Citations

Background: Heart failure with preserved ejection fraction (HFpEF) accounts for over half of all heart failure (HF) cases and remains diagnostically challenging due to nonspecific symptoms and a lack of accessible noninvasive screening tools, leading to widespread underdiagnosis and delayed treatment. The electrocardiogram (ECG) is a low-cost, widely available tool that reflects myocardial electrical remodeling. We previously developed and externally validated an ECG-based artificial intelligence (ECG-AI) model capable of classifying ECGs into four categories: reduced ejection fraction (rEF), mid-range ejection fraction (mEF), HFpEF, and controls. In this study, we evaluate the ability of this ECG-AI model to predict future HFpEF diagnosis using real-world data from a large integrated health system. Methods: We applied the validated ECG-AI model to an independent cohort of 7713 patients from Wake Forest Baptist Health (WFBH), using one ECG per patient recorded before the clinical diagnosis of HFpEF. Model discrimination was evaluated across multiple prediction windows from six months up to ten years before diagnosis using the area under the receiver operating characteristic curve (AUC), with comparisons performed using DeLong’s test. Performance was also compared head-to-head with the H2FPEF score, a validated clinical score for HFpEF, in the subset of patients with complete data for score calculation. ECG-AI outputs were stratified into quartiles and evaluated using Kaplan–Meier survival analysis and multivariable Cox proportional hazards regression adjusted for demographics and major comorbidities. Results: Of the 7713 patients, 283 (3.7%) were subsequently diagnosed with HFpEF. The ECG-AI model achieved an AUC of 0.79 (95% CI, 0.72–0.86) using ECGs recorded within six months before diagnosis. Discrimination remained stable across prediction windows extending up to ten years before diagnosis (AUC range, 0.78–0.80; all DeLong p > 0.01 vs. the six-month window). Compared with the H2FPEF score, ECG-AI demonstrated superior discrimination, improving the AUC by 0.06–0.07 across the evaluated prediction windows. Patients in the highest ECG-AI risk quartile had an unadjusted hazard ratio (HR) of 11.18 (95% CI, 7.27–17.21; C-index, 0.75) and an adjusted HR of 6.60 (95% CI, 4.24–10.28; C-index, 0.82). Adding clinical covariates to ECG-AI improved the C-index by 0.07 and 0.09 for the five- and ten-year prediction windows, respectively. Conclusions: An independently validated ECG-AI model predicted incident HFpEF up to ten years before clinical diagnosis and outperformed the H2FPEF score using ECG alone, indicating that ECG-derived signatures precede clinical recognition of the syndrome. ECG-AI shows promise as a prognostic, risk-stratification tool to prioritize further evaluation; prospective validation and single-lead assessment are needed before screening or wearable deployment.

Objective Respiratory syncytial virus (RSV) is an important viral pathogen in children, older adults and adults with certain high-risk conditions. In our prospective community-based cohort study of adults 50 years and older before the COVID-19 pandemic, the incidence of RSV acute respiratory infection (ARI) was 48.6 cases/1000 person-years (PY), which decreased to near zero during the COVID-19 pandemic. Our objective was to determine the incidence of RSV-ARI during the 2 years following the initial phase of the pandemic (2021–2022 and 2022–2023). Design This is a community-based prospective cohort study. Setting Adults living in southeast Minnesota from October 2021 to September 2022 (year 3) and October 2022 to September 2023 (year 4). Participants Adults≥50 years (n=2500). Primary and secondary outcomes We calculated incidence and attack rates for RSV-ARI as primary outcome and reported hospitalisations, pneumonia and death following ARI as secondary outcome. Results There were 2500 participants in the study with a mean age of 68.2 years (SD 9.3) at the start of year 3. Participants were predominantly female (60%), non-Hispanic white (96%) and residing in urban areas (76%). The incidence rate of RSV-ARI was 6.12/1000 PY (95% CI 3.42 to 10.09) in 2021–2022 and 16.40/1000 PY (95% CI 11.66 to 22.42) in 2022–2023. We noted higher attack rates of RSV-ARI during the winter months. There were no hospitalisations, pneumonia or deaths within 30 days of RSV-ARI. Conclusions Compared with the period before the COVID-19 pandemic, RSV-ARI incidence was lower in both 2021–2022 and 2022–2023 periods. In 2022–2023, the incidence increased 2.7-fold compared with the 2021–2022 period. The observed incidence rates, particularly the significant increase in the most recent season, underscore the continued public health relevance of RSV-ARI and support the rationale for ongoing RSV vaccination efforts to mitigate its overall burden in the population.

BACKGROUND. Survey research in critical care has dramatically increased over the past 25 years, and use of surveys within Delphi methods, which provide consensus definitions for heterogeneous disease states, has similarly expanded significantly. It is crucial for survey researchers to understand the nuances of survey development and expectations of information provided by surveys, to use them correctly. Few simple sources exist to guide development considerations to generate high-quality survey research. No studies to our knowledge exist that draw parallels between the principles of survey research as a guide within the Delphi process, as one potential conduit between a steering committee and expert panel. METHODS. We present a narrative review of and framework for rigorous design of survey research, highlighting the applicability to the design of surveys administered within Delphi methods. RESULTS AND CONCLUSIONS. The methodologic considerations presented for survey research and Delphi methods can inform high-quality critical care research.

G protein-coupled receptors (GPCRs) are among the most common drug targets, with numerous agonists and antagonists approved for clinical use. More recently, it has been appreciated that drugs can also modulate the action of natural agonists of these receptors, thus providing unique clinical advantages. Here, we describe the identification and characterization of a small molecule positive allosteric modulator (PAM) of secretin action at the class B G protein-coupled secretin receptor. This phenyl(trifluoromethyl)-pyrimidine can occupy the secretin receptor without stimulating its internalization, yet priming it to enhance both the potency and efficacy of the action of natural secretin. This is also shown to exhibit its effects on cells expressing low numbers of these receptors, without enhancing the effects of other structurally related hormones acting at other class B GPCRs. The mechanism responsible for this PAM effect is the slowing of the off-rate of receptor-bound secretin. This compound can serve as a lead to the development of other drugs that enhance the action of natural endogenous secretin and can be utilized to explore the potential therapeutic utility of such compounds.

Abstract INTRODUCTION Although cerebrospinal fluid (CSF) biomarkers reflect neurodegeneration in Alzheimer's disease (AD), it remains unclear whether these biomarkers track neurodegeneration in early‐onset Alzheimer's disease (EOAD). METHODS In 80 EOAD patients, we examined correlations between eight CSF biomarker levels and cortical thickness decreases within the EOAD cortical atrophy signature. Significant correlations were then entered into a multiple regression analysis. We also examined contributions of EOAD atrophy and CSF biomarkers to cognitive impairment. RESULTS The levels of four CSF biomarkers correlated to EOAD signature atrophy. Stepwise regression analyses revealed that CSF neurofilament light chain (NfL) levels best predicted EOAD signature atrophy. Multiple regression showed EOAD signature atrophy combined with CSF NfL levels explained more variance in cognitive impairment than either factor alone. DISCUSSION Within EOAD patients, CSF NfL levels relate to the magnitude of cortical atrophy, and a combination of EOAD signature atrophy and CSF NfL levels most robustly predict cognitive impairment.

Acute myeloid leukemia (AML) pathogenesis is deeply rooted in the concept of clonal evolution, in which hematopoietic stem cells experience an initial genetic insult, followed by the sequential acquisition of mutations leading to various disease phenotypes. Through natural selection, a malignant clone can diversify and propagate with time. Aside from clonal evolution, a number of time-honored principles of molecular oncology account for the initiation and maintenance of AML. These principles include loss of heterozygosity, genomic instability, epigenomic disruption, deregulation of signaling pathways, anti-apoptotic mechanisms, and oncogene addiction. Such tenets of cancer biology not only explain AML cellular behavior but also may inform target validation in AML. Herein, we highlight the current state of targeted therapeutics, including the 14 novel agents (beyond 7+3 chemotherapy) approved by the Food and Drug Administration, in the context of these tenets and discuss future prospects by leveraging current knowledge of AML genomics. Such therapeutic concepts, including synthetic lethality, are especially relevant to TP53-mutant AML, as there are no unique therapies that have received regulatory approval for this subset to date. We emphasize the emerging role of single-cell genomics and multi-omics toward better understanding of AML biology and development of future successful AML therapies.

Abstract Background Breast cancer is etiologically heterogeneous, but which risk factors differ in their associations across tumor subtypes remains unclear. We conducted a large, pooled analysis to evaluate independent, dose-response associations between breast cancer risk factors and quantitative tumor features. Methods Analyses of 15,731 invasive breast cancers from 24 studies evaluated associations (p-trend) between reproductive and hormonal factors, body mass index (BMI), alcohol, smoking, and family history in relation to quantitative immunohistochemistry measures on tissue microarrays (ER, PR, HER2, KI67, TP53) and tumor grade. Analyses in a subset of 10 population-based studies estimated subtype-specific odds ratios (ORs) comparing cases to controls. A Bayesian False Discovery Probability (BFDP) <0.2 was used to identify associations with strong statistical evidence. Results Nulliparity and later age at menopause were associated with higher ER-positivity (p-trend=0.021 and 0.001, respectively), with corresponding OR[ER+] (95% CI) = 1.49 (1.16-1.90) for nulliparous vs. parous and 1.07 (1.03-1.11) per 5 years. Current combined menopausal hormone therapy (MHT) use was associated with lower grade (p-trend<0.001), with OR [grade1] = 3.37 (2.69-4.21) for current vs. never users. Higher BMI was associated with lower ER-positivity and higher grade in premenopausal women (p-trend<0.001 and <0.001), with OR[ER+] = 0.80 (0.74-0.87) and OR[grade1] = 0.75 (0.63-0.88) per 5 units, and with higher PR-positivity and higher grade in postmenopausal women (p-trend<0.001 and <0.001), with OR[PR+] = 1.08 (1.03-1.14) and OR[grade 3] = 1.10 (1.04-1.17) per 5 units. Conclusion This pooled analysis of 15,731 cases showed that nulliparity, age at menopause, MHT, and BMI have independent, dose-response associations with ER, PR, and grade, clarifying patterns of etiologic heterogeneity. Associations with HER2, KI67 and TP53, or other risk factors did not meet our threshold for strong evidence.

Background: Prior studies have reported higher rates of periprosthetic fracture, superficial infection, and neurologic deficit with the direct anterior approach (DAA), and higher rates of dislocation with the posterior approach (PA) for total hip arthroplasty (THA). Despite these differences, the overall clinical burden of complications between approaches remains unclear. The purpose of this study was to compare the profiles, severity, impact, and resolution of 5 clinically important complications between DAA and PA THA. Methods: A retrospective review was conducted of 11,783 consecutive primary THAs performed between 2010 and 2021 across 3 centers within a single healthcare system, using either the DAA (n = 4,451) or the PA (n = 7,332). Complications assessed included dislocation, infection, periprosthetic fracture (PPFx), aseptic loosening, and neurologic deficit. Severity was graded using the Clavien-Dindo classification (I = minor, V = death). Impact was defined by reoperation burden, and outcomes were categorized as resolved or persistent. Kaplan-Meier survivorship and propensity-weighted Cox proportional hazards models were used to compare complication risk. Results: The overall 1-year risk of surgical complications did not differ between DAA and PA (hazard ratio [HR], 0.89; 95% confidence interval [CI], 0.75-1.06; p = 0.208). Dislocation occurred more frequently with PA THA than DAA THA (1.9% vs. 0.4%; HR, 5.20; 95% CI, 3.04-8.90; p < 0.001). Superficial infections were more frequent with the DAA (1.6% vs. 0.8%; HR, 2.43; 95% CI, 1.68-3.53; p < 0.001). The risk of deep infection, PPFx, aseptic loosening, and neurologic deficit did not differ significantly between approaches. Among patients with complications, the proportion classified as severe (Clavien-Dindo III–V) was similar, and adjusted analyses showed no difference in the odds of severe complications (adjusted odds ratio 1.34 for PA vs DAA; 95% CI, 0.95-1.91; p = 0.099). Complication impact and resolution were likewise comparable. Conclusion: Although the profile of complications differed between DAA and PA THA, the severity, early clinical impact, and resolution of complications appeared similar. Notably, DAA was associated with a lower risk of dislocation and a higher risk of superficial infection compared with PA THA. Level of Evidence: Level III , Retrospective Comparative Study. See Instructions for Authors for a complete description of levels of evidence.