Faculty Bibliography

Background/UNASSIGNED:Approximately one third of adults in adult day services (ADS) centers have Alzheimer's disease (AD) and AD-related dementias (ADRD). Understanding of the impact and effectiveness of ADS on persons living with dementia (PLWD) is limited by a lack of patient and caregiver relevant outcomes (PCRO) data. We identified PCROs collected at ADS sites in states that mandate serial data collection and examined the degree to which these data align with established Dementia Care Practice Recommendations (DCPR) and PCROs used in other areas of long-term care. Methods/UNASSIGNED:We conducted an item analysis of regulatory forms used by ADS. Consistent with the methodology used by the Imbedded Pragmatic AD/ADRD Clinical Trials (IMPACT) Collaboratory for PCROs collected in other long-term care settings, we created a matrix informed by DCPR. We matched each item in regulatory forms reflecting a PCRO to one of the seven DCPR domains as well as to the 53 PCROs from other long-term care sectors. Results/UNASSIGNED:Ten states routinely collect outcome data in ADS. Among these, 80% assess cognitive function. All 10 states capture PLWD's ability to complete activities of daily living. Presence and frequency of behavioral symptoms were collected by 80% of states. Very few or, in some cases, none of the 10 states, collected PCROs related to care planning and coordination, education, social support, and/or family caregiver burden and support. Discussion/UNASSIGNED:Lack of standardized collection of PCROs hampers researchers' understanding of ADS. The vast majority of PCROs collected center on participants' physical health; conversely, data on socialization, social support, and caregiver well-being, which are purportedly the most impactful services offered by ADS centers, are rarely collected. ADS would be well served to focus on these outcome domains as the resulting data could paint a more complete picture of the holistic impact of ADS on PLWD and their caregivers.

BACKGROUND:Post-acute sequelae of COVID-19 (PASC) includes a heterogeneous group of patients with variable symptomatology, who may respond to different therapeutic interventions. Identifying phenotypes of PASC and therapeutic strategies for different subgroups would be a major step forward in management. METHODS:In a prospective cohort study of patients hospitalized with COVID-19, 12-month symptoms and quantitative outcome metrics were collected. Unsupervised hierarchical cluster analyses were performed to identify patients with: (1) similar symptoms lasting ≥4 weeks after acute SARS-CoV-2 infection, and (2) similar therapeutic interventions. Logistic regression analyses were used to evaluate the association of these symptom and therapy clusters with quantitative 12-month outcome metrics (modified Rankin Scale, Barthel Index, NIH NeuroQoL). RESULTS:Among 242 patients, 122 (50%) reported ≥1 PASC symptom (median 3, IQR 1-5) lasting a median of 12-months (range 1-15) post-COVID diagnosis. Cluster analysis generated three symptom groups: Cluster1 had few symptoms (most commonly headache); Cluster2 had many symptoms including high levels of anxiety and depression; and Cluster3 primarily included shortness of breath, headache and cognitive symptoms. Cluster1 received few therapeutic interventions (OR 2.6, 95% CI 1.1-5.9), Cluster2 received several interventions, including antidepressants, anti-anxiety medications and psychological therapy (OR 15.7, 95% CI 4.1-59.7) and Cluster3 primarily received physical and occupational therapy (OR 3.1, 95%CI 1.3-7.1). The most severely affected patients (Symptom Cluster 2) had higher rates of disability (worse modified Rankin scores), worse NeuroQoL measures of anxiety, depression, fatigue and sleep disorder, and a higher number of stressors (all P<0.05). 100% of those who received a treatment strategy that included psychiatric therapies reported symptom improvement, compared to 97% who received primarily physical/occupational therapy, and 83% who received few interventions (P = 0.042). CONCLUSIONS:We identified three clinically relevant PASC symptom-based phenotypes, which received different therapeutic interventions with varying response rates. These data may be helpful in tailoring individual treatment programs.

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.

A hub and spoke model offers an effective and efficient approach to providing informed guidance to those who need it. The National Center for Ethics in Health Care (NCEHC) at the Veterans Health Administration, Department of Veterans Affairs, is the largest known hub and spoke healthcare ethics delivery model. In this article, we describe ways NCEHC's hub and spoke configuration succeeded during the COVID-19 pandemic, as well as limitations of the model and possible improvements to inform adoption at other healthcare systems.