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.

Sustainability of personal social networks of people with Down syndrome

Research continues to demonstrate that the characteristics of one's social network could have an impact on the development of Alzheimer's disease. Given the predisposition of people with Down syndrome to develop Alzheimer's disease, analysis of their social networks has become an emerging focus. Previous pilot research demonstrated that the personal networks of people with DS could be quantitatively analyzed, with no difference between self-report and parent-proxy report. This manuscript focuses on a 12-month follow-up period with the same original participants (24 adults with Down syndrome). Their social networks demonstrated sustainability, but not improvement, as reported by people with DS (mean network size: 8.88; mean density: 0.73; mean constraint: 0.44; mean effective size: 3.58; mean max degree: 6.04; mean degree: 4.78) and their proxies (mean network size: 7.90; mean density: 0.82; mean constraint: 53.13; mean effective size: 2.87; mean max degree: 5.19; mean degree: 4.30). Intentional and continued efforts are likely needed in order to improve the social network measures of people with Down syndrome.

Impact of the COVID-19 Pandemic on the Personal Networks and Neurological Outcomes of People With Multiple Sclerosis: Cross-Sectional and Longitudinal Case-Control Study

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has negatively affected the social fabric.

OBJECTIVE

We evaluated the associations between personal social networks and neurological function in people with multiple sclerosis (pwMS) and controls in the prepandemic and pandemic periods.

METHODS

During the early pandemic (March-December 2020), 8 cohorts of pwMS and controls completed a questionnaire quantifying the structure and composition of their personal social networks, including the health behaviors of network members. Participants from 3 of the 8 cohorts had additionally completed the questionnaire before the pandemic (2017-2019). We assessed neurological function using 3 interrelated patient-reported outcomes: Patient Determined Disease Steps (PDDS), Multiple Sclerosis Rating Scale-Revised (MSRS-R), and Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function. We identified the network features associated with neurological function using paired 2-tailed t tests and covariate-adjusted regressions.

RESULTS

In the cross-sectional analysis of the pandemic data from 1130 pwMS and 1250 controls during the pandemic, having a higher percentage of network members with a perceived negative health influence was associated with worse disability in pwMS (MSRS-R: β=2.181, 95% CI 1.082-3.279; P<.001) and poor physical function in controls (PROMIS Physical Function: β=-5.707, 95% CI -7.405 to -4.010; P<.001). In the longitudinal analysis of 230 pwMS and 136 controls, the networks of all participants contracted, given an increase in constraint (pwMS-prepandemic: mean 52.24, SD 15.81; pwMS-pandemic: mean 56.77, SD 18.91; P=.006. Controls-prepandemic: mean 48.07, SD 13.36; controls-pandemic: mean 53.99, SD 16.31; P=.001) and a decrease in network size (pwMS-prepandemic: mean 8.02, SD 5.70; pwMS-pandemic: mean 6.63, SD 4.16; P=.003. Controls-prepandemic: mean 8.18, SD 4.05; controls-pandemic: mean 6.44, SD 3.92; P<.001), effective size (pwMS-prepandemic: mean 3.30, SD 1.59; pwMS-pandemic: mean 2.90, SD 1.50; P=.007. Controls-prepandemic: mean 3.85, SD 1.56; controls-pandemic: mean 3.40, SD 1.55; P=.01), and maximum degree (pwMS-prepandemic: mean 4.78, SD 1.86; pwMS-pandemic: mean 4.32, SD 1.92; P=.01. Controls-prepandemic: mean 5.38, SD 1.94; controls-pandemic: mean 4.55, SD 2.06; P<.001). These network changes were not associated with worsening function. The percentage of kin in the networks of pwMS increased (mean 46.06%, SD 29.34% to mean 54.36%, SD 30.16%; P=.003) during the pandemic, a change that was not seen in controls.

CONCLUSIONS

Our findings suggest that high perceived negative health influence in the network was associated with worse function in all participants during the pandemic. The networks of all participants became tighter knit, and the percentage of kin in the networks of pwMS increased during the pandemic. Despite these perturbations in social connections, network changes from the prepandemic to the pandemic period were not associated with worsening function in all participants, suggesting possible resilience.

Personal Social Networks and Care-Seeking for Head and Neck Cancer: A Qualitative Study

OBJECTIVES

To investigate the role of patients' personal social networks (SNs) in accessing head and neck cancer (HNC) care through patients' and health care workers' (HCWs) perspectives.

STUDY DESIGN

Qualitative study.

SETTING

Tertiary HNC centers at 2 academic medical centers, including 1 safety net hospital.

METHODS

Patients with newly diagnosed HNC, and HCWs caring for HNC patients, aged ≥18 years were recruited between June 2022 and July 2023. Semistructured interviews were conducted with both patients and HCWs. Inductive and deductive thematic analysis was performed with 2 coders (κ = 0.82) to analyze the data.

RESULTS

The study included 72 participants: 42 patients (mean age 57 years, 64% female, 81% white), and 30 HCWs (mean age 42 years, 77% female, 83% white). Four themes emerged: (1) Patients' SNs facilitate care through various forms of support, (2) patients may hesitate to seek help from their networks, (3) obligations toward SNs may act as barriers to seeking care, and (4) the SN composition and dedication influence care-seeking.

CONCLUSION

Personal SNs play a vital role in prompting early care-seeking among HNC patients. SN-based interventions could enhance care and improve outcomes for HNC patients.

Dissecting patterns and predictors of interhospital transfers for patients with brain metastasis

OBJECTIVE

Interhospital transfers in the acute setting may contribute to high cost, patient inconvenience, and delayed treatment. The authors sought to understand patterns and predictors in the transfer of brain metastasis patients after emergency department (ED) encounter.

METHODS

The authors analyzed 3037 patients with brain metastasis who presented to the ED in Massachusetts and were included in the Healthcare Cost and Utilization Project State Inpatient Database and State Emergency Department Database in 2018 and 2019.

RESULTS

The authors found that 6.9% of brain metastasis patients who presented to the ED were transferred to another facility, either directly or indirectly after admission. The sending EDs were more likely to be nonteaching hospitals without neurosurgery and radiation oncology services (p < 0.01). Transferred patients were more likely to present with neurological symptoms compared to those admitted or discharged (p < 0.01). Among those transferred, approximately 30% did not undergo a significant procedure after transfer and approximately 10% were discharged within 3 days, in addition to not undergoing significant interventions. In total, 74% of transferred patients were sent to a facility significantly farther (> 3 miles) than the nearest facility with neurosurgery and radiation oncology services. Further distance transfers were not associated with improvements in 30-day readmission rate (OR [95% CI] 0.64 [0.30-1.34] for 15-30 miles; OR [95% CI] 0.73 [0.37-1.46] for > 30 miles), 90-day readmission rate (OR [95% CI] 0.50 [0.18-1.28] for 15-30 miles; OR [95% CI] 0.53 [0.18-1.51] for > 30 miles), and length of stay (OR [95% CI] 1.21 days [0.94-1.29] for both 15-30 miles and > 30 miles) compared to close-distance transfers.

CONCLUSIONS

The authors identified a notable proportion of transfers without subsequent significant intervention or appreciable medical management. This may reflect ED physician discomfort with the neurological symptoms of brain metastasis. Many patients were also transferred to hospitals distant from their point of origin and demonstrated no differences in readmission rates and length of stay.

Understanding Stakeholders' Perspectives to Increase COVID-19 Vaccine and Booster Uptake Among Black Individuals With Rheumatic Conditions

OBJECTIVE

Disparities in COVID-19 vaccine and booster uptake persist. This study aimed to obtain perspectives from community and physician stakeholders on COVID-19 vaccine and booster hesitancy and strategies to promote vaccine uptake among Black individuals with rheumatic and musculoskeletal conditions.

METHODS

We invited community leaders and physicians in greater Boston and Chicago to participate in semi-structured interviews using a moderator guide developed a priori. Participants were queried about how to best address vaccine hesitancy, strategies to target high-risk populations, and factors to identify future community leaders. Interviews were audio recorded, transcribed verbatim, and analyzed thematically using Dedoose.

RESULTS

A total of 8 physicians and 12 community leaders participated in this study between November 2021 and October 2022. Qualitative analyses revealed misinformation/mixed messaging and mistrust, with subthemes including conspiracy theories, concerns regarding vaccine development and function, racism and historical injustices, and general mistrust of health care systems as the top cited reasons for COVID-19 vaccine hesitancy. Participants also shared demographic-specific differences, such as race, ethnicity, age, and gender that influenced the identified themes, with emphasis on COVID-19 vaccine access and apathy. Strategies for community-based vaccine-related information dissemination included personal storytelling with an iterative and empathetic approach, while recognizing the importance of protecting community leader well-being.

CONCLUSION

To increase vaccine uptake among Black individuals with rheumatic conditions, strategies should acknowledge and respond to racial/ethnic and socioeconomic injustices that engender vaccine hesitancy. Messaging should be compassionate, individually tailored, and recognize heterogeneity in experiences and opinions. Results from these analyses will inform a planned community-based intervention in Boston and Chicago.

Hearing and sociality: the implications of hearing loss on social life

Hearing is essential to the formation of social relationships and is the principal afferent of social life. Yet hearing loss, which is one of the most prevalent forms of sensory disability worldwide and is critical for social development, has received little attention from the social interventionalist perspective. The purpose of this mini-review is to describe the basic neurobiological principles of hearing and to explore the reciprocal relationships between social support, hearing loss, and its psychosocial comorbidities. We also discuss the role of social enrichment in sensorineural recovery and identify open questions within the fields of hearing physiology and social networks.

SocialBit: protocol for a prospective observational study to validate a wearable social sensor for stroke survivors with diverse neurological abilities

INTRODUCTION

Social isolation has been found to be a significant risk factor for health outcomes, on par with traditional risk factors. This isolation is characterised by reduced social interactions, which can be detected acoustically. To accomplish this, we created a machine learning algorithm called SocialBit. SocialBit runs on a smartwatch and detects minutes of social interaction based on vocal features from ambient audio samples without natural language processing.

METHODS AND ANALYSIS

In this study, we aim to validate the accuracy of SocialBit in stroke survivors with varying speech, cognitive and physical deficits. Training and testing on persons with diverse neurological abilities allows SocialBit to be a universally accessible social sensor. We are recruiting 200 patients and following them for up to 8 days during hospitalisation and rehabilitation, while they wear a SocialBit-equipped smartwatch and engage in naturalistic daily interactions. Human observers tally the interactions via a video livestream (ground truth) to analyse the performance of SocialBit against it. We also examine the association of social interaction time with stroke characteristics and outcomes. If successful, SocialBit would be the first social sensor available on commercial devices for persons with diverse abilities.

ETHICS AND DISSEMINATION

This study has received ethical approval from the Institutional Review Board of Mass General Brigham (Protocol #2020P003739). The results of this study will be published in a peer-reviewed journal.

Mild Neurocognitive Disorder, Social Engagement, and Falls Among Older Primary Care Patients

OBJECTIVES

(1) To estimate the association between social engagement (SE) and falls; (2) To examine the relation between mild neurocognitive disorder (MNCD) and falls by different levels of SE.

DESIGN

We performed a secondary data analysis using prospective cohort study design.

SETTING

Primary care.

PARTICIPANTS

A total of 425 older adult primary care patients at risk for mobility decline (N=425). As previously reported, at baseline, 42% of participants exhibit MNCD.

MAIN OUTCOME MEASURES

The outcome variable was the number of falls during 2 years of follow-up. Exposure variables at baseline included (1) MNCD identified using a cut-off of 1.5 SD below the age-adjusted mean on at least 2 measures within a cognitive performance battery and (2) SE, which was assessed using the social component of the Late-Life Function and Disability Instrument. High SE was defined as having a score ≥ median value (≥49 out of 100). All models were adjusted for age, sex, education, marital status, comorbidities, and pain status.

RESULTS

Over 2 years of follow-up, 48% of participants fell at least once. MNCD was associated with a higher rate of falls, adjusting for the covariates (Incidence Rate Ratio=1.6, 95% confidence interval: 1.1-2.3). There was no significant association between MNCD and the rate of falls among people with high SE. In participants with low SE (having a score less than 49.5 out 100), MNCD was associated with a higher rate of falls as compared with participants with no neurocognitive disorder (No-NCD).

CONCLUSIONS

Among participants with low SE, MNCD was associated with a higher rate of falls, but not among participants with high SE. The findings suggest that high SE may be protective against falls among older primary care patients with MNCD.

Association of hospital centrality in inter-hospital patient-sharing networks with patient mortality and length of stay

OBJECTIVE

The interdependence of hospitals is underappreciated in patient outcomes studies. We used a network science approach to foreground this interdependence. Specifically, within two large state-based interhospital networks, we examined the relationship of a hospital's network position with in-hospital mortality and length of stay.

METHODS

We constructed interhospital network graphs using data from the Healthcare Cost and Utilization Project and the American Hospital Association Annual Survey for Florida (2014) and California (2011). The exposure of interest was hospital centrality, defined as weighted degree (sum of all ties to a given hospital from other hospitals). The outcomes were in-hospital mortality and length of stay with sub-analyses for four acute medical conditions: pneumonia, heart failure, ischemic stroke, myocardial infarction. We compared outcomes for each quartile of hospital centrality relative to the most central quartile (Q4), independent of patient- and hospital-level characteristics, in this retrospective cross-sectional study.

RESULTS

The inpatient cohorts had 1,246,169 patients in Florida and 1,415,728 in California. Compared to Florida's central hospitals which had an overall mortality 1.60%, peripheral hospitals had higher in-hospital mortality (1.97%, adjusted OR (95%CI): Q1 1.61 (1.37, 1.89), p<0.001). Hospitals in the middle quartiles had lower in-hospital mortality compared to central hospitals (%, adjusted OR (95% CI): Q2 1.39%, 0.79 (0.70, 0.89), p<0.001; Q3 1.33%, 0.78 (0.70, 0.87), p<0.001). Peripheral hospitals had longer lengths of stay (adjusted incidence rate ratio (95% CI): Q1 2.47 (2.44, 2.50), p<0.001). These findings were replicated in California, and in patients with heart failure and pneumonia in Florida. These results show a u-shaped distribution of outcomes based on hospital network centrality quartile.

CONCLUSIONS

The position of hospitals within an inter-hospital network is associated with patient outcomes. Specifically, hospitals located in the peripheral or central positions may be most vulnerable to diminished quality outcomes due to the network. Results should be replicated with deeper clinical data.

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.

Impact of the COVID-19 Pandemic on Personal Networks and Neurological Outcomes of People with Multiple Sclerosis: A Case-Control Cross-sectional and Longitudinal Analysis

Background

The COVID-19 pandemic has negatively impacted the social fabric of people with multiple sclerosis (pwMS).

Objective

To evaluate the associations between personal social network environment and neurological function in pwMS and controls during the COVID-19 pandemic and compare with the pre-pandemic baseline.

Methods

We first analyzed data collected from 8 cohorts of pwMS and control participants during the COVID-19 pandemic (March-December 2020). We then leveraged data collected between 2017-2019 in 3 of the 8 cohorts for longitudinal comparison. Participants completed a questionnaire that quantified the structure and composition of their personal social network, including the health behaviors of network members. We assessed neurological disability using three interrelated patient-reported outcomes: Patient Determined Disease Steps (PDDS), Multiple Sclerosis Rating Scale â€" Revised (MSRS-R), and Patient Reported Outcomes Measurement Information System (PROMIS)-Physical Function. We identified the network features associated with neurologic disability using paired t-tests and covariate-adjusted regressions.

Results

In the cross-sectional analysis of the pandemic data from 1130 pwMS and 1250 control participants, higher percent of network members with a perceived negative health influence was associated with greater neurological symptom burden in pwMS (MSRS-R: Beta[95% CI]=2.181[1.082, 3.279], p<.001) and worse physical function in controls (PROMIS-Physical Function: Beta[95% CI]=-5.707[-7.405, -4.010], p<.001). In the longitudinal analysis of 230 pwMS and 136 control participants, the networks of both pwMS and controls experienced an increase in constraint (pwMS p=.006, control p=.001) as well as a decrease in network size (pwMS p=.003, control p<.001), effective size (pwMS p=.007, control p=.013), maximum degree (pwMS p=.01, control p<.001), and percent contacted weekly or less (pwMS p<.001, control p<.001), suggesting overall network contraction during the COVID-19 pandemic. There was also an increase in percentage of kin (p=.003) in the networks of pwMS but not controls during the COVID-19 pandemic when compared to the pre-pandemic baseline. These changes in personal social network due to the pandemic were not associated with worsening neurological disability during the pandemic.

Conclusions

Our findings suggest that perceived negative health influences in personal social networks are associated with worse disability in all participants during the COVID-19 pandemic. Despite the perturbation in social environment and connections during the pandemic, the stability in neurological function among pwMS suggests potential resilience.

Survival and renal outcomes of direct heart transplant from veno-arterial extracorporeal membrane oxygenation support

Backgrounds

Patients on veno-arterial extracorporeal membrane oxygenation (VA-ECMO) support are given the highest priority for cardiac transplantation (OHT) in the new UNOS heart allocation policy adopted in October 2018. Although patients may receive an organ quicker there may not be enough time to recover end-organ function. To date, little is known about survival and renal outcomes of direct OHT in patients that have been supported with VA-ECMO as a bridge to transplant due to limited experience in most transplant centers.

Purpose

The aim of this study was to investigate survival and renal outcomes of direct OHT in patients supported with VA-ECMO prior to transplant.

Methods

From January 2010 to February 2022, 23 patients who received single organ OHT alone directly from VA-ECMO support were retrospectively analyzed (16 patients after the new allocation policy). Kaplan-Meier analysis was used to estimate event-free survival.

Results

The median age of recipients was 48 years. The median length of pre-transplant VA-ECMO support was 5 days. Additional pre-transplant support with intra-aortic balloon pump or Impella was utilized in 15 patients (65.2%) and 2 patients (9%) respectively. There was a trend toward improvement of serum creatinine after initiation of VA-ECMO support (Pre-ECMO: 1.66±1.22 mg/dl vs. Pre-OHT: 1.20±0.74 mg/dl, P=0.084). Four patients required preoperative renal replacement therapy (RRT); three were on RRT at the time of OHT. The median ischemic time of donor hearts was 168 minutes. VA-ECMO support was continued in 10 patients (43.5%) after OHT.

Hospital mortality was 8.7% (2 patients). Post-transplant RRT was required in 9 patients (39.1%), and, of these, 5 patients were transitioned to permanent dialysis. Among the 14 patients who did not require post-transplant RRT, none required RRT during the follow-up period (median, 21.5 months). Kaplan-Meier survival analysis showed that estimated survival at 1 year and 3 years were 86.1%, and 77.5%, respectively (Figure 1A). The freedom from dialysis rate was 82.4% at 1 year, and 74.9% at 3 years (Figure 2A). Both survival (100% vs. 66.7%, P=0.008, Fig.1B) and dialysis free rate (100% vs. 55.6%, P=0.002, Figure 2B) at one-year were significantly worse in patients who required postoperative RRT.

Conclusions

To our knowledge this is the largest single center study of OHT in patients that were supported with VA-ECMO. VA-ECMO as a bridge to end-organ recovery and OHT resulted in excellent outcomes. Patients who required post-transplant RRT more likely to require long-term dialysis, while those that did not receive RRT showed favorable outcomes. Overall survival in this patient population is comparable to patients that were not on VA-ECMO prior to transplant.

Funding Acknowledgement

Type of funding sources: None.

Understanding Online and Offline Social Networks in Illness Management of Older Patients With Asthma and Chronic Obstructive Pulmonary Disease: Mixed Methods Study Using Quantitative Social Network Assessment and Qualitative Analysis

Background

Individuals’ social networks and social support are fundamental determinants of self-management and self-efficacy. In chronic respiratory conditions, social support can be promoted and optimized to facilitate the self-management of breathlessness.

Objective

This study aimed to identify how online and offline social networks play a role in the health management of older patients with chronic respiratory conditions, explore the role of support from online peers in patients’ self-management, and understand the barriers to and potential benefits of digital social interventions.

Methods

We recruited participants from a hospital-run singing group to a workshop in London, the United Kingdom, and adapted PERSNET, a quantitative social network assessment tool. The second workshop was replaced by telephone interviews because of the COVID-19 lockdown. The transcripts were analyzed using thematic analysis.

Results

A total of 7 participants (2/7, 29%, men and 5/7, 71%, women), with an age range of 64 to 81 years, produced network maps that comprised between 5 and 10 individuals, including family members, health care professionals, colleagues, activity groups, offline and online friends, and peers. The visual maps facilitated reflections and enhanced participants’ understanding of the role of offline and online social networks in the management of chronic respiratory conditions. It also highlighted the work undertaken by the networks themselves in the self-management support. Participants with small, close-knit networks received physical, health, and emotional support, whereas those with more diverse and large networks benefited from accessing alternative and complementary sources of information. Participants in the latter type of network tended to communicate more openly and comfortably about their illness, shared the impact of their illness on their day-to-day life, and demonstrated distinct traits in terms of identity and perception of chronic disease. Participants described the potential benefits of expanding their networks to include online peers as sources of novel information, motivation, and access to supportive environments. Lack of technological skills, fear of being scammed, or preference for keeping illness-related problems for themselves and immediate family were reported by some as barriers to engaging with online peer support.

Conclusions

In this small-scale study, the social network assessment tool proved feasible and acceptable. These data show the value of using a social network tool as a research tool that can help assess and understand network structure and engagement in the self-management support and could be developed into an intervention to support self-management. Patients’ preferences to share illness experiences with their online peers, as well as the contexts in which this can be acceptable, should be considered when developing and offering digital social interventions. Future studies can explore the evolution of the social networks of older people with chronic illnesses to understand whether their willingness to engage with online peers can change over time.

Association of Traumatic Brain Injury With the Risk of Developing Chronic Cardiovascular, Endocrine, Neurological, and Psychiatric Disorders

IMPORTANCE

Increased risk of neurological and psychiatric conditions after traumatic brain injury (TBI) is well-defined. However, cardiovascular and endocrine comorbidity risk after TBI in individuals without these comorbidities and associations with post-TBI mortality have received little attention.

OBJECTIVE

To assess the incidence of cardiovascular, endocrine, neurological, and psychiatric comorbidities in patients with mild TBI (mTBI) or moderate to severe TBI (msTBI) and analyze associations between post-TBI comorbidities and mortality.

DESIGN, SETTING, AND PARTICIPANTS

This prospective longitudinal cohort study used hospital-based patient registry data from a tertiary academic medical center to select patients without any prior clinical comorbidities who experienced TBI from 2000 to 2015. Using the same data registry, individuals without head injuries, the unexposed group, and without target comorbidities were selected and age-, sex-, and race-frequency-matched to TBI subgroups. Patients were followed-up for up to 10 years. Data were analyzed in 2021.

EXPOSURES

Mild or moderate to severe head trauma.

MAIN OUTCOMES AND MEASURES

Cardiovascular, endocrine, neurologic, and psychiatric conditions were defined based on International Classification of Diseases, Ninth Revision (ICD-9) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10). Associations between TBI and comorbidities, as well as associations between the comorbidities and mortality, were analyzed.

RESULTS

A total of 4351 patients with mTBI (median [IQR] age, 45 [29-57] years), 4351 patients with msTBI (median [IQR] age, 47 [30-58] years), and 4351 unexposed individuals (median [IQR] age, 46 [30-58] years) were included in analyses. In each group, 45% of participants were women. mTBI and msTBI were significantly associated with higher risks of cardiovascular, endocrine, neurologic, and psychiatric disorders compared with unexposed individuals. In particular, hypertension risk was increased in both mTBI (HR, 2.5; 95% CI, 2.1-2.9) and msTBI (HR, 2.4; 95% CI, 2.0-2.9) groups. Diabetes risk was increased in both mTBI (HR, 1.9; 95% CI, 1.4-2.7) and msTBI (HR, 1.9; 95% CI, 1.4-2.6) groups, and risk of ischemic stroke or transient ischemic attack was also increased in mTBI (HR, 2.2; 95% CI, 1.4-3.3) and msTBI (HR, 3.6; 95% CI, 2.4-5.3) groups. All comorbidities in the TBI subgroups emerged within a median (IQR) of 3.49 (1.76-5.96) years after injury. Risks for post-TBI comorbidities were also higher in patients aged 18 to 40 years compared with age-matched unexposed individuals: hypertension risk was increased in the mTBI (HR, 5.9; 95% CI, 3.9-9.1) and msTBI (HR, 3.9; 95% CI, 2.5-6.1) groups, while hyperlipidemia (HR, 2.3; 95% CI, 1.5-3.4) and diabetes (HR, 4.6; 95% CI, 2.1-9.9) were increased in the mTBI group. Individuals with msTBI, compared with unexposed patients, had higher risk of mortality (432 deaths [9.9%] vs 250 deaths [5.7%]; P < .001); postinjury hypertension (HR, 1.3; 95% CI, 1.1-1.7), coronary artery disease (HR, 2.2; 95% CI, 1.6-3.0), and adrenal insufficiency (HR, 6.2; 95% CI, 2.8-13.0) were also associated with higher mortality.

CONCLUSIONS AND RELEVANCE

These findings suggest that TBI of any severity was associated with a higher risk of chronic cardiovascular, endocrine, and neurological comorbidities in patients without baseline diagnoses. Medical comorbidities were observed in relatively young patients with TBI. Comorbidities occurring after TBI were associated with higher mortality. These findings suggest the need for a targeted screening program for multisystem diseases after TBI, particularly chronic cardiometabolic diseases.

Leveraging Social Networks for the Assessment and Management of Neurological Patients

Social networks are the persons surrounding a patient who provide support, circulate information, and influence health behaviors. For patients seen by neurologists, social networks are one of the most proximate social determinants of health that are actually accessible to clinicians, compared with wider social forces such as structural inequalities. We can measure social networks and related phenomena of social connection using a growing set of scalable and quantitative tools increasing familiarity with social network effects and mechanisms. This scientific approach is built on decades of neurobiological and psychological research highlighting the impact of the social environment on physical and mental well-being, nervous system structure, and neuro-recovery. Here, we review the biology and psychology of social networks, assessment methods including novel social sensors, and the design of network interventions and social therapeutics.

Concussion and Risk of Chronic Medical and Behavioral Health Comorbidities

While chronic neurological effects from concussion have been studied widely, little is known about possible links between concussion and long-term medical and behavioral comorbidities. We performed a retrospective cohort study of 9205 adult patients with concussion, matched to non-concussion controls from a hospital-based electronic medical registry. Patients with comorbidities before the index visit were excluded. Behavioral and medical comorbidities were defined by International Classification of Diseases, Ninth and Tenth Revision codes. Groups were followed for up to 10 years to identify comorbidity incidence after a concussion. Cox proportional hazards models were used to calculate associations between concussion and comorbidities after multi-variable adjustment. Patients with concussion were 57% male (median age: 31; interquartile range [IQR] = 23-48 years) at enrollment with a median follow-up time of 6.1 years (IQR = 4.2-9.1) and well-matched to healthy controls. Most (83%) concussions were evaluated in outpatient settings (5% inpatient). During follow-up, we found significantly higher risks of cardiovascular risks developing including hypertension (hazard ratio [HR] = 1.7, 95% confidence interval [CI]: 1.5-1.9), obesity (HR = 1.7, 95% CI: 1.3-2.0), and diabetes mellitus (HR = 1.8, 95% CI: 1.4-2.3) in the concussion group compared with controls. Similarly, psychiatric and neurological disorders such as depression (HR = 3.0, 95% CI: 2.6-3.5), psychosis (HR = 6.0, 95% CI: 4.2-8.6), stroke (HR = 2.1 95% CI: 1.5-2.9), and epilepsy (HR = 4.4, 95% CI: 3.2-5.9) were higher in the concussion group. Most comorbidities developed less than five years post-concussion. The risks for post-concussion comorbidities were also higher in patients under 40 years old compared with controls. Patients with concussion demonstrated an increased risk of development of medical and behavioral health comorbidities. Prospective studies are warranted to better describe the burden of long-term comorbidities in patients with concussion.

Disparities in the Geographic Distribution of Neurosurgeons in the United States: A Geospatial Analysis

OBJECTIVE

Large disparities in access to neurosurgical care are known, but there are limited data on whether geographic distribution of the neurosurgery workforce potentially plays a role in these disparities. The goal of this study was to identify the geographic distribution of neurosurgeons in the United States and to study the association of the per capita workforce distribution with socioeconomic characteristics of the population.

METHODS

The number of practicing neurosurgeons in the United States in 2016 was obtained from the 2017-2018 American Medical Association Masterfile contained within the Area Health Resource File. The association of the number of neurosurgeons per 100,000 population with socioeconomic characteristics was assessed through linear regression analysis at Hospital Referral Region (HRR) level.

RESULTS

The median number of neurosurgeons per capita across all HRRs was 1.47 neurosurgeons per 100,000 population (interquartile range, 1.02-2.27). Bivariable analysis showed that greater supply of neurosurgeons was positively associated with regional levels of college education, median income, and median age. The number of neurosurgeons per capita at the HRR level was negatively associated with unemployment, poverty, and percent uninsured.

CONCLUSIONS

Regions characterized by low socioeconomic status have fewer neurosurgeons per capita in the United States. Low income, low number of college graduates, and high unemployment rate are associated with fewer numbers of neurosurgeons per capita. Further research is needed to determine if these geographic workforce disparities contribute to poor access to quality neurosurgical care.

Abstract P91: Excess Cerebrovascular Mortality in the U.S. During the Covid-19 Pandemic

Introduction: The magnitude and drivers of excess cerebrovascular-specific mortality during the coronavirus-19 (COVID-19) pandemic are unknown. We aim to quantify excess stroke-related death and characterize its association with psychosocial factors and emerging COVID-19 related mortality.

Methods: U.S. and state-level excess cerebrovascular deaths from January-May 2020 were quantified by Poisson regression models built using National Center for Health Statistic (NCHS) data. Weekly excess cerebrovascular deaths in the U.S. were analyzed as functions of time-varying, weekly stroke-related EMS calls and weekly COVID-19 deaths by univariable linear regression. A state-level negative binomial regression analysis was performed to determine the association between excess cerebrovascular deaths and social distancing (degree of change in mobility per Google COVID-19 Community Mobility Reports) during the height of the pandemic after the first COVID-19 death (February 29, 2020), adjusting for cumulative COVID-19 related deaths and completeness of deaths attributable to COVID-19 in NCHS.

Findings: There were 918 more cerebrovascular deaths than expected from January 1-May 16 th , 2020 in the U.S. Excess cerebrovascular mortality occurred during every week between March 28-May 2 nd , 2020, up to 7.8% during the week of April 18 th . Decreased stroke-related EMS calls were associated with excess stroke deaths one (β -0.06, 95% CI -0.11, -0.02) and two weeks (β -0.08, 95% CI -0.12, -0.04) later. There was no significant association between weekly excess stroke death and COVID-19 death. Twenty-three states and NYC experienced excess cerebrovascular mortality during the pandemic height. At the state level, a 10% increase in social distancing was associated with a 4.3% increase in stroke deaths (IRR 1.043, 95% CI 1.001–1.085) after adjusting for COVID-19 mortality.

Conclusions: Excess U.S. cerebrovascular deaths during the COVID-19 pandemic were observed with decreases in stroke-related EMS calls nationally and less mobility at the state level. Public health measures are needed to identify and counter the reticence to seeking medical care for acute stroke during the COVID-19 pandemic.

Abstract P133: Geospatial Mapping of Prehospital Delay in Acute Ischemic Stroke and Association With Social Vulnerability

Introduction: Prehospital delay, defined as the delay between symptom discovery and hospital arrival, remains a major barrier to timely acute stroke treatments. Delay is worse in socially vulnerable populations. A geospatial map of prehospital delay may identify high-risk areas and highlight the role of community social vulnerability in delay. We hypothesized that a community’s social vulnerability would be associated with delay.

Methods: We analyzed national Get With The Guidelines ischemic stroke data between 2015 and 2017. We calculated the median arrival time (symptom discovery-to-door times) for each Zip Code Tabulation Area (ZCTA), and created geospatial map using ArcGIS. The primary exposure variable was the Center for Disease Control’s Social Vulnerability Index (SVI), and its 4 subcomponents. The SVI is a composite metric of community vulnerability using U.S. Census data (0, least vulnerable to 1, most vulnerable). To account for clustering within ZCTAs, we performed a multilevel linear regression of community-level SVI and patient-level prehospital delay.

Results: During the study period, 149,774 patients had an ischemic stroke in 16,949 ZCTAs. Across patients, the median time of arrival was 140 mins, IQR was 60-459 mins, and range was 1-1439 mins. Arrival by 2h occurred in 46% of patients. Multilevel regression showed a strong positive association between the SVI and prehospital delay, evident in the maps (Figure). For every 10% increase in the SVI, the arrival time increased by 38 minutes [CI, 30 - 47] (p<0.001). Considering the 4 SVI subcomponents, delay was most strongly associated with socioeconomic status, household composition, and housing/transportation, but not minority status/language.

Conclusion: Using geospatial mapping of prehospital delay across the United States, we show that community SVI is strongly associated with delayed ischemic stroke arrival. These maps help identify communities to target for stroke preparedness campaigns.

A Feasibility Study of Expanded Home-Based Telerehabilitation After Stroke

Introduction: High doses of activity-based rehabilitation therapy improve outcomes after stroke, but many patients do not receive this for various reasons such as poor access, transportation difficulties, and low compliance. Home-based telerehabilitation (TR) can address these issues. The current study evaluated the feasibility of an expanded TR program. Methods: Under the supervision of a licensed therapist, adults with stroke and limb weakness received home-based TR (1 h/day, 6 days/week) delivered using games and exercises. New features examined include extending therapy to 12 weeks duration, treating both arm and leg motor deficits, patient assessments performed with no therapist supervision, adding sensors to real objects, ingesting a daily experimental (placebo) pill, and generating automated actionable reports. Results: Enrollees (n = 13) were median age 61 (IQR 52-65.5), and 129 (52-486) days post-stroke. Patients initiated therapy on 79.9% of assigned days and completed therapy on 65.7% of days; median therapy dose was 50.4 (33.3-56.7) h. Non-compliance doubled during weeks 7-12. Modified Rankin scores improved in 6/13 patients, 3 of whom were >3 months post-stroke. Fugl-Meyer motor scores increased by 6 (2.5-12.5) points in the arm and 1 (-0.5 to 5) point in the leg. Assessments spanning numerous dimensions of stroke outcomes were successfully implemented; some, including a weekly measure that documented a decline in fatigue (p = 0.004), were successfully scored without therapist supervision. Using data from an attached sensor, real objects could be used to drive game play. The experimental pill was taken on 90.9% of therapy days. Automatic actionable reports reliably notified study personnel when critical values were reached. Conclusions: Several new features performed well, and useful insights were obtained for those that did not. A home-based telehealth system supports a holistic approach to rehabilitation care, including intensive rehabilitation therapy, secondary stroke prevention, screening for complications of stroke, and daily ingestion of a pill. This feasibility study informs future efforts to expand stroke TR. Clinical Trial Registration: Clinicaltrials.gov, # NCT03460587.

Social Network Structure Is Related to Functional Improvement From Home-Based Telerehabilitation After Stroke

Objective: Telerehabilitation (TR) is now, in the context of COVID-19, more clinically relevant than ever as a major source of outpatient care. The social network of a patient is a critical yet understudied factor in the success of TR that may influence both engagement in therapy programs and post-stroke outcomes. We designed a 12-week home-based TR program for stroke patients and evaluated which social factors might be related to motor gains and reduced depressive symptoms. Methods: Stroke patients (n = 13) with arm motor deficits underwent supervised home-based TR for 12 weeks with routine assessments of motor function and mood. At the 6-week midpoint, we mapped each patient's personal social network and evaluated relationships between social network metrics and functional improvements from TR. Finally, we compared social networks of TR patients with a historical cohort of 176 stroke patients who did not receive any TR to identify social network differences. Results: Both network size and network density were related to walk time improvement (p = 0.025; p = 0.003). Social network density was related to arm motor gains (p = 0.003). Social network size was related to reduced depressive symptoms (p = 0.015). TR patient networks were larger (p = 0.012) and less dense (p = 0.046) than historical stroke control networks. Conclusions: Social network structure is positively related to improvement in motor status and mood from TR. TR patients had larger and more open social networks than stroke patients who did not receive TR. Understanding how social networks intersect with TR outcomes is crucial to maximize effects of virtual rehabilitation.

Social network structure and composition in former NFL football players

Social networks have broad effects on health and quality of life. Biopsychosocial factors may also modify the effects of brain trauma on clinical and pathological outcomes. However, social network characterization is missing in studies of contact sports athletes. Here, we characterized the personal social networks of former National Football League players compared to non-football US males. In 303 former football players and 269 US males, we found that network structure (e.g., network size) did not differ, but network composition (e.g., proportion of family versus friends) did differ. Football players had more men than women, and more friends than family in their networks compared to US males. Black players had more racially diverse networks than White players and US males. These results are unexpected because brain trauma and chronic illnesses typically cause diminished social relationships. We anticipate our study will inform more multi-dimensional study of, and treatment options for, contact sports athletes. For example, the strong allegiances of former athletes may be harnessed in the form of social network interventions after brain trauma. Because preserving health of contact sports athletes is a major goal, the study of social networks is critical to the design of future research and treatment trials.

Excess Cerebrovascular Mortality in the United States During the COVID-19 Pandemic

Supplemental Digital Content is available in the text.

The magnitude and drivers of excess cerebrovascular-specific mortality during the coronavirus disease 2019 (COVID-19) pandemic are unknown. We aim to quantify excess stroke-related deaths and characterize its association with social distancing behavior and COVID-19–related vascular pathology.

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.

Association of social network structure and physical function in patients with multiple sclerosis

OBJECTIVE

To test the association between physical function and the social environment in multiple sclerosis (MS), we quantified personal social networks.

METHODS

In this cross-sectional study, we analyzed data from 2 academic MS centers, with center 1 serving as a discovery group and center 2 as the extension group. We performed a meta-analysis of the centers to extend the analysis. We used responses from a questionnaire to map the structure and health habits of participants' social networks as well as the NIH Patient-Reported Outcomes Measurement Information System (PROMIS) physical function scale (0-100, mean 50 for US general population) as the primary outcome. We applied multivariable models to test the association between network metrics and physical function.

RESULTS

The discovery cohort included 263 patients with MS: 81% were women, 96% non-Hispanic European, 78% had relapsing MS, average age was 50 (12.4) years, and mean disease duration was 17 (12.3) years. The extension group included 163 patients, who were younger, more racially diverse, and less physically disabled, and had shorter disease duration. In the meta-analysis, higher network constraint, a measure of tightly bound networks, was associated with worse physical function (β = -0.163 ± 0.047, p < 0.001), while larger network effective size, a measure of clustered groups in the network, correlated with better physical function (β = 0.134 ± 0.046, p = 0.003).

CONCLUSIONS

Our study highlights personal networks as an important environmental factor associated with physical function in MS. Patients with close-knit networks had worse function than those with more open networks. Longitudinal studies are warranted to evaluate a causal relationship between network structure and physical impairment.

Abstract TMP49: Social Network Simulation Identifies Persistent Racial Disparities of Delay to Hospital in Acute Ischemic Stroke Patients

Introduction: Delayed arrival to the hospital remains the major reason for non-use of stroke therapies. Minority patients have longer delays that have not been adequately understood nor acted upon. Social context plays a key role, because most strokes occur in front of witnesses who influence decision-making. We created a social network simulation to understand the interpersonal factors that influence decision-making, particularly in minority patients.

Methods: We developed an agent-based computer simulation of individual traits and social contextual factors that contribute to decision-making. The inputs into this parsimonious model were based on the largest empirical studies (e.g., Get With The Guidelines) and included: stroke severity, use of Emergency Medical Services (EMS), race, and social network size. The model outputs were the number of stroke patients who arrived at the hospital early (≤3 hours) and late (>3 hours). For each run of the model, 1,000 stroke patients decided to go to the hospital early or late based on individual and social contextual factors. Two sample t-tests were used to compare means between white and non-white patients.

Results: In 1.03 million simulations, the model reproduced observed population trends of delay. The overall mean percent of early arrivers was 25.2% (SD 0.02), which matched national metrics showing good calibration of the model. Race predicted delay and modified the relationship of the main effects. 17.9% of non-white patients arrived early compared to 28.3% white patients (p<0.0001) (Fig 1-A). 17.6% of non-white patients with moderate strokes arrived early compared to 39.8% of white patients (p<0.0001) (Fig 1-B). 18.8% of non-white patients with a social network size of 10 arrived early compared to 31.5% of white patients (p<0.0001) (Fig 1-C).

Conclusion: A social network simulation reproduced persistent racial disparities of delayed arrival allowing for novel interventions to be tested on this platform.

Abstract WP193: A Pilot Study of Expanded Home-Based Telerehabilitation After Stroke

Introduction: High doses of activity-based rehabilitation therapy help but many patients do not receive this, e.g., due to access, cost, and low compliance. Home-based telerehabilitation (TR) can address these issues. A prior study found 6 weeks of TR targeting arm motor deficits after stroke comparably efficacious vs. therapy delivered in-clinic. Here, we evaluated a program expanded in TR dose and scope.

Methods: Adults with stroke and arm motor deficits saw a licensed OT/PT who performed a live exam then supervised home-based TR (6 days/week, 1 hour/day) through games, exercises, and education. New features examined herein included (a) extending therapy to 12 weeks, (b) treating both arm and leg motor deficits, (c) augmented reality games, (d) wireless smart devices, (e) ingesting a daily experimental (placebo) pill, (f) using functional objects, (g) evaluating social networks, and (h) automated actionable reports.

Results: Patients (n=13) were median age 61 [IQR=52-65.5], and 129 [52-486] days post-stroke. Patients initiated therapy on 79.9% of the 72 assigned days and completed >30 min on 65.7% of days, for a 12-week total therapy dose of 50.4 [33.3 - 56.7] hours. Non-compliant days during weeks 7-12 were double those of weeks 1-6. Modified Rankin scores improved by 1 level in 6/13 patients, 3 of whom were > 3month post-stroke. Fugl-Meyer motor scores increased by 6 [2.5-12.5] points in the arm and 1 [-0.5 - 5] point in the leg, mainly in weeks 1-6. Geriatric Depression Scale scores fell from 3 [1-5] at baseline (3/13 with depression) to 1 [0-4] (0/13 with depression) at week 12. Augmented reality gaming and functional objects were well received. Communication with smart devices was challenging. The experimental pill was taken, with photo verification, on 90.9% of days. Enrollees had large social networks. Automatic reports reliably notified study personnel when compliance was low or behavioral scores were concerning.

Conclusions: High doses of home-based TR targeting arm and leg motor deficits are feasible and improve functional outcomes, motor deficits, and mood. The current system automates experimental pill ingestion and actionable reports to clinicians. Compliance declined over time, suggesting the need for novel approaches to extended periods of TR.

Social Network Mapping and Functional Recovery Within 6 Months of Ischemic Stroke

Objective. Stroke recovery is a multidimensional process influenced by biological and psychosocial factors. To understand the latter, we mapped the social networks of stroke patients, analyzing their changes and effects on physical function at 3 and 6 months after stroke. Methods. We used a quantitative social network assessment tool to map the structure and health habits embedded in patients' personal social networks. The physical function outcome was determined using the National Institutes of Health (NIH) Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function Scale (0-100, mean 50 for US general population). We used mixed-effects models to assess changes in social network metrics. We used multivariable models to test the association between social networks and physical function, independent of demographics, socioeconomic status, clinical characteristics, comorbidities, cognition, and depression. Results. The cohort consisted of 172 patients, with mostly mild motor-predominant stroke (median NIH Stroke Scale of 2) with retention of 149 at 3 months and 139 at 6 months. An average patient's network over 6 months contracted by 1.25 people and became denser and family oriented. Network composition also became healthier with pruning of ties with people who smoked or did not exercise. The baseline network size, and not density or health habits in the network, was independently associated with 3- and 6-month physical function PROMIS scores. Patients embedded in small kin-based networks reported more negative social interactions. Conclusions. Despite social networks becoming smaller and close-knit after stroke, they also become healthier. Larger baseline social networks are independently associated with better patient-reported physical function after stroke.

A Network Approach to Stroke Systems of Care

The landscape of stroke systems of care is evolving as patients are increasingly transferred between hospitals for access to higher levels of care. This is driven by time-sensitive disability-reducing interventions such as mechanical thrombectomy. However, coordination and triage of patients for such treatment remain a challenge worldwide, particularly given complex eligibility criteria and varying time windows for treatment. Network analysis is an approach that may be applied to this problem. Hospital networks interlinked by patients moved from facility to facility can be studied using network modeling that respects the interdependent nature of the system. This allows understanding of the central hubs, the change of network structure over time, and the diffusion of innovations. This topical review introduces the basic principles of network science and provides an overview on the applications and potential interventions in stroke systems of care.

Social networks and risk of delayed hospital arrival after acute stroke

Arriving rapidly to the hospital after a heart attack or stroke is critical for patients to be within time windows for treatment. Prior research in heart attacks has suggested a paradoxical role of the social environment: those who arrive early are surrounded by nonrelatives, while those who arrive late are surrounded by spouses or family members. Here, we used network methods to more deeply examine the influence of social context in stroke. We examined the relationship of personal social networks and arrival time in 175 stroke patients. Our results confirmed the paradox by showing that small and close-knit personal networks of highly familiar contacts, independent of demographic, clinical, and socioeconomic factors, were related to delay. The closed network structure led to constricted information flow in which patients and close confidants, absent outside perspectives, elected to watch-and-wait. Targeting patients with small, close-knit networks may be one strategy to improve response times.

Rapid arrival to hospital after stroke is critical for patients to receive effective treatment. Here, the authors examine how stroke patients’ social network structure relates to stroke arrival time, and show that small and close-knit personal networks predict delayed arrival.

Sex Venue-Based Network Analysis to Identify HIV Prevention Dissemination Targets for Men Who Have Sex with Men

PURPOSE

The aim of this study was to identify sex venue-based networks among men who have sex with men (MSM) to inform HIV preexposure prophylaxis (PrEP) dissemination efforts.

METHODS

Using a cross-sectional design, we interviewed MSM about the venues where their recent sexual partners were found. Venues were organized into network matrices grouped by condom use and race. We examined network structure, central venues, and network subgroups.

RESULTS

Among 49 participants, the median age was 27 years, 49% were Black and 86% reported condomless anal sex (ncAS). Analysis revealed a map of 54 virtual and physical venues with an overlap in the ncAS and with condom anal sex (cAS) venues. In the ncAS network, virtual and physical locations were more interconnected. The ncAS venues reported by Blacks were more diffusely organized than those reported by Whites.

CONCLUSION

The network structures of sex venues for at-risk MSM differed by race. Network information can enhance HIV prevention dissemination efforts among subpopulations, including PrEP implementation.

A scalable online tool for quantitative social network assessment reveals potentially modifiable social environmental risks

Social networks are conduits of support, information, and health behavior flows. Existing measures of social networks used in clinical research are typically summative scales of social support or artificially truncated networks of ≤ 5 people. Here, we introduce a quantitative social network assessment tool on a secure open-source web platform, readily deployable in large-scale clinical studies. The tool maps an individual’s personal network, including specific persons, their relationships to each other, and their health habits. To demonstrate utility, we used the tool to measure the social networks of 1493 persons at risk of multiple sclerosis. We examined each person’s social network in relation to self-reported neurological disability. We found that the characteristics of persons surrounding the participant, such as negative health behaviors, were strongly associated with the individual’s functional disability. This quantitative assessment reveals the key elements of individuals’ social environments that could be targeted in clinical trials.

An individual’s social network—their friends, family, and acquaintances—is important for their health, but existing tools for assessing social networks have limitations. Here, the authors introduce a quantitative social network assessment tool on a secure open-source web platform and show its utility in a nation-wide study.

Social Network Trajectories in Myocardial Infarction Versus Ischemic Stroke

BACKGROUND

Changes in social networks are rarely examined before and after various diseases because of insufficient data. CHS (The Cardiovascular Health Study) offers an opportunity to compare social network trajectories surrounding well-adjudicated myocardial infarction (MI) or stroke events. We tested the hypothesis that social networks will be stable after MI and decrease after stroke.

METHODS AND RESULTS

We examined trajectories of the Lubben Social Network Scale score (LSNS, range 0-50) before and after vascular events over 11 years. The LSNS assesses engagement in family networks, friends' networks, and social supports. We used a linear mixed model with repeated measures and fixed effects to compare the change in social network score before and after events in 395 people with MI and 382 with ischemic stroke. Over a mean of 12.4 years of follow-up for MI and 11.1 years for stroke, we examined an average of 4 social network scores for each participant. We controlled for sociodemographics, baseline cognitive function, and comorbidities. The participants' mean age was 73.5, 51% were women, and 88% were non-Hispanic white. After MI, the social network trajectory remained stable compared with the baseline trajectory (-0.06 points per year, adjusted P=0.2356). After stroke, the social network trajectory declined compared with the baseline trajectory (-0.14 points per year, adjusted P=0.0364).

CONCLUSIONS

Social networks remained stable after MI and declined after stroke. This small and persistent decline after adjustment for potential confounders is notable because it deviates from stable network trajectories found in CHS participants and is specific to stroke.

Abstract TMP37: Social Network Size at Stroke Onset is Associated With 3 and 6-Month Stroke Outcomes

Introduction: Social mechanisms involved in stroke recovery are important and underutilized. For at least three decades, research has shown that social factors such as living alone negatively influence outcomes after stroke. Prior studies relied on social support measures without study of the network social structure. Our study uses higher-resolution social network analysis to examine structure (e.g., size and connectivity) and composition (e.g., proportion kin) in relation to stroke outcomes at 3 and 6 months.

Hypothesis: Social network structural traits, size and connectivity, at stroke onset is related to the Patient Recovery Outcome Measurement Information System (PROMIS) physical function score at 3 and 6 months.

Methods: In a cohort study, 160 patients with a first-time ischemic stroke were enrolled at stroke hospitalization. Social network characteristics were assessed using a bedside survey interview. The PROMIS physical function score was assessed on the phone at 3 and 6 months after stroke. Unadjusted and adjusted analyses were completed using Spearman Correlation and multivariate linear regression.

Results: 144 patients (90%) at 3 months and 120 patients (75%) at 6 months completed the study. The mean age was 62, and NIH stroke scale was 3. Social network size at stroke onset was positively associated with 3- (spearman correlation=0.22, p<0.01) and 6-month (spearman correlation=0.21, p=0.02) PROMIS physical function score. Connectivity measures and the proportion of kin in the network were not associated with the outcome. After control of age, stroke severity, and depression, network size remained strongly associated to physical function at 3 and 6-months, beta=0.74 [0.51,0.97], p<0.01.

Conclusions: Of social network traits, network size at stroke onset is independently associated with physical function after stroke. Small networks are an important risk factor for poor recovery, likely equivalent to traditional risk factors.

Adoption and sustained use of cleaner cooking fuels in rural India: a case control study protocol to understand household, network, and organizational drivers

Background

Implementing efficient stoves and clean fuels in low and middle-income countries are critical for improving health of poor women and children and improve the environment. Cleaner biomass stoves, however, perform poorly against the World Health Organization’s indoor air quality guidelines. This has shifted the focus to systematic dissemination and implementation of cleaner cooking systems such as liquefied petroleum gas (LPG) among poor communities. Even when there is some uptake of LPG by poor communities, its sustained use has been low. Concurrent use of LPG with traditional biomass cookstoves compromises reductions in household air pollution and limits health and environmental dividends. Therefore understanding key drivers of adoption and sustained implementation of clean fuels among the poor is critical. There is a significant gap, however, in the research to understand determinants and sustained exclusive use of clean fuels in rural poor communities.

Methods/design

Using a case control study design, this study will explore the impact of affordability, accessibility, and awareness on adoption and sustained use of LPG among rural poor communities of India. The study uses a multistage random sampling to collect primary data from 510 households. Case group or LPG adopters constitute 255 households while control group or non-LPG adopters constitute the remaining 255 households. The study will deploy sophisticated stove use monitoring sensors in each of the stoves in 100 case group households to monitor stove use and stacking behavior (using clean and traditional systems of cooking) of participants for 12 months. Moreover, this will be the first study to explore the impact of personal social networks striated by gender on LPG adoption. This study is guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) implementation science evaluation framework.

Discussion

Lessons from this study will feed into a larger discussion on developing a pro-poor strategy to foster uptake and sustained use of cleaner cooking systems such as LPG. Understanding the determinants of adoption and sustained use of cleaner cooking systems through the RE-AIM framework will expand our insights on implementation of cleaner cooking systems among poor communities and will advance implementation science in the clean cooking sector. A thorough study of such implementation strategies is crucial to realize multiple UN Sustainable Development Goals on global health, climate change, and energy security.

Clival metastasis from a gastrointestinal adenocarcinoma causing multiple cranial neuropathies

A 78-year-old man with a history of benign prostatic hyperplasia presented with double vision, facial pain, altered taste and headache for 7 weeks. Neurological exam was notable for palsies of the right V, VI, VII and XII cranial nerves. An expansive clival mass and multiple lesions in the vertebra were found on MRI. Radionuclide studies showed extensive tumour burden in his liver and peritoneum. His serologies showed normal carcinoembryonic antigen and carbohydrate antigen 19-9 levels and modestly elevated prostate-specific antigen, which was a red herring. Biopsy of his omentum was consistent with metastatic adenocarcinoma with immunostaining indicating an upper gastrointestinal primary tumour. The patient underwent several cycles of radiation therapy, but ultimately elected to pursue hospice care. This case demonstrates the presentation of multiple cranial neuropathies from a clival mass and an unusual primary source from an upper gastrointestinal tumour.

Early Withdrawal Decision-Making in Patients with Coma After Cardiac Arrest: A Qualitative Study of Intensive Care Clinicians

INTRODUCTION

Neurologists are often asked to define prognosis in comatose patients. However, comatose patients following cardiac arrest are usually cared for by cardiologists or intensivists, and it is their approach that will influence decisions regarding withdrawal of life-sustaining interventions (WLSI). We observed that factors leading to these decisions vary across specialties and considered whether they could result in self-fulfilling prophecies and early WLSI. We conducted a hypothesis-generating qualitative study to identify factors used by non-neurologists to define prognosis in these patients and construct an explanatory model for how early WLSI might occur.

METHODS

This was a single-center qualitative study of intensivists caring for cardiac arrest patients with hypoxic-ischemic coma. Thirty attending physicians (n = 16) and fellows (n = 14) from cardiac (n = 8), medical (n = 6), surgical (n = 10), and neuro (n = 6) intensive care units underwent semi-structured interviews. Interview transcripts were analyzed using grounded theory techniques.

RESULTS

We found three components of early WLSI among non-neurointensivists: (1) development of fixed negative opinions; (2) early framing of poor clinical pictures to families; and (3) shortened windows for judging recovery potential. In contrast to neurointensivists, non-neurointensivists' negative opinions were frequently driven by patients' lack of consciousness and cardiopulmonary resuscitation circumstances. Both groups were influenced by age and comorbidities.

CONCLUSIONS

The results demonstrate that factors influencing prognostication differ across specialties. Some differ from those recommended by published guidelines and may lead to self-fulfilling prophecies and early WLSI. Better understanding of this framework would facilitate educational interventions to mitigate this phenomenon and its implications on patient care.

Three months of weekly rifapentine plus isoniazid for latent tuberculosis treatment in solid organ transplant candidates

BACKGROUND

Isoniazid daily for 9 months is the recommended regimen for latent tuberculosis infection (LTBI) in solid organ transplant (SOT) candidates, but its use is controversial, due to reports of hepatotoxicity and low treatment completion rates. A 12-week course of once weekly directly observed therapy (DOT) with isoniazid plus rifapentine (3HP) is a new LTBI treatment regimen. Tolerability and safety data of 3HP LTBI treatment in SOT candidates are limited.

METHODS

Twelve consecutive SOT candidates who underwent DOT with 3HP for LTBI at Westchester Medical Center, Valhalla, New York, USA, between January 2013 and August 2016 were prospectively evaluated for tolerability and safety of 3HP. The diagnosis of LTBI was made in a person with a positive interferon-gamma release test, without a history of previously treated active or latent tuberculosis infection, and without signs, symptoms, or radiographic evidence of active tuberculosis. Patients were followed up 1 month after treatment completion and at routine follow-up visits with their transplant providers.

RESULTS

Eleven patients were men, and the median age was 60 years (range 44-72). Eight patients were liver, and four kidney transplant candidates. The median Model for End-Stage Liver Disease (MELD score) was 17 (range 10-31). All patients completed treatment. Only a single patient developed transaminitis greater than twice the baseline value. Three patients underwent liver transplantation. None of them developed tuberculosis at 9, 22, or 40 months following transplantation.

CONCLUSION

Directly observed 3HP LTBI treatment was not associated with hepatotoxicity, even in patients with higher MELD scores. Further studies are needed to confirm the safety and efficacy of this LTBI treatment regimen in the SOT population.

Monitoring the Diagnostic Process on an Inpatient Neurology Service

The Institute of Medicine report Improving Diagnosis in Health Care called for tools to monitor physicians' diagnostic process. We addressed this need by developing a tool for clinicians to record and analyze their diagnostic process. The tool was a secure web application in which clinicians used a structured grading system to assess the relative impact of clinical, laboratory, and neuroimaging data for every new diagnosis. Four neurohospitalists used the tool for 6.5 months on a general neurology ward service at a single tertiary-level teaching hospital. Process measures of tool use included number of diagnoses entered, time spent on each data entry, and concordance of diagnoses compared to the medical record. We also aggregated the data across clinicians to examine the average process scores across common inpatient disorders. The 4 clinicians entered 254 new diagnoses that took approximately 3 minutes per patient. In 50 randomly chosen cases, the neurohospitalists' diagnoses entered into the tool agreed with 92% of diagnoses in the medical record, which was better than the agreement between billing code and medical record diagnoses (74%). The diagnostic process varied across disease categories, showing a spectrum of clinical-dominant (eg, headache), laboratory-dominant (eg, encephalitis), and neuroimaging-dominant (eg, stroke) disorders. This study demonstrated the feasibility of a clinician-driven diagnostic process monitoring system, along with preliminary characterization of the process for common disorders. The tracking of diagnostic process has the potential to promote reflection on clinical practice, deconstruct neurologists' clinical decision-making, and improve health-care safety.

Accuracy of Wearable Cameras to Track Social Interactions in Stroke Survivors

BACKGROUND

Social isolation after a stroke is related to poor outcomes. However, a full study of social networks on stroke outcomes is limited by the current metrics available. Typical measures of social networks rely on self-report, which is vulnerable to response bias and measurement error. We aimed to test the accuracy of an objective measure-wearable cameras-to capture face-to-face social interactions in stroke survivors. If accurate and usable in real-world settings, this technology would allow improved examination of social factors on stroke outcomes.

METHODS

In this prospective study, 10 stroke survivors each wore 2 wearable cameras: Autographer (OMG Life Limited, Oxford, United Kingdom) and Narrative Clip (Narrative, Linköping, Sweden). Each camera automatically took a picture every 20-30 seconds. Patients mingled with healthy controls for 5 minutes of 1-on-1 interactions followed by 5 minutes of no interaction for 2 hours. After the event, 2 blinded judges assessed whether photograph sequences identified interactions or noninteractions. Diagnostic accuracy statistics were calculated.

RESULTS

A total of 8776 photographs were taken and adjudicated. In distinguishing interactions, the Autographer's sensitivity was 1.00 and specificity was .98. The Narrative Clip's sensitivity was .58 and specificity was 1.00. The receiver operating characteristic curves of the 2 devices were statistically different (Z = 8.26, P < .001).

CONCLUSIONS

Wearable cameras can accurately detect social interactions of stroke survivors. Likely because of its large field of view, the Autographer was more sensitive than the Narrative Clip for this purpose.

Abstract WMP51: Patients’ Social Networks Influence Timing of Hospital Arrival After Acute Ischemic Stroke: a Mixed Methods Study

Introduction: Delay in hospital arrival is a major reason for stroke patients’ exclusion from acute therapy. Risk factors for delay include older age, minor symptoms, and living alone. Personal social networks, consisting of the structure and content of relationships around a patient, are important and modifiable factors to health behavior. This study examined the role and mechanisms of patients’ social networks in prehospital delay.

Hypothesis: Social network structure is an independent risk factor of prehospital delay through social influence mechanisms.

Methods: Seventy consecutive patients with mild acute ischemic stroke were interviewed in the hospital. An established social network analysis instrument was used to assess personal network structure and composition. This was followed by semi-structured interviews in 14 patients focused on the arrival process. Fast arrival was defined as before 6 hours, and slow was after 6 hours.

Results: There were 32 slow and 38 fast arrivers. The mean age (63) and NIHSS (3) did not differ between groups. Subcortical stroke location (53% versus 26%) and being unmarried (75% versus 44%) were more common in slow compared to fast arrivers (p<0.05). After controlling for known risk factors, social network structure was significantly associated with arrival time. As shown in figure 1, patients (A) who had networks with high constraint (e.g., strong ties among all network members) were slower to arrive than patients (B) with low constraint (e.g., weak or no ties among network members). Constraint had an adjusted OR=1.08 (95% CI 1.03-1.13, p<0.005) for slow arrival. Mechanisms revealed from qualitative analysis were social capital benefits in fast arrivers, and family members’ perceptual bias to minimize symptoms in slow arrivers.

Conclusions: Patients’ social network structure is an independent risk factor for prehospital delay. These results may be used to develop network-tailored stroke education.

Academic Cross-Pollination: The Role of Disciplinary Affiliation in Research Collaboration

Academic collaboration is critical to knowledge production, especially as teams dominate scientific endeavors. Typical predictors of collaboration include individual characteristics such as academic rank or institution, and network characteristics such as a central position in a publication network. The role of disciplinary affiliation in the initiation of an academic collaboration between two investigators deserves more attention. Here, we examine the influence of disciplinary patterns on collaboration formation with control of known predictors using an inferential network model. The study group included all researchers in the Institute of Clinical and Translational Sciences (ICTS) at Washington University in St. Louis. Longitudinal data were collected on co-authorships in grants and publications before and after ICTS establishment. Exponential-family random graph models were used to build the network models. The results show that disciplinary affiliation independently predicted collaboration in grant and publication networks, particularly in the later years. Overall collaboration increased in the post-ICTS networks, with cross-discipline ties occurring more often than within-discipline ties in grants, but not publications. This research may inform better evaluation models of university-based collaboration, and offer a roadmap to improve cross-disciplinary collaboration with discipline-informed network interventions.

Quality Metrics in Inpatient Neurology

Quality of care in the context of inpatient neurology is the standard of performance by neurologists and the hospital system as measured against ideal models of care. There are growing regulatory pressures to define health care value through concrete quantifiable metrics linked to reimbursement. Theoretical models of quality acknowledge its multimodal character with quantitative and qualitative dimensions. For example, the Donabedian model distils quality as a phenomenon of three interconnected domains, structure-process-outcome, with each domain mutually influential. The actual measurement of quality may be implicit, as in peer review in morbidity and mortality rounds, or explicit, in which criteria are prespecified and systemized before assessment. As a practical contribution, in this article a set of candidate quality indicators for inpatient neurology based on an updated review of treatment guidelines is proposed. These quality indicators may serve as an initial blueprint for explicit quality metrics long overdue for inpatient neurology.

Breaking down silos: mapping growth of cross-disciplinary collaboration in a translational science initiative

The importance of transdisciplinary collaboration is growing, though not much is known about how to measure collaboration patterns. The purpose of this paper is to present multiple ways of mapping and evaluating the growth of cross-disciplinary partnerships over time. Social network analysis was used to examine the impact of a Clinical and Translational Science Award (CTSA) on collaboration patterns. Grant submissions from 2007 through 2010 and publications from 2007 through 2011 of Institute of Clinical and Translational Sciences (ICTS) members were examined. A Cohort Model examining the first-year ICTS members demonstrated an overall increase in collaborations on grants and publications, as well as an increase in cross-discipline collaboration as compared to within-discipline. A Growth Model that included additional members over time demonstrated the same pattern for grant submissions, but a decrease in cross-discipline collaboration as compared to within-discipline collaboration for publications. ICTS members generally became more cross-disciplinary in their collaborations during the CTSA. The exception of publications for the Growth Model may be due to the time lag between funding and publication, as well as pressure for younger scientists to publish in their own fields. Network analysis serves as a valuable tool for evaluating changes in scientific collaboration.