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Objective To evaluate the clinical effectiveness of sodium glucose cotransporter 2 (SGLT2) inhibitors in reducing the risk of hospital admission for heart failure and mortality in a contemporary nationwide cohort of patients with heart failure with preserved ejection fraction (HFpEF). Design Nationwide cohort study (REFINE-HFpEF). Setting 170 veteran health medical centres across the US, 1 January 2014 to 31 December 2021. Participants 2177 patients with type 2 diabetes and HFpEF; 1129 patients were newly prescribed SGLT2 inhibitors and 1048 were newly prescribed dipeptidyl peptidase 4 (DPP4) inhibitors or sulfonylureas. Main outcome measures The primary outcome was a composite of all cause mortality and hospital admission for heart failure. Secondary outcomes included all cause mortality only and serial changes in body weight. Hazard ratios were derived from Cox proportional hazards models, incorporating inverse probability of treatment weighting based on propensity scores to account for confounding. Results From a validated cohort of 179 288 patients with type 2 diabetes and HFpEF, the study included 1129 new users of SGLT2 inhibitors (active treatment) and 1048 new users of DPP4 inhibitors or sulfonylureas (comparators). After a median follow-up of 2.63 years, 46.4% of the study population had at least one hospital admission for heart failure (n=1011) and the overall mortality rate was 45.9% (n=1000). Use of SGLT2 inhibitors was associated with a relative risk reduction in the primary composite outcome of 18% compared with the use of DPP4 inhibitors or sulfonylureas (hazard ratio 0.82, 95% confidence interval 0.70 to 0.96; P=0.01). The adjusted hazard ratio for all cause mortality only was 0.73 (0.60 to 0.89; P=0.002). Weight loss was similar in the two groups. Conclusions In this large, contemporary, nationwide cohort of patients with HFpEF, type 2 diabetes, and high event rates, starting SGLT2 inhibitors was associated with a significantly lower risk of hospital admission for heart failure and all cause mortality compared with starting treatment with DPP4 inhibitors or sulfonylureas.

Abstract. Introduction: Preterm birth drives adverse perinatal maternal and infant health outcomes through heterogeneous symptoms, severity, and etiologies. Delivery prior to reaching 37 weeks of gestation may result from medically indicated intervention for pregnancy complications or spontaneously in the absence of prior symptoms. Placental tissue collected following preterm birth exhibits differential DNA methylation compared to full-term placentas and may indicate pregnancy health during gestation. Placental DNA currently has limited utility for assessing health of ongoing pregnancy, as sampling placental tissue during gestation increases the risk of infection and miscarriage. Risks associated with placental sampling during pregnancy limit the use of DNA methylation in clinical preterm birth prediction. Assessing preterm birth risk during gestation requires non-invasive methods for characterizing placental DNA methylation. Results: We quantified genome-wide DNA methylation patterns of hypermethylated cell-free DNA in pregnant (n = 99) and non-pregnant (n = 93) plasma using cell-free methylated DNA immunoprecipitation sequencing (cfMeDIP-seq). In each sample, we assessed DNA methylation status in 300-bp genomic windows, examining both sequencing read counts and calculated absolute molar DNA amount. Known hypermethylated placental regions, including RASSF1, STAT5A, and ERG promoters showed significantly increased odds of detection in pregnant samples, suggesting enrichment of cell-free placental DNA. Of the 536,444 300-bp windows examined, 173,071 (32%) showed significant enrichment in pregnant plasma. Linear modeling identified 107,505 differentially methylated regions (DMRs) associated with pregnancies later diagnosed with intrauterine growth restriction (IUGR) (n = 22). Alu elements showed increased representation in these DMRs than expected, while other repetitive elements exhibited underrepresentation. Discussion: These results demonstrate cfMeDIP-seq's ability to enrich for cell-free placental DNA and characterize cell-free DNA methylation signatures of pregnancies complicated by IUGR. Enrichment of cell-free placental DNA enables non-invasive profiling of placental DNA methylation from maternal plasma. Detectable epigenetic signatures in maternal plasma may identify pregnancies at elevated risk for preterm birth before clinical symptoms appear. Our findings further highlight the potential of cell-free placental DNA for monitoring pregnancy health.

Objectives: Rates of locoregional recurrence and distant metastases are high following curative-intent resection for patients with localized pancreatic adenocarcinoma. Adjuvant therapies have been investigated with the intent to reduce the risk of recurrence and improve OS. The objective of this study is to update and summarize the current evidence for adjuvant therapy following surgical resection for nonmetastatic PDAC with a focus on high-level evidence and randomized controlled trials is provided. Methods: This multispecialty-led committee included gastrointestinal radiation and medical oncology, gastroenterology, radiology, and surgical oncology. Using the population, intervention, comparator, outcome, timing and study design framework, evidence regarding treatment outcomes was assessed using Cochrane and PRISMA methodology. Eligible studies included prospective and retrospective (n≥25) studies published between January 1, 2013 and February 13, 2026, from Ovid MEDLINE, Ovid EMBASE, Ovid Cochrane Database of Systematic Review, and Scopus databases. Study type and quality were assessed. Well-established RAND/UCLA consensus methodology (modified Delphi) was used to rate the appropriateness of the treatment options. Results: Of the 74 references used as evidence, 74 are categorized as therapeutic references. Study type and quality for the references were assessed, and included 31 well-designed studies (phase II randomized and phase III), 14 moderately well-designed studies that account for most common biases (matched cohort and phase II studies), 28 studies with design limitations (retrospective reviews), and 1 reference meta-analysis. Conclusions: This systematic review and guidelines provide up-to-date recommendations focusing on recent advancements for adjuvant treatment of resected PDAC using modern systemic therapy regimens and selective use of radiotherapy using modern techniques.

Cardiac allograft vasculopathy (CAV) remains a leading cause of graft failure after heart transplantation, yet an early, non-invasive risk stratification tool is not available. Artificial intelligence electrocardiography (AI-ECG) can estimate biological heart age, and it has been associated with cardiovascular risk. Its deviation with chronological age, called delta age, and its utility in the prediction of CAV has never been explored. We conducted a retrospective single-center study for heart transplant recipients bridged with Impella 5.5 (Abiomed, Danvers, MA, USA) at Mayo Clinic Florida (2020–2023). ΔAge was calculated at discharge and 1-year post-transplant. The primary outcome was confirmed CAV at 1 year. Univariate and multivariable logistic regression models were used to assess the independent association between the ΔAge and the development of CAV, with discrimination evaluated by AUC and internally validated via bootstrap resampling (2000 iterations). Fifty patients were reviewed. CAV developed in 13 (26%) patients in 3 years. CAV+ patients had a significantly higher ΔAge at discharge compared to CAV- patients (median −1.0 vs. −11.0 years, p = 0.0023) and at 1 year (median +7.0 vs. −4.0 years, p = 0.0080). On univariate analysis, ΔAge at discharge was a significant predictor of the development of CAV (OR 1.084 per year, AUC 0.788). On multivariable adjustment, ΔAge at discharge remained an independent predictor (adjusted OR 1.138, 95% CI 1.023–1.265, p = 0.018, and model AUC 0.859). ΔAge at discharge is a novel and potential predictor of the development of CAV within 3 years. These findings support the integration of AI-ECG into post-transplant surveillance as a scalable, low-cost tool.

Abstract Background Synthetic control arms (SCAs) derived from historical trial data can complement randomized controlled trials (RCTs), particularly in oncology where feasibility, ethical, and cost constraints may limit conventional trial designs. However, their validity for overall survival (OS) remains uncertain. We evaluated the feasibility and limitations of constructing SCAs from the ARCAD metastatic colorectal cancer (mCRC) database across multiple treatment lines. Methods Seven landmark RCTs representing first-, second-, and third-line settings were selected. External control arms were constructed from ARCAD individual patient-level data using propensity score matching based on key clinical and biological variables from a validated ARCAD prognostic score, with adjustment for geographic region and time era when needed. A prespecified two-step benchmarking framework assessed: (1) control-arm OS reproducibility and (2) virtual trial comparisons between matched synthetic controls and original RCT experimental arms. Agreement was evaluated using hazard ratios (HRs) and Z-tests. Results A total of 28,022 patients met the inclusion criteria. ARCAD-derived SCAs were successfully constructed for all selected RCTs and closely reproduced control-arm OS. After matching, baseline characteristics were well balanced, with minimal differences between included and excluded patients. Virtual trials showed concordant treatment-effect estimates with the original RCTs, with a median absolute HR deviation of 0.05 and no significant differences by Z-tests (P>.05). Survival outcomes were consistently reproduced across treatment lines. Conclusion ARCAD-derived SCAs reliably reproduced control-arm OS and benchmark treatment-effect estimates from landmark RCTs in mCRC. Despite limitations related to residual confounding and missing data, this framework supports benchmarking, trial design, and exploratory analyses when conventional control arms are impractical.

Background We examined the relationship between infection‐related hospitalization (IRH) and heart failure (HF) in a large clinical health system and assessed whether IRH improved prediction beyond HF risk equations. Methods We studied 80 880 adults (14 150 with IRH and 66 730 age‐ and sex‐matched comparators) aged ≥18 years without HF in the Rochester Epidemiology Project from 1/1/2005–12/31/2019. IRH was identified using International Classification of Diseases ( ICD ) codes. HF incidence was defined as ≥1 HF‐related ICD code. Multivariable Cox models assessed the association between IRH and incident HF. Among 29 219 adults aged 30 to 79 years without baseline cardiovascular disease in the Rochester Epidemiology Project, Harrell's concordance statistic assessed whether IRH improved discrimination of the Predicting Risk of Cardiovascular Disease EVENTs–Heart Failure (PREVENT‐HF) equations. Results Participants were 53.3% women, 85.6% White individuals, and 95.1% non‐Hispanic individuals, with a mean age of 56.0±20.0 years. Median follow‐up time was 6.2 years. Among the IRH group, 2729 developed incident HF (2.75/100 person‐years) versus 4854 (1.00/100 person‐years) in the comparator. The multivariable adjusted hazard ratio for incident HF among participants with versus without an IRH was 1.85 (95% CI, 1.76, 1.94). In a separate cohort, incorporating IRH into PREVENT‐HF increased the concordance statistic from 0.776 to 0.779 (change, 0.003 [95% CI, 0.001–0.004]). The PREVENT‐HF risk score underestimated the 10‐year risk of HF by up to 9% among participants with an IRH. Conclusions IRH was associated with incident HF but provided negligible change to 10‐year HF risk discrimination. However, among individuals with an IRH, incorporating this information meaningfully improved 10‐year HF risk prediction. Severe infections may serve as a risk‐enhancing factor warranting enhanced preventive measures, particularly in populations where IRH is more common.