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e16535 Background: RMC is a rare and highly aggressive malignancy that predominantly affects young individuals with sickle hemoglobinopathies. Due to its rarity, no validated prognostic models exist to guide clinical decision-making. We aimed to develop and internally validate a prognostic model for patients with RMC using routinely available clinical and laboratory variables. Methods: We analyzed a single-institution cohort of patients with RMC. Candidate variables were identified based on biological plausibility and represented in a directed acyclic graph. Missing data were handled via multiple imputation by chained equations ( m = 50). Variables were ranked using elastic net Cox regression ( α = 0.5, λ = λ min ) with stability selection derived from 100 bootstrap resamples per imputed dataset. Predictors achieving > 60% selection frequency were retained for a nested parsimony analysis. Bootstrap internal validation ( B = 2000) estimated optimism-corrected discrimination and calibration performance, with the calibration slope applied as global shrinkage to penalize final coefficients for overfitting. Clinical utility was evaluated via decision curve analysis (DCA) at 18- and 24-month horizons. Results: Among 180 patients (median age 29; IQR 23–37), 142 deaths occurred with a median follow-up of 12.4 months. The final model included four predictors (Table). The optimism-corrected c-index was 0.667 (optimism = 0.009), and the calibration slope was 0.964, indicating minimal overfitting. Calibration plots showed excellent predicted-observed agreement at 12, 18, 24, and 36 months. DCA showed net benefit across threshold probabilities of 10%–75% at 18 months and 10%–80% at 24 months compared to default strategies. In sensitivity analysis, inclusion of TP53 mutation status improved discrimination ( c -index 0.686) and model fit ( ΔAIC −10.6). An interactive web-based risk calculator was developed to facilitate clinical implementation. Conclusions: This study presents the first internally validated prognostic model for RMC, demonstrating acceptable discrimination and excellent calibration using routinely available variables. By stratifying patients into distinct risk groups, this model may inform treatment intensity—guiding escalation to multi-agent regimens or sequential chemotherapy cycling in high-risk patients, while identifying lower-risk patients who may benefit from de-escalation strategies such as metastasis-directed therapy for oligometastatic disease or consideration of cytoreductive nephrectomy. External validation is warranted. Variable Time Ratio 95% CI p value ECOG performance status 0.64 0.53–0.77 <0.001 Distal (non-retroperitoneal) lymph node metastases 0.69 0.52–0.92 0.011 Neutrophil-to-lymphocyte ratio 0.98 0.94–1.02 0.25 Corrected calcium (mg/dL) 0.77 0.56–1.06 0.10 Sensitivity Analysis Only TP53 Mutation 0.63 0.36-1-10 0.10

Background The rapid evolution of artificial intelligence (AI) in conjunction with recent updates in dual antiplatelet therapy (DAPT) management guidelines emphasizes the necessity for innovative models to predict ischemic or bleeding events after drug‐eluting stent implantation. Leveraging AI for dynamic prediction has the potential to revolutionize risk stratification and provide personalized decision support for DAPT management. Methods and Results We developed and validated a new AI‐based pipeline using retrospective data of drug‐eluting stent‐treated patients, sourced from the Cerner Health Facts data set (n=98 236) and Optum's de‐identified Clinformatics Data Mart Database (n=9978). The 36 months following drug‐eluting stent implantation were designated as our primary forecasting interval, further segmented into 6 sequential prediction windows. We evaluated 5 distinct AI algorithms for their precision in predicting ischemic and bleeding risks. Model discriminative accuracy was assessed using the area under the receiver operating characteristic curve, among other metrics. The weighted light gradient boosting machine stood out as the preeminent model, thus earning its place as our AI‐DAPT model. The AI‐DAPT demonstrated peak accuracy in the 30 to 36 months window, charting an area under the receiver operating characteristic curve of 90% [95% CI, 88%–92%] for ischemia and 84% [95% CI, 82%–87%] for bleeding predictions. Conclusions Our AI‐DAPT excels in formulating iterative, refined dynamic predictions by assimilating ongoing updates from patients' clinical profiles, holding value as a novel smart clinical tool to facilitate optimal DAPT duration management with high accuracy and adaptability.

SummaryBackgroundPrevious studies have demonstrated an association between nonselective beta‐blockers (NSBBs) and lower risk of hepatocellular carcinoma (HCC) in cirrhosis. However, there has been no population‐based study investigating the risk of HCC among cirrhotic patients treated using carvedilol.AimsTo determine the risk of HCC among cirrhotic patients with NSBBs including carvedilol.MethodsThis retrospective cohort study utilised the Cerner Health Facts database in the United States from 2000 to 2017. Kaplan‐Meier estimate, Cox proportional hazards regression, and propensity score matching (PSM) were used to test the HCC risk among the carvedilol, nadolol, and propranolol groups compared with no beta‐blocker group.ResultsThe final cohort comprised 107 428 eligible patients. The 100‐month cumulative HCC incidence of NSBBs was significantly lower than the no beta‐blocker group (carvedilol (11.24%) vs no beta‐blocker (15.69%), nadolol (27.55%) vs no beta‐blocker (32.11%), and propranolol (26.17%) vs no beta‐blocker (28.84%) (P values < 0.0001). NSBBs were associated with a significantly lower risk of HCC (Hazard ratio: carvedilol 0.61 (95% CI 0.51‐0.73), nadolol 0.74 (95% CI 0.63‐0.87), propranolol 0.75 (95% CI 0.66‐0.84) after PSM in the multivariate cox analysis. In subgroup analysis, NSBBs reduced the risk of HCC in cirrhosis with complications and non‐alcoholic cirrhosis.ConclusionsNSBBs, including carvedilol, were associated with a significantly decreased risk of HCC in patients with cirrhosis when compared with no beta‐blocker regardless of complications status. Future randomised‐controlled studies comparing the incidence of HCC among NSBBs should elucidate which NSBB would be the best option to prevent HCC in cirrhosis.

Background: Mechanical injury in the conduction system requiring permanent pacemaker (PPM) associated with transcatheter aortic valve replacement (TAVR) procedure is a common complication. The objective of this study was to use ambulatory monitor BodyGuardian to assess late occurrence of atrioventricular block (AVB) after TAVR. Methods: This prospective study evaluated 365 patients who underwent TAVR at Mayo Clinic, Rochester, Minnesota between June 2016 and August 2017. Patients who received PPM for bradycardia after TAVR before discharge were considered as the PPM group. Those not requiring PPM received a BodyGuardian system (BodyGuardian group) for 30 days of continuous monitoring. Primary end point was Mobitz II or third-degree atrioventricular block (II/III AVB) at 30-day follow-up. Results: Of 365 patients, 74 who had a PPM or an implantable cardioverter-defibrillator before TAVR and 94 who were enrolled in other studies were excluded. Of 197 patients enrolled in the study, 70 (35.5%) received PPM and 127 had BodyGuardian before the hospital dismissal. Eleven of 127 (8.6%) BodyGuardian group required PPM within 30 days after TAVR for late occurrence of symptomatic bradycardia. In total, 33 of 197 (16.7%) patients developed II/III AVB (24 before and 9 after discharge). Thirty-four patients had preexisting right bundle branch block. Of them, 16 (47%) developed II/III AVB. Of 53 patients who developed new left bundle branch block after TAVR, 14% progressed to II/III AVB within 30 days. Conclusions: In patients without a standard post-TAVR pacing indication, yet a potential risk to develop AVB, a strategy of 30-day monitoring identifies additional patients who require permanent pacing.

Background: Percutaneous stellate ganglion blockade (SGB) has been used for drug-refractory electrical storm due to ventricular arrhythmia (VA); however, the effects and long-term outcomes have not been well studied. Methods: This study included 30 consecutive patients who had drug-refractory electrical storm and underwent percutaneous SGB between October 1, 2013, and March 31, 2018. Bupivacaine, alone or combined with lidocaine, was injected into the neck with good local anesthetic spread in the vicinity of the left stellate ganglion (n=15) or both stellate ganglia (n=15). Data were collected for patient clinical characteristics, immediate and long-term outcomes, and procedure-related complications. Results: Clinical characteristics included age, 58±14 years; men, 73.3%; and left ventricular ejection fraction, 34±16%. At 24 hours, 60% of patients were free of VA. Patients whose VA was controlled had a lower hospital mortality rate than patients whose VA continued (5.6% versus 50.0%; P =0.009). Implantable cardioverter-defibrillator interrogation showed a significant 92% reduction in VA episodes from 26±41 to 2±4 in the 72 hours after SGB ( P <0.001). Patients who died during the same hospitalization (n=7) were more likely to have ischemic cardiomyopathy (100% versus 43.5%; P =0.03) and recurrent VA within 24 hours (85.7% versus 26.1%; P =0.009). There were no procedure-related major complications. Conclusions: SGB effectively attenuated electrical storm in more than half of patients without procedure-related complications. Percutaneous SGB may be considered for stabilizing ventricular rhythm in patients for whom other therapies have failed.