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Background: The National Cardiovascular Data Registry Left Atrial Appendage Occlusion Registry (LAAO) includes the vast majority of transcatheter LAAO procedures performed in the United States. The objective of this study was to develop a model predicting adverse events among patients undergoing LAAO with Watchman FLX., Methods: Data from 41 001 LAAO procedures with Watchman FLX from July 2020 to September 2021 were used to develop and validate a model predicting in-hospital major adverse events. Randomly selected development (70%, n=28 530) and validation (30%, n=12 471) cohorts were analyzed with 1000 bootstrapped samples, using forward stepwise logistic regression to create the final model. A simplified bedside risk score was also developed using this model., Results: Increased age, female sex, low preprocedure hemoglobin, no prior attempt at atrial fibrillation termination, and increased fall risk most strongly predicted in-hospital major adverse events and were included in the final model along with other clinically relevant variables. The median in-hospital risk-standardized adverse event rate was 1.50% (range, 1.03%-2.84%; interquartile range, 1.42%-1.64%). The model demonstrated moderate discrimination (development C-index, 0.67 [95% CI, 0.65-0.70] and validation C-index, 0.66 [95% CI, 0.62-0.70]) with good calibration. The simplified risk score was well calibrated with risk of in-hospital major adverse events ranging from 0.26% to 3.90% for a score of 0 to 8, respectively., Conclusions: A transcatheter LAAO risk model using National Cardiovascular Data Registry and LAAO Registry data can predict in-hospital major adverse events, demonstrated consistency across hospitals and can be used for quality improvement efforts. A simple bedside risk score was similarly predictive and may inform shared decision-making., Competing Interests: Disclosures Dr Faridi receives research funding from the National Institutes of Health (NIH)/National Heart, Lung and Blood Institute (NHLBI;K23HL161424). Dr Friedman reports receiving research grants from Abbott, American Heart Association, Biosense Webster, Boston Scientific, Medtronic, Merit Medical, National Cardiovascular Data Registry, Phillips, and NIH, and consulting fees from Abbott, NI Medical, Microport, and Sanofi. Dr Hsu reports receiving honoraria from Medtronic, Abbott, Boston Scientific, Biotronik, Janssen Pharmaceuticals, Bristol-Myers Squibb, Pfizer, Sanofi, Altathera, Zoll Medical, Hillrom, iRhythm, Acutus Medical, Galvanize Therapeutics, and Biosense-Webster, research grants from Biotronik and Biosense-Webster, and has equity interest in Vektor Medical. Dr Mortazavi receives research funding from the National Science Foundation (IIS #2014475) and the NIH (R21EB028486, R01HL151240, R01EB028106, and R01HL142765). Dr Lakkireddy reports being a consultant for Abbott, Boston Sci, Atricure, Biosense Webster, and Acutus. Dr Curtis has a contract with the American College of Cardiology (ACC) for his role as Chief Scientific Advisor of the ACC’s National Cardiovascular Data Registry. He holds equity interest in Medtronic. Dr Freeman reports receiving research grants from the N NHLBI and the ACC National Cardiovascular Data Registry and consulting/advisory board fees from Boston Scientific, Biosense Webster, Medtronic, and PaceMate. and equity in PaceMate.

Background: Radical prostatectomy (RP) is the most common definitive treatment for men with intermediate-risk prostate cancer and is frequently complicated by erectile dysfunction., Objective: To develop and validate models to predict 12- and 24-month post-RP sexual function., Design Setting and Participants: Using Michigan Urological Surgery Improvement Collaborative (MUSIC) registry data from 2016 to 2021, we developed dynamic, multivariate, random-forest models to predict sexual function recovery following RP. Model factors (established a priori) included baseline patient characteristics and repeated assessments of sexual satisfaction, and Expanded Prostate Cancer Index Composite 26 (EPIC-26) overall scores and sexual domain questions., Outcome Measurements and Statistical Analysis: We evaluated three outcomes related to sexual function: (1) the EPIC-26 sexual domain score (range 0-100); (2) the EPIC-26 sexual domain score dichotomized at ≥73 for "good" function; and (3) a dichotomized variable for erection quality at 12 and 24 months after RP. A gradient-boosting decision tree was used for the prediction models, which combines many decision trees into a single model. We evaluated the performance of our model using the root mean squared error (RMSE) and mean absolute error (MAE) for the EPIC-26 score as a continuous variable, and the area under the receiver operating characteristic curve (AUC) for the dichotomized EPIC-26 sexual domain score (SDS) and erection quality. All analyses were conducted using R v3.6.3., Results and Limitations: We identified 3983 patients at 12 months and 2494 patients at 24 months who were randomized to the derivation cohort at 12 and 24 months, respectively. Using baseline information only, our model predicted the 12-month EPIC-26 SDS with RMSE of 24 and MAE of 20. The AUC for predicting EPIC-26 SDS ≥73 (a previously published threshold) was 0.82. Our model predicted 24-month EPIC-26 SDS with RMSE of 26 and MAE of 21, and AUC for SDS ≥73 of 0.81. Inclusion of post-RP data improved the AUC to 0.91 and 0.94 at 12 and 24 months, respectively. A web tool has also been developed and is available at https://ml4lhs.shinyapps.io/askmusic_prostate_pro/., Conclusions: Our model provides a valid way to predict sexual function recovery at 12 and 24 months after RP. With this dynamic, multivariate (multiple outcomes) model, accurate predictions can be made for decision-making and during survivorship, which may reduce decision regret., Patient Summary: Our prediction model allows patients considering prostate cancer surgery to understand their probability before and after surgery of recovering their erectile function and may reduce decision regret., (© 2022 The Author(s).)

Background: The inclusion criterion for active surveillance (AS) is low- or intermediate-risk prostate cancer. The predictive value of the presence of a suspicious lesion at magnetic resonance imaging (MRI) at the time of inclusion is insufficiently known., Objective: To evaluate the percentage of patients needing active treatment stratified by the presence or absence of a suspicious lesion at baseline MRI., Design Setting and Participants: A retrospective analysis of the data from the multicentric AS GAP3 Consortium database was conducted. The inclusion criteria were men with grade group (GG) 1 or GG 2 prostate cancer combined with prostate-specific antigen <20 ng/ml. We selected a subgroup of patients who had MRI at baseline and for whom MRI results and targeted biopsies were used for AS eligibility. Suspicious MRI was defined as an MRI lesion with Prostate Imaging Reporting and Data System (PI-RADS)/Likert ≥3 and for which targeted biopsies did not exclude the patient for AS., Outcome Measurements and Statistical Analysis: The primary outcome was treatment free survival (FS). The secondary outcomes were histological GG progression FS and continuation of AS (discontinuation FS)., Results and Limitations: The study cohort included 2119 patients (1035 men with nonsuspicious MRI and 1084 with suspicious MRI) with a median follow-up of 23 (12-43) mo. For the whole cohort, 3-yr treatment FS was 71% (95% confidence interval [CI]: 69-74). For nonsuspicious MRI and suspicious MRI groups, 3-yr treatment FS rates were, respectively, 80% (95% CI: 77-83) and 63% (95% CI: 59-66). Active treatment (hazard ratio [HR] = 2.0, p < 0.001), grade progression (HR = 1.9, p < 0.001), and discontinuation of AS (HR = 1.7, p < 0.001) were significantly higher in the suspicious MRI group than in the nonsuspicious MRI group., Conclusions: The risks of switching to treatment, histological progression, and AS discontinuation are higher in cases of suspicious MRI at inclusion., Patient Summary: Among men with low- or intermediate-risk prostate cancer who choose active surveillance, those with suspicious magnetic resonance imaging (MRI) at the time of inclusion in active surveillance are more likely to show switch to treatment than men with nonsuspicious MRI., (© 2021 The Author(s).)