Sex differences in device-measured physical activity after transcatheter aortic valve replacement.

OBJECTIVE: Physical activity (PA) is an important clinical and quality of life outcome after transcatheter aortic valve replacement (TAVR). We examined the effect of TAVR on objectively measured PA in patients with cardiac implanted electronic devices (CIEDs). METHODS: Daily accelerometer data was obtained from CIEDs. Patients in the University of North Carolina Health System with continuous PA data at least 6 months before TAVR and 12 months after TAVR were included. Changes in activity pre- and post-TAVR were analyzed with linear mixed-effects models using a random intercept for each patient. An interaction term was included to determine differences in PA between men and women pre- and post-TAVR. RESULTS: Of the 306 patients with CIEDs who underwent TAVR, 24,655 patient-days of data from 46 patients, mean age of 82 years old, 44% of whom were female met inclusion criteria. A significant and sustained increase of 14.7% in daily PA was seen after TAVR [10.15 minutes per day, 95% confidence interval (CI) 8.75 to 11.56 P < .001] after adjusting for sex, obesity, race, history of depression, and Charlson Comorbidity Index. Effects were more prominent in women (18.57 [95% CI 16.36 to 20.79, P < .001] minute increase post-TAVR) compared to men (4.51 [95% CI 3.87 to 5.16] minute increase post-TAVR, P < .001). CONCLUSIONS: This study demonstrates PA increases after TAVR with effects more pronounced in women than men. Further, this study highlights the potential use of remote monitoring data for monitoring functional outcomes in device patients after a procedure.

High-frequency fecal indicator bacteria (FIB) observations to assess water quality drivers at an enclosed beach.

Fecal indicator bacteria (FIB) are monitored at beaches to assess water quality and associated health risk from recreational exposure. However, monitoring is generally conducted infrequently (i.e. weekly or less often), potentially leading to inaccurate assessment of water quality at a beach at the time of use. While some work has shown that FIB in marine environments can vary over short (e.g. subhourly) time scales, that work has been mainly focused on 'open' beaches. 'Enclosed' beaches-those that are partially barriered from exchange with offshore water and thus have different residence times and mixing dynamics in the nearshore environment-have been less studied. Here we present results from a high-frequency (once per 30 minutes) FIB sampling event conducted within a Central California, USA, harbor over 48 hours. FIB concentrations at this enclosed site were more variable at high-frequencies than what has been reported at open beach sites. Correlation and regression analyses showed FIB concentrations were most strongly associated with chlorophyll a concentration, turbidity, wind speed, and tide level. Results indicate the importance of measuring FIB concentrations and explanatory environmental parameters at appropriate temporal resolutions when conducting water quality monitoring or source tracking studies. Overall, this work highlights how high-frequency sampling can effectively provide information about water quality dynamics at beaches of interest.

Know Before You Go: Data-Driven Beach Water Quality Forecasting.

Forecasting environmental hazards is critical in preventing or building resilience to their impacts on human communities and ecosystems. Environmental data science is an emerging field that can be harnessed for forecasting, yet more work is needed to develop methodologies that can leverage increasingly large and complex data sets for decision support. Here, we design a data-driven framework that can, for the first time, forecast bacterial standard exceedances at marine beaches with 3 days lead time. Using historical data sets collected at two California sites, we train nearly 400 forecast models using statistical and machine learning techniques and test forecasts against predictions from both a naive "persistence" model and a baseline nowcast model. Overall, forecast models are found to have similar sensitivities and specificities to the persistence model, but significantly higher areas under the ROC curve (a metric distinguishing a model's ability to effectively parse classes across decision thresholds), suggesting that forecasts can provide enhanced information beyond past observations alone. Forecast model performance at all lead times was similar to that of nowcast models. Together, results suggest that integrating the forecasting framework developed in this study into beach management programs can enable better public notification and aid in proactive pollution and health risk management.

A Day at the Beach: Enabling Coastal Water Quality Prediction with High-Frequency Sampling and Data-Driven Models.

To reduce the incidence of recreational waterborne illness, fecal indicator bacteria (FIB) are measured to assess water quality and inform beach management. Recently, predictive FIB models have been used to aid managers in making beach posting and closure decisions. However, those predictive models must be trained using rich historical data sets consisting of FIB and environmental data that span years, and many beaches lack such data sets. Here, we investigate whether water quality data collected during discrete short duration, high-frequency beach sampling events (e.g., samples collected at sub-hourly intervals for 24-48 h) are sufficient to train predictive models that can be used for beach management. We use data collected during six high-frequency sampling events at three California marine beaches and train a total of 126 models using common data-driven techniques. Tide, solar irradiation, water temperature, significant wave height, and offshore wind speed were found to be the most important environmental variables in the models. We validate the predictive performance of models using withheld data. Random forests are consistently the top performing model type. Overall, we find that data-driven models trained using high-frequency FIB and environmental data perform well at predicting water quality and can be used to inform public health decisions at beaches.

Curriculum Vitae Workshops: Promoting Transparency in Alpha Omega Alpha While Serving Student Needs.

OBJECTIVE: To promote equity in the Alpha Omega Alpha Honor Medical Society (AOA) selection process, clear and timely communication of eligibility criteria is needed. Herein, the authors describe and assess the effectiveness of a novel method for improving transparency in the AOA selection process while also teaching students key professional development skills. METHODS: The authors hosted curriculum vitae (CV) workshops for interested medical students. One part of each session was dedicated to sharing information about AOA and its selection process, while the rest focused on teaching students how to build effective CVs. After the most recent session, students were asked to complete a survey about the effectiveness of the workshop. RESULTS: Between 2019 and 2020, three CV workshops were hosted. Interest in the events was high, with approximately 15 to 30 first- and second-year medical students participating in each. Based on survey results, participants found the workshop helped them gain a better understanding of AOA eligibility and selection (100%, n = 10) and taught them key CV development skills (100%, n = 10). CONCLUSION: These workshops are a novel approach to disseminating AOA eligibility criteria and can be employed by medical schools to promote transparency in the AOA selection process. They also give students the skills to craft CVs that will better prepare them for applying to residency and other academic opportunities. As such medical schools and AOA chapters should consider implementing a similar model at their institutions.

Early Termination of Cardiac Rehabilitation Is More Common With Heart Failure With Reduced Ejection Fraction Than With Ischemic Heart Disease.

PURPOSE: Despite known benefits of cardiac rehabilitation (CR), early termination (failure to complete >1 mo of CR) attenuates these benefits. We analyzed whether early termination varied by referral indication in the context of recent growth in patients referred for heart failure with reduced ejection fraction (HFrEF). METHODS: We reviewed records from 1111 consecutive patients enrolled in the NYU Langone Health Rusk CR program (2013-2017). Sessions attended, demographics, and comorbidities were abstracted, as well as primary referral indication: HFrEF or ischemic heart disease (IHD; including post-coronary revascularization, post-acute myocardial infarction, or chronic stable angina). We compared rates of early termination between HFrEF and IHD, and used multivariable logistic regression to determine whether differences persisted after adjusting for relevant characteristics (age, race, ethnicity, body mass index, smoking, hypertension, chronic obstructive pulmonary disease, and depression). RESULTS: Mean patient age was 64 yr, 31% were female, and 28% were nonwhite. Most referrals (85%) were for IHD; 15% were for HFrEF. Early termination occurred in 206 patients (18%) and was more common in HFrEF (26%) than in IHD (17%) (P < .01). After multivariable adjustment, patients with HFrEF remained at higher risk of early termination than patients with IHD (unadjusted OR = 1.73, 95% CI, 1.17-2.54; adjusted OR = 1.53, 95% CI, 1.01-2.31). CONCLUSIONS: Nearly 1 in 5 patients in our program terminated CR within 1 mo, with HFrEF patients at higher risk than IHD patients. While broad efforts at preventing early termination are warranted, particular attention may be required in patients with HFrEF.

IL35 Hinders Endogenous Antitumor T-cell Immunity and Responsiveness to Immunotherapy in Pancreatic Cancer.

Although successes in cancer immunotherapy have generated considerable excitement, this form of treatment has been largely ineffective in patients with pancreatic ductal adenocarcinoma (PDA). Mechanisms that contribute to the poor antitumor immune response in PDA are not well understood. Here, we demonstrated that cytokine IL35 is a major immunosuppressive driver in PDA and potentiates tumor growth via the suppression of endogenous antitumor T-cell responses. The growth of pancreatic tumors in mice deficient for IL35 was significantly reduced. An analysis of tumor-infiltrating immune cells revealed a role for IL35 in the expansion of regulatory T cells and the suppression of CD4+ effector T cells. We also detected a robust increase in both the infiltration and activation of cytotoxic CD8+ T cells, suggesting that targeting IL35 may be an effective strategy to convert PDA from an immunologically "cold" to "hot" tumor. Although PDA is typically resistant to anti-PD-1 immunotherapy, we demonstrated robust synergistic reduction in tumor growth when IL35 deficiency was combined with anti-PD-1 treatment. These findings provide new insight into the function of IL35 in the pathogenesis of pancreatic cancer and underscore the potential significance of IL35 as a therapeutic target for use in combination immunotherapy approaches in this deadly malignancy. Cancer Immunol Res; 6(9); 1014-24. ©2018 AACR.

Implementation of an automated beach water quality nowcast system at ten California oceanic beaches.

Fecal indicator bacteria like Escherichia coli and entercococci are monitored at beaches around the world to reduce incidence of recreational waterborne illness. Measurements are usually made weekly, but FIB concentrations can exhibit extreme variability, fluctuating at shorter periods. The result is that water quality has likely changed by the time data are provided to beachgoers. Here, we present an automated water quality prediction system (called the nowcast system) that is capable of providing daily predictions of water quality for numerous beaches. We created nowcast models for 10 California beaches using weather, oceanographic, and other environmental variables as input to tuned regression models to predict if FIB concentrations were above single sample water quality standards. Rainfall was used as a variable in nearly every model. The models were calibrated and validated using historical data. Subsequently, models were implemented during the 2017 swim season in collaboration with local beach managers. During the 2017 swim season, the median sensitivity of the nowcast models was 0.5 compared to 0 for the current method of using day-to-week old measurements to make beach posting decisions. Model specificity was also high (median of 0.87). During the implementation phase, nowcast models provided an average of 140 additional days per beach of updated water quality information to managers when water quality measurements were not made. The work presented herein emphasizes that a one-size-fits all approach to nowcast modeling, even when beaches are in close proximity, is infeasible. Flexibility in modeling approaches and adaptive responses to modeling and data challenges are required when implementing nowcast models for beach management.