, not providing a transplant to a patient who needs one also brings significant costs. Kidney transplants can save the health system money by reducing the need for dialysis. Increasing the number of kidney's available for transplant could save the NHS money whilst saving and improving lives.

Crimean Congo hemorrhagic fever (CCHF) disease, caused by CCHF virus (CCHFV), poses a significant fatality risk whose underlying pathological mechanisms, including the contribution of coagulation factors imbalances and platelets abnormalities, remain poorly understood. Here we present a meta-analysis and meta-regression analysis using clinical data from coagulation assays and platelet parameters as predictive disease indices with the goal of uncovering pathognomonic factors and to pave a path for the development of effective therapeutic approaches. MethodsWe systematically analyzed published studies reporting coagulation assays and platelet indices in patients with confirmed CCHF. Data from 1,779 patients across published studies were analyzed to assess associations between laboratory parameters and fatality risk, while evaluating heterogeneity and prognostic significance. ResultsFatal outcomes were strongly associated with elevated liver enzymes (AST: 1116.71 {+/-} 1454.08 IU/mL; ALT: 446.56 {+/-} 457.41 IU/mL) and prolonged clotting times (PT: 19.53 {+/-} 6.57 s; aPTT: 64.02 {+/-} 23.13 s; INR: 1.53 {+/-} 0.56). D-dimer levels did not significantly predict fatality. Thrombocytopenia and coagulopathy emerged as independent risk factors for adverse outcomes. Notably, protein C and protein S levels did not differ between survivors and non-survivors, suggesting that the coagulopathy is not purely consumptive or a result of impaired hepatic synthesis. In contrast, mildly reduced antithrombin levels (83.65 {+/-} 19.90) were weighted toward increased mortality. Simple SummaryCrimean-Congo Hemorrhagic Fever (CCHF) causes high mortality through hemorrhage, but whether this reflects thrombocytopenia alone or combined coagulopathy remains unclear. We conducted meta-analyses of studies each of coagulation parameters (PT, aPTT, INR, fibrinogen, D-dimer, protein C and protein S, antithrombin) from survivors vs non-survivors. Fatal cases showed combined thrombocytopenia and coagulopathy (elevated PT/aPTT/INR, reduced fibrinogen/antithrombin) and liver damage (elevated AST/ALT). Protein C and protein S were unaffected, suggesting complex mechanisms beyond simple consumption or hepatic failure. These findings indicate coagulopathy contributes independently of thrombocytopenia to CCHF hemorrhage, supporting combined platelet and coagulation factor replacement therapy.

Background Acute kidney injury (AKI) is a major contributor to morbidity, mortality, and healthcare utilization among hospitalized adults. Long-standing racial and ethnic inequities in U.S. healthcare--including unequal access to care, neighborhood disadvantage, and other structural factors--are known to influence kidney health, yet national data describing how these inequities manifest in AKI remain limited. Methods We conducted a retrospective, cross-sectional analysis of the 2022 National Inpatient Sample. AKI was identified using ICD-10-CM codes N17.x, and race/ethnicity followed HCUP categories. Descriptive analyses compared characteristics across groups. Survey-weighted logistic regression estimated adjusted odds of developing AKI, in-hospital mortality among AKI patients, and dialysis use, adjusting for demographics, payer, and comorbidities. Age-specific predicted AKI probabilities were derived from the adjusted model. Results AKI prevalence ranged from 15% to 23% across racial and ethnic groups. After adjustment, Black (OR 1.34), Native American (OR 1.08), and Other patients (OR 1.07) had higher odds of AKI, whereas Asian/Pacific Islander (OR 0.94) and Hispanic (OR 0.98) had slightly lower or similar odds. Among AKI hospitalizations, mortality was modestly lower for Black and Hispanic patients relative to White patients and higher for Asian/Pacific Islander and Native American patients. All non-White groups had higher odds of dialysis use. Age-specific curves showed persistent risk differences across adulthood. Conclusions Substantial racial disparities in AKI incidence, mortality, and dialysis use persisted after adjustment, reflecting broader structural inequities. Addressing these gaps will require both targeted clinical strategies and policy interventions focused on upstream determinants.

We evaluated 2024/25 KP.2 vaccine effectiveness (VE) against COVID-19 hospitalization among adults >60 years old eligible for publicly-funded vaccination during fall and/or spring campaigns in the province of Quebec, Canada. We included Quebec residents tested for COVID-19-compatible symptoms in an acute-care hospital between October 13, 2024 (epi-week 2024-42) and August 23, 2025 (2025-34), linking vaccine, hospital, chronic diseases and laboratory administrative records to assess VE through test-negative design. We compared the odds of being COVID-19 test-positive versus test-negative among vaccinated versus non-vaccinated participants, adjusting for sex, age, comorbidities, place of residence, and epidemiological week. Overall, 49,949 (43%) participants were vaccinated. Over an analysis period spanning up to ten months, including median time since vaccination of 16 weeks (interquartile range 9-24 weeks), VE was 34% overall, declining from 43% <8 weeks to negligible by the 32nd week post-vaccination. Findings confirm meaningful but short-lived COVID-19 vaccine protection against hospitalization in older adults.

Household transmission of EV-D68 was identified in 35 of 1040 households (3.4%) in the Pacific Northwest between 2022-2024, with an estimated secondary attack rate of 15%. Sequences from within households clustered closely with 0 to 2 pairwise nucleotide differences (median 1) between cases 6-14 days apart (median 7).

BackgroundUnderrepresentation of minority groups in clinical trials worsens health disparities and reduces generalizability of results. Transthyretin-associated cardiac amyloidosis (ATTR), is a condition that disproportionately impacts some racial and ethnic groups yet the extent to which trial enrollment reflects disease burden remains unclear. Misalignment between disease prevalence and trial representation may delay treatment development and increase the economic burden of late diagnosis and mismanagement. MethodsThis was a systematic review of US-based ATTR clinical trials found on clinicaltrials.gov up to 2025 (search date February 12, 2025). Only completed trials with publicly available results were included. Demographic data were extracted at the trial level. An enrollment fraction (where EF = observed enrollment / expected enrollment based on Cardiac Amyloidosis Registry Study (CARS) prevalence; adequacy defined EF [&ge;] 0.75) was calculated for each group. ResultsOf the 264 clinical trials on ATTR identified, 16 met inclusion criteria. African Americans/Individuals of African descent had EFs below the adequate ratio of 0.75 in all phases of the trials reviewed compared to their Asian or White counterparts. Despite the FDA Final Rule in 2017, our study showed that there was increased study demographic reporting (60% to 85.7%), but a paradoxical decline for Black participants (EF 0.29 to 0.12, p < 0.001) and other minority participants. ConclusionsBlack individuals remain substantially underrepresented in U.S. ATTR-CM clinical trials despite improved demographic reporting after the 2017 Final Rule. Actionable strategies, community engagement, trial-site diversification, enrollment targets, and sponsor accountability are needed to improve representativeness and expand access.