Faculty Bibliography

BACKGROUND/UNASSIGNED:Nonadherence to antihypertensive medications remains a persistent problem that leads to preventable morbidity and mortality. Behavioral economic strategies represent a novel way to improve antihypertensive medication adherence, but remain largely untested especially in vulnerable populations which stand to benefit the most. The Behavioral Economics Trial To Enhance Regulation of Blood Pressure (BETTER-BP) was designed in this context, to test whether a digitally-enabled incentive lottery improves antihypertensive adherence and reduces systolic blood pressure (SBP). DESIGN/UNASSIGNED:BETTER-BP is a pragmatic randomized trial conducted within 3 safety-net clinics in New York City: Bellevue Hospital Center, Gouveneur Hospital Center, and NYU Family Health Centers - Park Slope. The trial will randomize 435 patients with poorly controlled hypertension and poor adherence (<80% days adherent) in a 2:1 ratio (intervention:control) to receive either an incentive lottery versus passive monitoring. The incentive lottery is delivered via short messaging service (SMS) text messages that are delivered based on (1) antihypertensive adherence tracked via a wireless electronic monitoring device, paired with (2) a probability of lottery winning with variable incentives and a regret component for nonadherence. The study intervention lasts for 6 months, and ambulatory systolic blood pressure (SBP) will be measured at both 6 and 12 months to evaluate immediate and durable lottery effects. CONCLUSIONS/UNASSIGNED:BETTER-BP will generate knowledge about whether an incentive lottery is effective in vulnerable populations to improve antihypertensive medication adherence. If successful, this could lead to the implementation of this novel strategy on a larger scale to improve outcomes.

Background Angiotensin receptor neprilysin inhibitors (ARNI) reduce mortality and hospitalization for patients with heart failure. However, relatively high copayments for ARNI may contribute to suboptimal adherence, thus potentially limiting their benefits. Methods and Results We conducted a retrospective cohort study within a large, multi-site health system. We included patients with: ARNI prescription between November 20, 2020 and June 30, 2021; diagnosis of heart failure or left ventricular ejection fraction ≤40%; and available pharmacy or pharmacy benefit manager copayment data. The primary exposure was copayment, categorized as $0, $0.01 to $10, $10.01 to $100, and >$100. The primary outcome was prescription fill nonadherence, defined as the proportion of days covered <80% over 6 months. We assessed the association between copayment and nonadherence using multivariable logistic regression, and nonbinarized proportion of days covered using multivariable Poisson regression, adjusting for demographic, clinical, and neighborhood-level covariates. A total of 921 patients met inclusion criteria, with 192 (20.8%) having $0 copayment, 228 (24.8%) with $0.01 to $10 copayment, 206 (22.4%) with $10.01 to $100, and 295 (32.0%) with >$100. Patients with higher copayments had higher rates of nonadherence, ranging from 17.2% for $0 copayment to 34.2% for copayment >$100 (P<0.001). After multivariable adjustment, odds of nonadherence were significantly higher for copayment of $10.01 to $100 (odds ratio [OR], 1.93 [95% CI, 1.15-3.27], P=0.01) or >$100 (OR, 2.58 [95% CI, 1.63-4.18], P<0.001), as compared with $0 copayment. Similar associations were seen when assessing proportion of days covered as a proportion. Conclusions We found higher rates of not filling ARNI prescriptions among patients with higher copayments, which persisted after multivariable adjustment. Our findings support future studies to assess whether reducing copayments can increase adherence to ARNI and improve outcomes for heart failure.

BACKGROUND:Male sex, elevated troponin levels, and elevated D-dimer levels are associated with more complicated COVID-19 illness and greater mortality; however, while there are known sex differences in the prognostic value of troponin and D-dimer in other disease states, it is unknown whether they exist in the setting of COVID-19. OBJECTIVE:We assessed whether sex modified the relationship between troponin, D-dimer, and severe COVID-19 illness (defined as mechanical ventilation, ICU admission or transfer, discharge to hospice, or death). METHODS:We conducted a retrospective cohort study of patients hospitalized with COVID-19 at a large, academic health system. We used multivariable regression to assess associations between sex, troponin, D-dimer, and severe COVID-19 illness, adjusting for demographic, clinical, and laboratory covariates. To test whether sex modified the relationship between severe COVID-19 illness and troponin or D-dimer, models with interaction terms were utilized. RESULTS:Among 4,574 patients hospitalized with COVID-19, male sex was associated with higher levels of troponin and greater odds of severe COVID-19 illness, but lower levels of initial D-dimer when compared with female sex. While sex did not modify the relationship between troponin level and severe COVID-19 illness, peak D-dimer level was more strongly associated with severe COVID-19 illness in male patients compared to female patients (males: OR=2.91, 95%CI=2.63-2.34, p<0.001; females: OR=2.31, 95%CI=2.04-2.63, p<0.001; p-interaction=0.005). CONCLUSION/CONCLUSIONS:Sex did not modify the association between troponin level and severe COVID-19 illness, but did modify the association between peak D-dimer and severe COVID-19 illness, suggesting greater prognostic value for D-dimer in males with COVID-19.

For interventions that affect how individuals interact, social network data may aid in understanding the mechanisms through which an intervention is effective. Social networks may even be an intermediate outcome observed prior to end of the study. In fact, social networks may also mediate the effects of the intervention on the outcome of interest, and Sweet (2019) introduced a statistical model for social networks as mediators in network-level interventions. We build on their approach and introduce a new model in which the network is a mediator using a latent space approach. We investigate our model through a simulation study and a real-world analysis of teacher advice-seeking networks.

BACKGROUND:Environmental exposures account for a growing proportion of global mortality. Large cohort studies are needed to characterize the independent impact of environmental exposures on mortality in low-income settings. METHODS:We collected data on individual and environmental risk factors for a multiethnic cohort of 50,045 individuals in a low-income region in Iran. Environmental risk factors included: ambient fine particular matter air pollution; household fuel use and ventilation; proximity to traffic; distance to percutaneous coronary intervention (PCI) center; socioeconomic environment; population density; local land use; and nighttime light exposure. We developed a spatial survival model to estimate the independent associations between these environmental exposures and all-cause and cardiovascular mortality. FINDINGS:Several environmental factors demonstrated associations with mortality after adjusting for individual risk factors. Ambient fine particulate matter air pollution predicted all-cause mortality (per μg/m3, HR 1.20, 95% CI 1.07, 1.36) and cardiovascular mortality (HR 1.17, 95% CI 0.98, 1.39). Biomass fuel use without chimney predicted all-cause mortality (reference = gas, HR 1.23, 95% CI 0.99, 1.53) and cardiovascular mortality (HR 1.36, 95% CI 0.99, 1.87). Kerosene fuel use without chimney predicted all-cause mortality (reference = gas, HR 1.09, 95% CI 0.97, 1.23) and cardiovascular mortality (HR 1.19, 95% CI 1.01, 1.41). Distance to PCI center predicted all-cause mortality (per 10km, HR 1.01, 95% CI 1.004, 1.022) and cardiovascular mortality (HR 1.02, 95% CI 1.004, 1.031). Additionally, proximity to traffic predicted all-cause mortality (HR 1.13, 95% CI 1.01, 1.27). In a separate validation cohort, the multivariable model effectively predicted both all-cause mortality (AUC 0.76) and cardiovascular mortality (AUC 0.81). Population attributable fractions demonstrated a high mortality burden attributable to environmental exposures. INTERPRETATION:Several environmental factors predicted cardiovascular and all-cause mortality, independent of each other and of individual risk factors. Mortality attributable to environmental factors represents a critical opportunity for targeted policies and programs.

There is some, but inconsistent, evidence to suggest that matching patient treatment preference enhances treatment engagement and outcome. The current study examined differential preferences and factors associated with treatment preference for 12-week group cognitive behavioral therapy (CBT), yoga, or stress education in 226 adults with generalized anxiety disorder (GAD; 70% female, Mean age = 33 ± 13.5). In a subsample of 165 patients who reported an intervention preference and were randomized to yoga or CBT, we further examined whether match to preferred intervention improved the primary treatment outcome (responder status on Clinical Global Impressions Scale) and engagement (dropout, homework compliance). Preferences for CBT (44%) and yoga (40%) were similar among patients. Women tended to prefer yoga (OR = 2.75, p = .01) and CBT preference was associated with higher baseline perceived stress (OR = 0.92, p = .04) and self-consciousness meta-cognitions (OR = 0.90, p = .02). Among those not matched to their preference, treatment response was higher for those receiving CBT than yoga (OR = 11.73, p = .013); there were no group differences for those matched to their treatment preference. In yoga, those who received their preference were more likely to drop than those who did not (OR = 3.02, 95% CI = [1.20, 7.58], p = .037). This was not the case for CBT (OR = 0.37, 95% CI = [0.13, 1.03], p = .076). Preference match did not predict homework compliance. Overall, results suggest that treatment preference may be important to consider to optimize outcome and engagement; however, it may vary by treatment modality. Future research incorporating preference, especially with yoga for anxiety, is aligned with personalized medicine. TRIAL REGISTRATION: clinicaltrials.gov: NCT01912287; https://clinicaltrials.gov/ct2/show/NCT01912287.

Background: Mobile health cardiac rehabilitation (mHealth-CR) may improve outcomes among older adults with ischemic heart disease, but variable engagement is not yet understood. We therefore analyzed preliminary data from the RESILIENT trial, an ongoing randomized trial of mHealth-CR vs. usual care in patients age >= 65.
Method(s): Data from the first 50 intervention participants were analyzed. Weekly engagement was scored from 0-11 based on exercise completion, therapist communication, video viewing, and BP self-measurement. Participants were classified as high or low engagement based on median engagement scores. Groups were compared by age, sex, social support (living alone), depression (PHQ-8), and Charlson Comorbidity Index (CCI).
Result(s): There was widely varying engagement with mHealth-CR that ranged from nearly zero to nearly perfect engagement (Figure). There were no significant differences between high and low engagement groups based on mean age (72.6 vs. 72.8, P=0.8), sex (76% male vs. 80%, P=0.7), living alone (28% vs. 44%, P=0.2), depression (mean 3.9 vs. 4.6, P=0.5), or comorbidity burden (mean 4.4 vs. 4.8, P=0.3), although the sample size was small.
Conclusion(s): Our early findings show wide variation in mHealth-CR engagement among older adults