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Importance Anemia is a common complication of surgery and acute illness that is associated with adverse clinical outcomes. The role of anemia prevention and treatment strategies in this setting remains unclear. Objective To evaluate the effect of a multifaceted anemia management bundle vs standard care on posthospitalization hemoglobin recovery and multidimensional functional outcomes in survivors of acute illness. Design, Setting, and Participants This parallel group randomized clinical trial, known as the Practical Anemia Bundle for Sustained Blood Recovery, was conducted at postsurgical and medical intensive care units at a large US medical center. Critically ill patients (aged ≥18 years) with moderate to severe anemia (hemoglobin concentration <10 g/dL) were enrolled between March 2022 and November 2023. Participants were randomly assigned 1:1 to the intervention or standard care group. Intention-to-treat analyses were performed between July 2024 and January 2025. Intervention The intervention bundle was delivered throughout the duration of hospitalization and included optimized phlebotomy practices, clinical decision support, and pharmacological anemia treatment with intravenous iron. Main Outcomes and Measures The primary outcome was the mean difference in hemoglobin concentration at 1 month after hospital discharge. Results A total of 100 patients (median [IQR] age, 68 [61-72] years; 57 men [57.0%]; 65 [65.0%] with postsurgical admission to the intensive care unit) were enrolled during acute illness. Forty-nine patients (49.0%) were assigned to receive the intervention, and 51 (51.0%) were assigned to receive standard care. Hemoglobin concentration at 1 month after discharge was greater in patients receiving the intervention vs standard care (median [IQR], 12.2 [11.8-13.0] g/dL vs 11.5 [10.2-12.6] g/dL; adjusted mean difference, 0.69 [95% CI, 0.13-1.20] g/dL; P = .02). Conclusions and Relevance This randomized clinical trial found that a multifaceted anemia prevention and treatment bundle was feasible, was well tolerated, and improved posthospitalization hemoglobin concentrations up to 3 months in critically ill adults. These findings can inform the design of future trials. Trial Registration ClinicalTrials.gov Identifier: NCT05167734

BACKGROUND: Patients presenting with cervical artery dissection (CAD) are at risk for subsequent ischemic events. We aimed to identify characteristics that are associated with increased risk of ischemic stroke after initial presentation of CAD and to evaluate the differential impact of anticoagulant versus antiplatelet therapy in these high-risk individuals. METHODS: This was a preplanned secondary analysis of the STOP-CAD study (Antithrombotic Treatment for Stroke Prevention in Cervical Artery Dissection), a multicenter international retrospective observational study (63 sites from 16 countries in North America, South America, Europe, Asia, and Africa) that included patients with CAD predominantly between January 2015 and June 2022. The primary outcome was subsequent ischemic stroke by day 180 after diagnosis. Clinical and imaging variables were compared between those with versus without subsequent ischemic stroke. Significant factors associated with subsequent stroke risk were identified using stepwise Cox regression. Associations between subsequent ischemic stroke risk and antithrombotic therapy type (anticoagulation versus antiplatelets) among patients with identified risk factors were explored using adjusted Cox regression. RESULTS: In all, 4023 patients (mean age was 47.4 years; 44.5% were women) were included. By day 180, subsequent ischemic stroke occurred in 5.3% of the cohort. In adjusted Cox regression, factors associated with increased risk of subsequent ischemic stroke were prior history of ischemic stroke (adjusted hazard ratio [aHR], 7.31 [95% CI, 1.61–33.13]; P =0.010), presentation within 7 days from first symptoms (aHR, 3.04 [95% CI, 1.04–8.91]; P =0.043), infarct on baseline imaging (aHR, 9.85 [95% CI, 3.65–26.58]; P <0.001), and occlusive dissection (aHR, 2.34 [95% CI, 1.03–5.34]; P =0.043). Only patients with occlusive dissection demonstrated a reduced risk of subsequent ischemic stroke when treated with anticoagulation versus antiplatelets (aHR, 0.36 [95% CI, 0.16–0.80]; P =0.01). CONCLUSIONS: In this post hoc analysis of the STOP-CAD study, several factors associated with subsequent ischemic stroke were identified among patients with CAD. Furthermore, we identified a potential benefit of anticoagulation in patients with CAD with occlusive dissection. These findings require validation by meta-analyses of prior studies to formulate optimal treatment strategies for specific high-risk CAD subgroups.

Background Flow-diverter stents (FDS) have become the standard of care for a wide range of intracranial aneurysms, but their efficacy/safety in the context of recurrent/recanalized aneurysms following stent-assisted coiling (SAC) is not well established. We evaluate the outcomes of FDS retreatment in a large multicenter cohort. Methods We retrospectively analyzed data from 118 patients across 22 institutions who underwent FDS retreatment for recurrent/persistent aneurysms after SAC (2008–22). The primary outcome was angiographic occlusion status at last follow-up, categorized as complete (100%), near-complete (90–99%), or incomplete (<90%) occlusion. Secondary outcomes included procedural complications and clinical outcomes measured by the modified Rankin Scale (mRS). Results A total of 118 patients (median age 57, 74.6% female) with median follow-up of 15.3 months were identified. Complete occlusion was achieved in 62.5% and near-complete occlusion in 25%. FDS deployment within the pre-existing stent was successful in 98.3% of cases. Major complications occurred in 3.4% of cases, including postoperative aneurysmal rupture with resultant mortality (1.6%) and thromboembolic events with long-term disability (1.6%). Favorable clinical outcomes (mRS 0–2) were observed in 95.1% of patients. Wider aneurysm neck diameter was a significant predictor of incomplete occlusion (adjusted OR (aOR) 1.23 per mm, P=0.044), with male sex trending towards association with non-occlusion (aOR 3.2, P=0.07), while baseline hypertension was associated with complete occlusion (aOR 0.32, P=0.048). Conclusions FDS treatment for recurrent/residual aneurysms after SAC represents a viable treatment option for these challenging cases with acceptable safety and reasonable occlusion rates, although lower than de novo FDS occlusion rates.

Objective: Multicancer Detection (MCD) tests, such as the GRAIL Galleri, offer a novel approach to cancer screening by detecting cancer-specific methylation patterns in cell-free DNA through a single blood sample. This study evaluated an 18-month implementation of MCD testing in a tertiary ambulatory internal medicine clinic. Patients and Methods: Between June 2022 and November 2023, 2244 asymptomatic (without symptoms attributed to cancer) patients underwent MCD testing. The study focused on operational workflows, patient and physician education, and diagnostic follow-up of positive results. Standardized materials, including electronic health record (EHR) workflows, FAQs, and diagnostic pathways, were developed to facilitate implementation. Challenges included managing false positives, patient anxiety, costs, and ethical considerations. Results: Of the 2244 patients tested, 17 (0.76%) had positive results, and 15 underwent further diagnostic evaluation. Cancer was confirmed in 11 (73.3%) patients, including cases of breast, colon, esophageal, lymphoma, ovarian, and pancreatic cancers. Four patients had no identifiable malignancy despite comprehensive work-up. Conclusions: MCD testing is feasible in routine clinical workflows, with 73% of positive cases yielding cancer diagnoses. While promising, further research is required to assess long-term outcomes, cost-effectiveness, and optimal implementation strategies of cancer interception in broader healthcare settings.

Objectives/Goals: This study aims to evaluate the performance of a third-party artificial intelligence (AI) product in predicting diagnosis-related groups (DRGs) in a community healthcare system. We highlight a use case illustrating how clinical practice leverages AI-predicted information in unexpected yet advantageous ways and assess the AI predictions accuracy and practical application. Methods/Study Population: DRGs are crucial for hospital reimbursement under the prospective payment model. The Mayo Clinic Health System (MCHS), a network of clinics and hospitals serving a substantial rural population in Minnesota and Wisconsin, has recently adopted an AI algorithm developed by Xsolis (an AI-focused healthcare solution provider). This algorithm, a 1D convolutional neural network, predicts DRGs based on clinical documentation. To assess the accuracy of AI-generated DRG predictions for inpatient discharges, we analyzed data from 930 patients hospitalized at MCHS Mankato between March 2 and May 13, 2024. The Xsolis platform provided the top three DRG predictions for the first 48 hours of each inpatient stay. The accuracy of these predictions was then compared against the final billed DRG codes from the hospital’s records. Results/Anticipated Results: In our validation set, Xsolis achieved a top-3 DRG prediction accuracy of 71% at 24 hours and 81% at 48 hours, which is lower than the originally reported accuracy of 81.1% and 83.3%, respectively. Interestingly, discussions with clinical practice leaders revealed that the most valuable information derived from the AI predictions was the expected geometric mean length of stay (GMLOS), which Xsolis was perceived to predict accurately. In the Medicare system, each DRG is associated with an expected GMLOS, a critical factor for efficient hospital flow planning. A subsequent analysis comparing predicted GMLOS with the actual length of stay showed variances of -0.10 days on day 1 and 0.14 days on day 2, indicating a high degree of accuracy and aligning with clinical practice perceptions. Discussion/Significance of Impact: Our research underscores that clinical practice can leverage AI predictions in unexpected yet beneficial ways. While initially focused on DRG prediction, the associated GMLOS emerged as more significant. This suggests that AI algorithm validation should be tailored to specific clinical needs rather than relying solely on generalized benchmarks.