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Scientific evidence regarding AKI and acute kidney care has advanced in recent years. However, a knowledge gap remains on the implementation of these evidence-based practices (EBPs) into clinical care. Implementation science (IS) is focused on ensuring that this knowledge is translated in an effective, efficient and sustainable fashion. Objectives: 1) Define the current status of IS; 2) Define a roadmap for accelerating IS with a focus on patient/care partner advocacy, digital tool application, social determinants of health, and resource-limited settings; and 3) Develop a robust and broad research agenda incorporating IS methodology into the programs. Evidence Review: ADQI XXXV was conducted through a modified Delphi process with virtual meetings preceding an in-person meeting. Five workgroups were determined a priori to focus on 1) IS definitions and methods applicable to AKI and acute kidney care; 2) IS literature in AKI and acute kidney care; 3) Innovations in IS to accelerate the adoption, adherence to, and sustainment of EBPs in AKI and acute kidney care; 4) IS methods in resource-limited settings; and 5) Recommendations to identify and evaluate EBPs that are ready for implementation or de-implementation. Prior to the in-person meeting, each workgroup met virtually to review the literature and develop framework questions to address their objectives. During the two-day in person meeting, through iterative discussions, questions and supporting statements were finalized. These questions and statements were agreed upon through voting to achieve consensus, defined as agreement of ≥80%. Conclusions and Relevance: We report a structured multidisciplinary consensus for defining the role of IS in AKI and acute kidney care. Future programs should address these consensus questions and apply these statements along with IS methodology in the translation of science into clinical practice and the implementation/de-implementation of EBPs in clinical care.

Abstract Background Existing formal feedback systems in graduate medical education often rely heavily on intangible Likert Scales linked to ACGME milestones as an end-of-rotation summative assessment. However, more frequent, actionable, formative feedback based on observations is essential to personal growth. Objective To evaluate the impact of changing from a milestone-based evaluation form to a brief narrative-based feedback form in a Pulmonary Disease and Critical Care Medicine (PCCM) fellowship as an exploratory pilot project. Our aim was to describe change in perception of feedback quality and the impact on Clinical Competency Committee (CCC) decisions. Methods We compared the quality of written rotation feedback before and after implementing a shorter feedback form on January 1, 2024 for 15 PCCM fellows at a single large academic institution using the Quality of Assessment for Learning (QuAL) score, (July 2023-December 2023 compared to January 2024-July 2024), fellow pre- and post-surveys (December 2023 and June 2024) and a CCC focus group (June 2024). Results Overall QuAL score improved significantly after narrative-based feedback form implementation (2.71 pre [n = 75] vs 3.70 post [n = 85], p < 0.001). Surveys had 13/14 (92.8%) fellows respond pre-intervention and 8/14 (57.1%) post-intervention. There was significant improvement in the number of fellows indicating they could identify new learning goals based on written feedback after implementation of the new form (23.1% pre vs 75.0% post, p = 0.03). The CCC focus group with 5 of 8 eligible faculty participating described milestone decisions were better supported by more detailed narratives. Conclusions Implementing a brief narrative-based form improved feedback quality and the number of trainees able to create learning goals. The CCC identified that the new form provided better details to support milestone recommendations.

Importance Although adding immune checkpoint inhibitors to neoadjuvant chemotherapy improves outcomes in high-risk early-stage breast cancer, opportunities remain to further enhance response. Dual checkpoint blockade offers a potential strategy to further enhance efficacy. Objective To evaluate the combination of anti−programmed cell death 1 protein (PD-1) cemiplimab and anti−lymphocyte activation gene 3 (LAG-3) added to neoadjuvant therapy in ERBB2 -negative early-stage, high-risk breast cancer. Design, Setting, and Participants The I-SPY2 (Investigation of Serial Studies to Predict Your Therapeutic Response With Imaging and Molecular Analysis 2) is an ongoing randomized clinical platform trial being conducted at multiple US clinical sites including patients with early-stage (II or III) ERBB2 -negative, high-risk breast cancer. Participants, continuously enrolled since 2010, were adaptively randomized from February 2, 2020, to December 9, 2021, to one of several experimental neoadjuvant therapies or control groups based on receptor subtypes defined by hormone receptor (HR), ERBB2 status, and MammaPrint (Agendia Inc) molecular risk, categorized as high (MP1) or ultrahigh (MP2). Data were analyzed from January 1, 2022, to August 5, 2025. Interventions Both groups received weekly paclitaxel for 12 weeks, then doxorubicin and cyclophosphamide followed by surgery; concomitant with paclitaxel, the intervention group also received 4 doses of cemiplimab and fianlimab (PCF) every 3 weeks. Main Outcomes and Measures Pathologic complete response (pCR). Treatments graduated when they achieved 85% bayesian probability of success in a subtype-specific phase 3 trial. Pathway-specific biomarkers were assessed for response prediction. Results A total of 78 participants (mean [SD] age, 47 [39-54] years) were randomized to the intervention group, with 350 participants (mean [SD] age, 48 [39-57] years) randomized to the historical control population. PCF graduated in all clinical signatures, with pCR rates vs control of 44% (95% CI, 34%-53%) vs 21% (95% CI, 17%-25%) in all ERBB2 , 53% (95% CI, 39%-67%) vs 29% (95% CI, 22%-36%) in triple-negative, and 36% (95% CI, 23%-49%) vs 14% (95% CI, 9%-19%) in HR-positive and ERBB2 -negative disease. Among the total participants, 16 (21%) experienced adrenal insufficiency, including hypophysitis (11% grade 3 or 4), mostly occurring after immunotherapy completion. PCF was found to be highly effective in the subset of patients with immune signature positive status (ImPrint positive). Conclusions and Relevance In this randomized clinical trial, the combination of PD-1 and anti−LAG-3 inhibition with standard NAC was effective in early-stage ERBB2 -negative breast cancer, particularly in patients displaying a positive ImPrint immune signature. These results warrant further definitive trials. Trial Registration ClinicalTrials.gov Identifier: NCT01042379

Abstract Introduction Distinct temperature patterns have long been recognized to correlate with fevers of differing etiologies. While the use of wearable sensors for high-frequency temperature monitoring (HFTM) on a near minute-by-minute basis has been shown to detect fevers earlier than standard-of-care nursing vital sign assessments in hospitalized patients, leveraging these high-resolution datasets to computationally identify unique digital signatures for real-time diagnosis of underlying fever etiology has not been widely explored. Diagnostic uncertainty is common in patients undergoing hematopoietic stem cell transplantation (HCT), with only 20–30% of febrile neutropenic episodes being microbiologically documented. We hypothesized that unique temperature patterns extracted from HFTM data collected during episodes of febrile neutropenia could be used to develop a supervised machine learning classifier capable of accurately predicting underlying fever etiology in HCT patients. Methods We analyzed 68 clinically independent fever episodes recorded in HCT patients (n=90) outfitted with an FDA-cleared wireless temperature sensor (TempTraq®, BlueSpark Technologies) that measured axillary temperature every 2 minutes throughout hospitalization. Time-series features were extracted from temperature traces spanning 1 hour before to 3 hours after fever onset and used to train a suite of machine-learning models to distinguish engraftment fevers from other fever etiologies. Model training and evaluation were performed using repeated stratified 5-fold patient-level cross-validation, yielding 100 train-test evaluations. Results Among all classification models, the logistic regression classifier provided the best overall performance and interpretability, achieving 94% specificity (95% CI, 0.84–1.0) for identifying engraftment fevers with a mean AUROC of 0.88 ± 0.10. Feature importance analysis demonstrated that both clinical variables and HFTM-derived temperature dynamics contributed to model performance, with a strong reliance on time-series features captured within the first 4 hours of fever onset. Conclusion Our study provides a demonstration that continuous temperature data collected from patients outfitted with wearable sensors can be leveraged not only for early fever detection but also for machine learning–based diagnosis of fever etiology. These findings suggest that dynamic temperature patterns contain clinically meaningful physiologic information that with further studies could support real-time diagnostic decision-making and guide safe de-escalation of empiric antibiotics during febrile neutropenia in patients undergoing intensive cancer therapy.

ABSTRACT Background Genetic testing for cardiomyopathy and arrhythmia (CM/ARRH) provides diagnostic information and informs screening for at-risk relatives. Clinical guidelines recommend genetic testing for these conditions; however, data on how genetic test results influence clinical management recommendations are limited. Here, we determined the frequency of cardiologist-recommended management changes for patients following CM/ARRH genetic testing. Methods This was a retrospective cross-sectional study of patients referred for multigene panel testing between April 2016 and April 2024. Genetically-experienced cardiologists at multicenter academic clinical practices were recruited for participation to complete surveys indicating clinical decision making on patients who had genetic testing. Cases for review were randomly selected to have both positive and non-positive results. Results Among 249 patients (138 positive, 111 non-positive), 136 (54.6%) received clinical management recommendations for their own or their at-risk relatives’ care. Of these, 75 (55.1%) received recommendations for the patient’s own care, most frequently additional diagnostic tests/procedures (n=33). Compared to non-positive results, patients with positive results were more likely to receive recommendations for their own management (66/138, 47.8% vs 9/111, 8.1%; P<0.00001). Patients with positive results in arrhythmogenic cardiomyopathy genes had 263% higher odds of recommended management changes compared to those with TTN (OR=3.63, CI:1.40-9.84, P=0.009). Conclusions The results from CM/ARRH genetic testing on affected patients influenced cardiologists’ medical decision making and management recommendations. Additional research is needed to evaluate how genetic testing for CM/ARRH impact health outcomes.

Importance Limited granular data exist on breast cancer in transgender, nonbinary, and/or gender-diverse (TGD) individuals. Objective To describe patient demographic and tumor clinicopathological variables, clinically relevant risk factors, method of breast cancer detection, treatment characteristics, and locoregional outcomes and to estimate a 5-year breast cancer–specific survival (BCSS). Design, Setting, and Participants This cohort study obtained data on patients treated from 1990 to 2023 from 22 US academic medical centers using institutional databases, electronic medical records, and tumor registries. Included participants were TGD individuals 18 years or older with stage 0 to IV breast cancer. A comparative breast cancer cohort was selected from the 2016 to 2021 Surveillance, Epidemiology, and End Results Program (SEER) breast cancer dataset. Data were analyzed from January to October 2025. Exposure Breast cancer. Main Outcomes and Measures Estimated 5-year BCSS and locoregional recurrence rates. Wilcoxon rank sum and χ 2 tests were used to compare continuous and categorical variables. Kaplan-Meier analysis was used to estimate 5-year BCSS. Results A total of 112 TGD persons (median [IQR] age at diagnosis, 42.5 [36.5-51.0] years; 104 individuals [92.9%] were assigned female at birth) with breast cancer and 1 with bilateral disease were included in the analysis. Forty-three patients (38.4%) used gender-affirming hormone therapy before diagnosis. Among the entire cohort, 58 patients (51.8%) detected their own breast cancer, 68 (60.7%) had a familial breast cancer history, and 16 (14.3%) had a pathogenic germline variant. Tumors were predominantly hormone receptor positive (96 [85.7%]) and early stage (29 [25.7%] ductal carcinoma in situ [DCIS]; 51 [45.1%] stage I). The TGD cohort, compared with patients with breast cancer in the SEER dataset (N = 480 915), was younger (median [IQR] age, 42.5 [36.5-51.0] years vs 62.0 [52.0-72.0] years), had a higher proportion of persons assigned male at birth (8 [7.1%] vs 3522 [0.7%]), more often had progesterone receptor–positive disease (89 [79.5%] vs 335 491 [69.8%]), and presented with earlier-stage disease (eg, DCIS: 29 [25.9%] vs 79 604 [16.6%]). With a median (IQR) follow-up time for the TGD cohort of 38 (24-74) months, 5-year BCSS was favorable at 96.2% (95% CI, 85.3%-99.0%). Conclusions and Relevance This cohort study of TGD patients with breast cancer found that this population was young and often detected their own tumors via self-examination, suggesting opportunities to improve early detection through screening for individuals at elevated risk. Although short-term BCSS appeared favorable, prospective research is essential to define evidence-based guidelines and elucidate long-term outcomes.

BACKGROUND: White matter hyperintensities (WMH) are widely used to assess cerebral small vessel disease but reflect late-stage injury. Diffusion magnetic resonance imaging (MRI) biomarkers have been proposed to capture earlier small vessel disease-related microstructural damage but their temporal progression relative to WMH and risk factors associated with progression remain unexplored. METHODS: We identified 2077 participants from the population-based cohort study of the Mayo Clinic Study of Aging in Olmsted County, Minnesota (aged 50–101 years) collected between 05/2005 and 09/2024 with longitudinal neuroimaging. Using multioutput nonlinear mixed-effects models in those with at least 2 fluid-attenuated inversion recovery-MRI and diffusion MRI scans, we characterized the temporal progression of WMH and 4 diffusion MRI biomarkers: fractional anisotropy of the genu of the corpus callosum, peak width of skeletonized mean diffusivity, free water, and Arteriolosclerosis-score, which were automatically estimated. Models incorporated participant-specific time shifts, correlations between biomarkers, and effects of risk factors (sex, education, APOE ε4 status, cardiometabolic conditions). RESULTS: The study population had a mean age of 78 years, 47% were women, 28% were APOE ε4 allele carriers, and 80% were cognitively unimpaired, with an average follow-up of 5.2 years (SD, 4.3 years) for fluid-attenuated inversion recovery-MRI and 4.3 years (SD, 3.9 years) for diffusion MRI. Arteriolosclerosis-score, fractional anisotropy of the genu of the corpus callosum, free water, and peak width of skeletonized mean diffusivity became abnormal in 50% of the study population 16, 12, 10, and 7 years before WMH become abnormal (half-width of CI <1 year), respectively. Global markers (Arteriolosclerosis-score, free water, peak width of skeletonized mean diffusivity, and WMH) were correlated, indicating shared substrates of widespread white matter injury. Fractional anisotropy of the genu of the corpus callosum, a vascular risk microstructural injury biomarker, was weakly coupled with WMH and had an earlier but more linear worsening across adulthood. Cardiometabolic conditions predicted earlier worsening of all biomarkers. Female participants showed earlier WMH, fractional anisotropy of the genu of the corpus callosum, and Arteriolosclerosis-score abnormalities, whereas male participants exhibited earlier peak width of skeletonized mean diffusivity and free water abnormalities. CONCLUSIONS: Diffusion MRI biomarkers were abnormal at least a decade before WMH become abnormal in the population, revealing a prolonged phase of early small vessel disease and highlighting their potential for small vessel disease prevention.

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.

Abstract Physical activity (PA) is a modifiable lifestyle behaviour associated with lower dementia risk; however, molecular pathways bridging PA-related dementia prevention are poorly understood. We leveraged large-scale plasma proteomics to identify biological signatures of objectively monitored PA and cognitive ageing in functionally intact older adults, cross-validated these signatures in independent exercise cohorts and tested associations with both symptomatic and presymptomatic stages of neurodegeneration across multiple Alzheimer’s disease and related dementias (ADRD) cohorts. We analysed large-scale plasma proteomics data (SomaScan 7k) across three cohorts including naturalistic, objective PA monitoring (University of California, San Francisco Brain Aging Network for Cognitive Health cohort, n = 65), self-reported PA (Atherosclerosis Risk In Communities study, n = 10 644) and PA intervention (Health Risk Factors, Exercise Training and Genetics study, n = 654). Differential regression models examined individual protein correlates of PA, adjusting for age and sex. Weighted gene co-expression network analysis assembled proteins into unbiased modules of protein co-expression, which were annotated for gene ontology and cell-type enrichment. To test clinical relevance to ADRD, we examined PA-related protein levels across-cohorts of symptomatic Alzheimer’s disease and Parkinson’s disease (Stanford Alzheimer’s Disease Research Center), as well as frontotemporal dementia-spectrum disorders (ARTFL/LEFFTDS Longitudinal Frontotemporal Lobar Degeneration consortium). PA-related plasma proteins were also tested as predictors of antemortem cognitive change and post-mortem brain tissue mass spectrometry proteomic signatures in brain donors from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) cohort. Differential regression and network analyses identified PA plasma proteomic signatures linked to cell adhesion/extracellular matrix (ECM), immune response and lipid metabolism. Protein co-expression module M12 ECM/neurodevelopment harboured growth factor, cell adhesion and vascular remodelling proteins that (i) were positively associated with PA across exercise cohorts, (ii) positively associated with cognitive function and (iii) negatively associated with Alzheimer’s disease, Parkinson’s disease and frontotemporal dementia. Furthermore, M12 was enriched for proteins from Alzheimer’s disease risk genes and antemortem plasma abundance of anthrax toxin receptor cell adhesion molecule 2 (ANTXR2), an M12 ‘hub’ protein and top PA hit across-cohorts, forecasted longitudinal global cognitive decline and post-mortem brain tissue signatures of synaptic function and proteolysis in ROSMAP. Collectively, our integrated systems biology analysis of six independent plasma proteomic datasets facilitated discovery and validation of blood-detectable molecular signatures of PA and neurodegenerative disease, including PA-related proteins with clinical and biological relevance to early stages of disease. Circulating levels of PA-related proteins reflecting ECM biology (e.g. ANTXR2) may represent key molecular targets for dementia prevention.