Mapping the Ecological Terrain of Stroke Prehospital Delay: A Nationwide Registry Study.

BACKGROUND: Delays in hospital presentation limit access to acute stroke treatments. While prior research has focused on patient-level factors, broader ecological and social determinants have not been well studied. We aimed to create a geospatial map of prehospital delay and examine the role of community-level social vulnerability. METHODS: We studied patients with ischemic stroke who arrived by emergency medical services in 2015 to 2017 from the American Heart Association Get With The Guidelines-Stroke registry. The primary outcome was time to hospital arrival after stroke (in minutes), beginning at last known well in most cases. Using Geographic Information System mapping, we displayed the geography of delay. We then used Cox proportional hazard models to study the relationship between community-level factors and arrival time (adjusted hazard ratios [aHR] <1.0 indicate delay). The primary exposure was the social vulnerability index (SVI), a metric of social vulnerability for every ZIP Code Tabulation Area ranging from 0.0 to 1.0. RESULTS: Of 750 336 patients, 149 145 met inclusion criteria. The mean age was 73 years, and 51% were female. The median time to hospital arrival was 140 minutes (Q1: 60 minutes, Q3: 458 minutes). The geospatial map revealed that many zones of delay overlapped with socially vulnerable areas (https://harvard-cga.maps.arcgis.com/apps/webappviewer/index.html?id=08f6e885c71b457f83cefc71013bcaa7). Cox models (aHR, 95% CI) confirmed that higher SVI, including quartiles 3 (aHR, 0.96 [95% CI, 0.93-0.98]) and 4 (aHR, 0.93 [95% CI, 0.91-0.95]), was associated with delay. Patients from SVI quartile 4 neighborhoods arrived 15.6 minutes [15-16.2] slower than patients from SVI quartile 1. Specific SVI themes associated with delay were a community's socioeconomic status (aHR, 0.80 [95% CI, 0.74-0.85]) and housing type and transportation (aHR, 0.89 [95% CI, 0.84-0.94]). CONCLUSIONS: This map of acute stroke presentation times shows areas with a high incidence of delay. Increased social vulnerability characterizes these areas. Such places should be systematically targeted to improve population-level stroke presentation times.

Prevalence and Predictors of Inappropriate Antithrombotic Prescription in Patients Presenting With Traumatic Brain Injury.

BACKGROUND AND OBJECTIVES: A growing proportion of the US population is on antithrombotic therapy (AT), most significantly within the older subpopulation. Decision to use AT is a balance between the intended benefits and known bleeding risk, especially after traumatic brain injury (TBI). Preinjury inappropriate AT offers no benefit for the patient and also increases the risk of intracranial hemorrhage and worse outcome in the setting of TBI. Our objective was to examine the prevalence and predictors of inappropriate AT among patients presenting with TBI to a Level-1 Trauma Center. METHODS: A retrospective chart review was performed on all patients with TBI and preinjury AT who presented to our institution between January 2016 and September 2020. Demographic and clinical data were collected. Appropriateness of AT was determined through established clinical guidelines. Clinical predictors were determined by logistic regression. RESULTS: Of 141 included patients, 41.8% were female (n = 59) and the average age (mean ± SD) was 80.6 ± 9.9. The prescribed antithrombotic agents included aspirin (25.5%, n = 36), clopidogrel (22.7%, n = 32), warfarin (46.8%, n = 66), dabigatran (2.1%, n = 3), rivaroxaban (Janssen) (10.6%, n = 15), and apixaban (Bristol-Myers Squibb Co.) (18.4%, n = 26). The indications for AT were atrial fibrillation (66.7%, n = 94), venous thromboembolism (13.4%, n = 19), cardiac stent (8.5%, n = 12), and myocardial infarction/residual coronary disease (11.3%, n = 16). Inappropriate antithrombotic therapy use varied significantly by antithrombotic indication ( P < .001) with the highest rates seen with venous thromboembolism. Predictive factors also include age ( P = .005) with higher rates younger than 65 years and older than 85 years and female sex ( P = .049). Race and antithrombotic agent were not significant predictors. CONCLUSION: Overall, 1 in 10 patients presenting with TBI were found to be on inappropriate AT. Our study is the first to describe this problem and warrants investigation into possible workflow interventions to prevent post-TBI continuation of inappropriate AT.

Personal social networks of people with Down syndrome.

Studies in the neurotypical population have demonstrated that personal social networks can mitigate cognitive decline and the development of Alzheimer disease. To assess whether these benefits can also be extended to people with Down syndrome (DS), we studied whether and how personal networks can be measured in this population. We adapted a personal networks instrument previously created, validated, and implemented for the neurotypical population. We created two versions of the survey: one for participants with DS, ages 25 and older, and another for their study partners, who spent a minimum of 10 h/wk in a caregiver role. Participants with DS gave concordant data to those of study partners. Their personal networks included a median network size of 7.50, density 0.80, constraint 46.00, and effective size 3.07. Personal networks were composed of 50% kin, 80% who live within 15 miles, and 80% who eat a healthy diet. In this proof-of-principle study, we demonstrated that the personal networks of people with DS can be quantitatively analyzed, with no statistical difference between self-report and parent-proxy report. Future research efforts can now evaluate interventions to enhance personal networks for preventing Alzheimer disease in this population.

Head-to-Head Comparison of Social Network Assessments in Stroke Survivors.

BACKGROUND AND PURPOSE: Social networks influence human health and disease through direct biological and indirect psychosocial mechanisms. They have particular importance in neurologic disease because of support, information, and healthy behavior adoption that circulate in networks. Investigations into social networks as determinants of disease risk and health outcomes have historically relied on summary indices of social support, such as the Lubben Social Network Scale-Revised (LSNS-R) or the Stroke Social Network Scale (SSNS). We compared these 2 survey tools to personal network (PERSNET) mapping tool, a novel social network survey that facilitates detailed mapping of social network structure, extraction of quantitative network structural parameters, and characterization of the demographic and health parameters of each network member. METHODS: In a cohort of inpatient and outpatient stroke survivors, we administered LSNS-R, SSNS, and PERSNET in a randomized order to each patient. We used logistic regression to generate correlation matrices between LSNS-R scores, SSNS scores, and PERSNET's network structure (eg, size and density) and composition metrics (eg, percent kin in network). We also examined the relationship between LSNS-R-derived risk of social isolation with PERSNET-derived network size. RESULTS: We analyzed survey responses for 67 participants and found a significant correlation between LSNS-R, SSNS, and PERSNET-derived indices of network structure. We found no correlation between LSNS-R, SSNS, and PERSNET-derived metrics of network composition. Personal network mapping tool structural and compositional variables were also internally correlated. Social isolation defined by LSNS-R corresponded to a network size of <5. CONCLUSIONS: Personal network mapping tool is a valid index of social network structure, with a significant correlation to validated indices of perceived social support. Personal network mapping tool also captures a novel range of health behavioral data that have not been well characterized by previous network surveys. Therefore, PERSNET offers a comprehensive social network assessment with visualization capabilities that quantifies the social environment in a valid and unique manner.