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  Neighborhood Resources Associated With Psychological Trajectories and Neural Reactivity to Reward After Trauma

  Webb, E Kate; Stevens, Jennifer S; Ely, Timothy D; Lebois, Lauren A M; van Rooij, Sanne J H; Bruce, Steven E; House, Stacey L; Beaudoin, Francesca L; An, Xinming; Neylan, Thomas C; et al. (2024-07-31)

  Importance: Research on resilience after trauma has often focused on individual-level factors (eg, ability to cope with adversity) and overlooked influential neighborhood-level factors that may help mitigate the development of posttraumatic stress disorder (PTSD). Objective: To investigate whether an interaction between residential greenspace and self-reported individual resources was associated with a resilient PTSD trajectory (ie, low/no symptoms) and to test if the association between greenspace and PTSD trajectory was mediated by neural reactivity to reward. Design, setting, and participants: As part of a longitudinal cohort study, trauma survivors were recruited from emergency departments across the US. Two weeks after trauma, a subset of participants underwent functional magnetic resonance imaging during a monetary reward task. Study data were analyzed from January to November 2023. Exposures: Residential greenspace within a 100-m buffer of each participant's home address was derived from satellite imagery and quantified using the Normalized Difference Vegetation Index and perceived individual resources measured by the Connor-Davidson Resilience Scale (CD-RISC). Main outcome and measures: PTSD symptom severity measured at 2 weeks, 8 weeks, 3 months, and 6 months after trauma. Neural responses to monetary reward in reward-related regions (ie, amygdala, nucleus accumbens, orbitofrontal cortex) was a secondary outcome. Covariates included both geocoded (eg, area deprivation index) and self-reported characteristics (eg, childhood maltreatment, income). Results: In 2597 trauma survivors (mean [SD] age, 36.5 [13.4] years; 1637 female [63%]; 1304 non-Hispanic Black [50.2%], 289 Hispanic [11.1%], 901 non-Hispanic White [34.7%], 93 non-Hispanic other race [3.6%], and 10 missing/unreported [0.4%]), 6 PTSD trajectories (resilient, nonremitting high, nonremitting moderate, slow recovery, rapid recovery, delayed) were identified through latent-class mixed-effect modeling. Multinominal logistic regressions revealed that for individuals with higher CD-RISC scores, greenspace was associated with a greater likelihood of assignment in a resilient trajectory compared with nonremitting high (Wald z test = -3.92; P < .001), nonremitting moderate (Wald z test = -2.24; P = .03), or slow recovery (Wald z test = -2.27; P = .02) classes. Greenspace was also associated with greater neural reactivity to reward in the amygdala (n = 288; t277 = 2.83; adjusted P value = 0.02); however, reward reactivity did not differ by PTSD trajectory. Conclusions and relevance: In this cohort study, greenspace and self-reported individual resources were significantly associated with PTSD trajectories. These findings suggest that factors at multiple ecological levels may contribute to the likelihood of resiliency to PTSD after trauma.
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  Relationship between acute SARS-CoV-2 viral clearance with Long COVID Symptoms: a cohort study [preprint]

  Herbert, Carly; Antar, Annukka A R; Broach, John; Wright, Colton; Stamegna, Pamela; Luzuriaga, Katherine; Hafer, Nathaniel; McManus, David D; Manabe, Yukari C; Soni, Apurv (2024-07-05)

  Introduction: The relationship between SARS-CoV-2 viral dynamics during acute infection and the development of long COVID is largely unknown. Methods: A total of 7361 asymptomatic community-dwelling people enrolled in the Test Us at Home parent study between October 2021 and February 2022. Participants self-collected anterior nasal swabs for SARS-CoV-2 RT-PCR testing every 24-48 hours for 10-14 days, regardless of symptom or infection status. Participants who had no history of COVID-19 at enrollment and who were subsequently found to have ≥1 positive SARS-CoV-2 RT-PCR test during the parent study were recontacted in August 2023 and asked whether they had experienced long COVID, defined as the development of new symptoms lasting 3 months or longer following SARS-CoV-2 infection. Participant's cycle threshold values were converted into viral loads, and slopes of viral clearance were modeled using post-nadir viral loads. Using a log binomial model with the modeled slopes as the exposure, we calculated the relative risk of subsequently developing long COVID with 1-2 symptoms, 3-4 symptoms, or 5+ symptoms, adjusting for age, number of symptoms, and SARS-CoV-2 variant. Adjusted relative risk (aRR) of individual long COVID symptoms based on viral clearance was also calculated. Results: 172 participants were eligible for analyses, and 59 (34.3%) reported experiencing long COVID. The risk of long COVID with 3-4 symptoms and 5+ symptoms increased by 2.44 times (aRR: 2.44; 95% CI: 0.88-6.82) and 4.97 times (aRR: 4.97; 95% CI: 1.90-13.0) per viral load slope-unit increase, respectively. Participants who developed long COVID had significantly longer times from peak viral load to viral clearance during acute disease than those who never developed long COVID (8.65 [95% CI: 8.28-9.01] vs. 10.0 [95% CI: 9.25-10.8]). The slope of viral clearance was significantly positively associated with long COVID symptoms of fatigue (aRR: 2.86; 95% CI: 1.22-6.69), brain fog (aRR: 4.94; 95% CI: 2.21-11.0), shortness of breath (aRR: 5.05; 95% CI: 1.24-20.6), and gastrointestinal symptoms (aRR: 5.46; 95% CI: 1.54-19.3). Discussion: We observed that longer time from peak viral load to viral RNA clearance during acute COVID-19 was associated with an increased risk of developing long COVID. Further, slower clearance rates were associated with greater number of symptoms of long COVID. These findings suggest that early viral-host dynamics are mechanistically important in the subsequent development of long COVID.
• Racial Disparities and Trends in Anticoagulant Use among Ambulatory Care Patients with Atrial Fibrillation and Atrial Flutter in the United States from 2007-2019 [preprint]

  Kan, Vincent; Lapane, Kate L; McManus, David D; Baek, Jonggyu; Darling, Chad E; Alcusky, Matthew J (2024-06-15)

  Introduction Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, significantly increasing the risk of stroke. The introduction of direct oral anticoagulants (DOACs) since 2010 has transformed anticoagulation therapy, offering an alternative to warfarin with improved safety profiles. Despite the increased adoption of DOACs, disparities in their use among different racial and ethnic groups in the United States remain understudied. Methods This study utilized a repeated cross-sectional design, analyzing data from the National Ambulatory Medical Care Survey (NAMCS) from 2007 to 2019. The study population included adults diagnosed with AF or atrial flutter (AFL). We analyzed the temporal trends of DOAC and warfarin use from 2007 to 2019. We examined the prevalence of DOAC versus warfarin use and assessed associations between race/ethnicity, patient characteristics, and DOAC utilization from 2011 to 2019. Multivariable modified Poisson regression models were used to calculate adjusted prevalence ratios (aPR) for the associations. Results From 2011 to 2019, NAMCS recorded 3,224 visits involving AF or AFL, representing a weighted estimate of 103.6 million visits. DOAC use increased significantly, with apixaban becoming the predominant anticoagulant by 2016. Non-Hispanic Black patients were less likely to use DOACs compared to non-Hispanic White patients over time (aPR 0.75; 95% CI, 0.63-0.90). Patients with Medicaid insurance were also less likely to use DOACs (aPR 0.14; 95% CI: 0.04-0.46). Conclusion Despite the shift from warfarin to DOACs for AF and AFL treatment, significant racial and socioeconomic disparities persist. Non-Hispanic Black patients and those with Medicaid insurance are less likely to use DOACs. These findings highlight the need for targeted strategies to ensure equitable access to advanced anticoagulant therapies.
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  Development of a predictive algorithm for patient survival after traumatic injury using a five analyte blood panel [preprint]

  Fathi, Parinaz; Karkanitsa, Maria; Rupert, Adam; Lin, Aaron; Darrah, Jenna; Thomas, F Dennis; Lai, Jeffrey T; Babu, Kavita M; Neavyn, Mark; Kozar, Rosemary; et al. (2024-06-11)

  Severe trauma can induce systemic inflammation but also immunosuppression, which makes understanding the immune response of trauma patients critical for therapeutic development and treatment approaches. By evaluating the levels of 59 proteins in the plasma of 50 healthy volunteers and 1000 trauma patients across five trauma centers in the United States, we identified 6 novel changes in immune proteins after traumatic injury and further new variations by sex, age, trauma type, comorbidities, and developed a new equation for prediction of patient survival. Blood was collected at the time of arrival at Level 1 trauma centers and patients were stratified based on trauma level, tissues injured, and injury types. Trauma patients had significantly upregulated proteins associated with immune activation (IL-23, MIP-5), immunosuppression (IL-10) and pleiotropic cytokines (IL-29, IL-6). A high ratio of IL-29 to IL-10 was identified as a new predictor of survival in less severe patients with ROC area of 0.933. Combining machine learning with statistical modeling we developed an equation ("VIPER") that could predict survival with ROC 0.966 in less severe patients and 0.8873 for all patients from a five analyte panel (IL-6, VEGF-A, IL-21, IL-29, and IL-10). Furthermore, we also identified three increased proteins (MIF, TRAIL, IL-29) and three decreased proteins (IL-7, TPO, IL-8) that were the most important in distinguishing a trauma blood profile. Biologic sex altered phenotype with IL-8 and MIF being lower in healthy women, but higher in female trauma patients when compared to male counterparts. This work identifies new responses to injury that may influence systemic immune dysfunction, serving as targets for therapeutics and immediate clinical benefit in identifying at-risk patients.
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  Performance of and Severe Acute Respiratory Syndrome Coronavirus 2 Diagnostics Based on Symptom Onset and Close Contact Exposure: An Analysis From the Test Us at Home Prospective Cohort Study

  Herbert, Carly; Wang, Biqi; Lin, Honghuang; Yan, Yi; Hafer, Nathaniel; Pretz, Caitlin; Stamegna, Pamela; Wright, Colton; Suvarna, Thejas; Harman, Emma; et al. (2024-05-31)

  Background: Understanding changes in diagnostic performance after symptom onset and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure within different populations is crucial to guide the use of diagnostics for SARS-CoV-2. Methods: The Test Us at Home study was a longitudinal cohort study that enrolled individuals across the United States between October 2021 and February 2022. Participants performed paired antigen-detection rapid diagnostic tests (Ag-RDTs) and reverse-transcriptase polymerase chain reaction (RT-PCR) tests at home every 48 hours for 15 days and self-reported symptoms and known coronavirus disease 2019 exposures immediately before testing. The percent positivity for Ag-RDTs and RT-PCR tests was calculated each day after symptom onset and exposure and stratified by vaccination status, variant, age category, and sex. Results: The highest percent positivity occurred 2 days after symptom onset (RT-PCR, 91.2%; Ag-RDT, 71.1%) and 6 days after exposure (RT-PCR, 91.8%; Ag-RDT, 86.2%). RT-PCR and Ag-RDT performance did not differ by vaccination status, variant, age category, or sex. The percent positivity for Ag-RDTs was lower among exposed, asymptomatic than among symptomatic individuals (37.5% (95% confidence interval [CI], 13.7%-69.4%) vs 90.3% (75.1%-96.7%). Cumulatively, Ag-RDTs detected 84.9% (95% CI, 78.2%-89.8%) of infections within 4 days of symptom onset. For exposed participants, Ag-RDTs detected 94.0% (95% CI, 86.7%-97.4%) of RT-PCR-confirmed infections within 6 days of exposure. Conclusions: The percent positivity for Ag-RDTs and RT-PCR tests was highest 2 days after symptom onset and 6 days after exposure, and performance increased with serial testing. The percent positivity of Ag-RDTs was lowest among asymptomatic individuals but did not differ by sex, variant, vaccination status, or age category.
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  Best of Both Worlds: Bridging One Model for All and Group-Specific Model Approaches using Ensemble-based Subpopulation Modeling

  Mugambi, Purity; Carreiro, Stephanie (2024-05-31)

  Subpopulation models have become of increasing interest in prediction of clinical outcomes because they promise to perform better for underrepresented patient subgroups. However, the personalization benefits gained from these models tradeoff their statistical power, and can be impractical when the subpopulation's sample size is small. We hypothesize that a hierarchical model in which population information is integrated into subpopulation models would preserve the personalization benefits and offset the loss of power. In this work, we integrate ideas from ensemble modeling, personalization, and hierarchical modeling and build ensemble-based subpopulation models in which specialization relies on whole group samples. This approach significantly improves the precision of the positive class, especially for the underrepresented subgroups, with minimal cost to the recall. It consistently outperforms one model for all and one model for each subgroup approaches, especially in the presence of a high class-imbalance, for subgroups with at least 380 training samples.
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  Rationale and Design of Healthy at Home for COPD: an Integrated Remote Patient Monitoring and Virtual Pulmonary Rehabilitation Pilot Study [preprint]

  O'Connor, Laurel; Behar, Stephanie; Tarrant, Seanan; Stamegna, Pamela; Pretz, Caitlin; Wang, Biqi; Savage, Brandon; Scornavacca, Thomas; Shirshac, Jeanne; Wilkie, Tracey; et al. (2024-04-29)

  Chronic Obstructive Pulmonary Disease (COPD) is a common, costly, and morbid condition. Pulmonary rehabilitation, close monitoring, and early intervention during acute exacerbations of symptoms represent a comprehensive approach to improve outcomes, but the optimal means of delivering these services is uncertain. Logistical, financial, and social barriers to providing healthcare through face-to-face encounters, paired with recent developments in technology, have stimulated interest in exploring alternative models of care. The Healthy at Home study seeks to determine the feasibility of a multimodal, digitally enhanced intervention provided to participants with COPD longitudinally over six months. This paper details the recruitment, methods, and analysis plan for the study, which is recruiting 100 participants in its pilot phase. Participants were provided with several integrated services including a smartwatch to track physiological data, a study app to track symptoms and study instruments, access to a mobile integrated health program for acute clinical needs, and a virtual comprehensive pulmonary support service. Participants shared physiologic, demographic, and symptom reports, electronic health records, and claims data with the study team, facilitating a better understanding of their symptoms and potential care needs longitudinally. The Healthy at Home study seeks to develop a comprehensive digital phenotype of COPD by tracking and responding to multiple indices of disease behavior and facilitating early and nuanced responses to changes in participants' health status. This study is registered at Clinicaltrials.gov (NCT06000696).
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  Face-off Droop: A Case Report of Pediatric Stroke

  Robertson, Duncan; Peirce, Hayden F; Nicpon, Marek D; Otterson, Eric M; O'Connor, Laurel; Rissmiller, Julia G; Binder, Zachary W (2024-04-24)

  Introduction: Cerebrovascular accidents rarely occur in children; the incidence of ischemic stroke in patients <16 years of age is between 0.6-7.9/100,000. However, they are the fourth most common cause of acute neurological deficits in the pediatric population, and possible cases should be evaluated with a high index of suspicion to ensure timely intervention. Case report: We describe a previously healthy 17-year-old male who presented to the pediatric emergency department with a left facial droop and hemiparesis consistent with a stroke. The patient's age and lack of comorbidities made this an extremely uncommon presentation. Our patient's neurologic symptoms were believed to have been caused by a recent traumatic clavicular injury sustained two weeks prior, which subsequently led to vascular insult. Conclusion: Cerebrovascular accidents are an important cause of morbidity and mortality in pediatric patients. Cerebrovascular accidents in children are most often secondary to congenital causes; however, care should be taken to assess for acquired causes, such as trauma to major blood vessels. While rarely implicated in traumatic injuries, arterial structures posterior to the medial clavicle can result in severe complications.
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  Syndromic surveillance of population-level COVID-19 burden with cough monitoring in a hospital emergency waiting room

  Al Hossain, Forsad; Tonmoy, M Tanjid Hasan; Nuvvula, Sri; Chapman, Brittany P; Gupta, Rajesh K; Lover, Andrew A; Dinglasan, Rhoel R; Carreiro, Stephanie; Rahman, Tauhidur (2024-03-28)

  Syndromic surveillance is an effective tool for enabling the timely detection of infectious disease outbreaks and facilitating the implementation of effective mitigation strategies by public health authorities. While various information sources are currently utilized to collect syndromic signal data for analysis, the aggregated measurement of cough, an important symptom for many illnesses, is not widely employed as a syndromic signal. With recent advancements in ubiquitous sensing technologies, it becomes feasible to continuously measure population-level cough incidence in a contactless, unobtrusive, and automated manner. In this work, we demonstrate the utility of monitoring aggregated cough count as a syndromic indicator to estimate COVID-19 cases. In our study, we deployed a sensor-based platform (Syndromic Logger) in the emergency room of a large hospital. The platform captured syndromic signals from audio, thermal imaging, and radar, while the ground truth data were collected from the hospital's electronic health record. Our analysis revealed a significant correlation between the aggregated cough count and positive COVID-19 cases in the hospital (Pearson correlation of 0.40, p-value < 0.001). Notably, this correlation was higher than that observed with the number of individuals presenting with fever (ρ = 0.22, p = 0.04), a widely used syndromic signal and screening tool for such diseases. Furthermore, we demonstrate how the data obtained from our Syndromic Logger platform could be leveraged to estimate various COVID-19-related statistics using multiple modeling approaches. Aggregated cough counts and other data, such as people density collected from our platform, can be utilized to predict COVID-19 patient visits related metrics in a hospital waiting room, and SHAP and Gini feature importance-based metrics showed cough count as the important feature for these prediction models. Furthermore, we have shown that predictions based on cough counting outperform models based on fever detection (e.g., temperatures over 39°C), which require more intrusive engagement with the population. Our findings highlight that incorporating cough-counting based signals into syndromic surveillance systems can significantly enhance overall resilience against future public health challenges, such as emerging disease outbreaks or pandemics.
• Factors Impacting the Implementation of Mobile Integrated Health Programs for the Acute Care of Older Adults

  O'Connor, Laurel; Behar, Stephanie; Refuerzo, Jade; Mele, Xhenifer; Sundling, Elsa; Johnson, Sharon A; Faro, Jamie M; Lindenauer, Peter K; Mattocks, Kristin M (2024-03-28)

  Objective: Emergency services utilization is increasing in older adult populations. Many such encounters may be preventable with better access to acute care in the community. Mobile integrated health (MIH) programs leverage mobile resources to deliver care and services to patients in the out-of-hospital environment and have the potential to improve clinical outcomes and decrease health care costs; however, they have not been widely implemented. We assessed barriers, potential facilitators, and other factors critical to the implementation of MIH programs with key vested partners. Methods: Professional and community-member partners were purposefully recruited to participate in recorded structured interviews. The study team used the Practical Robust Implementation and Sustainability Model (PRISM) framework to develop an interview guide and codebook. Coders employed a combination of deductive and inductive coding strategies to identify common themes across partner groups. Results: The study team interviewed 22 participants (mean age 56, 68% female). A cohort of professional subject matter experts included physicians, paramedics, public health personnel, and hospital administrators. A cohort of lay community partners included patients and caregivers. Coders identified three prominent themes that impact MIH implementation. First, MIH is disruptive to existing clinical workflows. Second, using MIH to improve patients' experience during acute care encounters is key to intervention adoption. Finally, legislative action is needed to augment central financial and regulatory policies to ensure the adoption of MIH programs. Conclusions: Common themes impacting the implementation of MIH programs were identified across vested partner groups. Multilevel strategies are needed to address patient adoption, clinical partners' workflow, and legislative policies to ensure the success of MIH programs.
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  Closing the Digital Divide in Interventions for Substance Use Disorder

  Hampton, Jazmin; Mugambi, Purity; Caggiano, Emily; Eugene, Reynalde; Valente, Alycia; Taylor, Melissa; Carreiro, Stephanie (2024-03-26)

  Digital health interventions are exploding in today's medical practice and have tremendous potential to support the treatment of substance use disorders (SUD). Developers and healthcare providers alike must be cognizant of the potential for digital interventions to exacerbate existing inequities in SUD treatment, particularly as they relate to Social Determinants of Health (SDoH). To explore this evolving area of study, this manuscript will review the existing concepts of the digital divide and digital inequities, and the role SDoH play as drivers of digital inequities. We will then explore how the data used and modeling strategies can create bias in digital health tools for SUD. Finally, we will discuss potential solutions and future directions to bridge these gaps including smartphone ownership, Wi-Fi access, digital literacy, and mitigation of historical, algorithmic, and measurement bias. Thoughtful design of digital interventions is quintessential to reduce the risk of bias, decrease the digital divide, and create equitable health outcomes for individuals with SUD.
• Pharmacokinetics-Informed Neural Network for Predicting Opioid Administration Moments with Wearable Sensors

  Gullapalli, Bhanu Teja; Carreiro, Stephanie; Chapman, Brittany P; Garland, Eric L; Rahman, Tauhidur (2024-03-24)

  Long-term and high-dose prescription opioid use places individuals at risk for opioid misuse, opioid use disorder (OUD), and overdose. Existing methods for monitoring opioid use and detecting misuse rely on self-reports, which are prone to reporting bias, and toxicology testing, which may be infeasible in outpatient settings. Although wearable technologies for monitoring day-to-day health metrics have gained significant traction in recent years due to their ease of use, flexibility, and advancements in sensor technology, their application within the opioid use space remains underexplored. In the current work, we demonstrate that oral opioid administrations can be detected using physiological signals collected from a wrist sensor. More importantly, we show that models informed by opioid pharmacokinetics increase reliability in predicting the timing of opioid administrations. Forty-two individuals who were prescribed opioids as a part of their medical treatment in-hospital and after discharge were enrolled. Participants wore a wrist sensor throughout the study, while opioid administrations were tracked using electronic medical records and self-reports. We collected 1,983 hours of sensor data containing 187 opioid administrations from the inpatient setting and 927 hours of sensor data containing 40 opioid administrations from the outpatient setting. We demonstrate that a self-supervised pre-trained model, capable of learning the canonical time series of plasma concentration of the drug derived from opioid pharmacokinetics, can reliably detect opioid administration in both settings. Our work suggests the potential of pharmacokinetic-informed, data-driven models to objectively detect opioid use in daily life.
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  A machine learning approach for diagnostic and prognostic predictions, key risk factors and interactions

  Nasir, Murtaza; Summerfield, Nichalin S.; Carreiro, Stephanie; Berlowitz, Dan; Oztekin, Asil (2024-03-18)

  Machine learning (ML) has the potential to revolutionize healthcare, allowing healthcare providers to improve patient-care planning, resource planning and utilization. Furthermore, identifying key-risk-factors and interaction-effects can help service-providers and decision-makers to institute better policies and procedures. This study used COVID-19 electronic health record (EHR) data to predict five crucial outcomes: positive-test, ventilation, death, hospitalization days, and ICU days. Our models achieved high accuracy and precision, with AUC values of 91.6%, 99.1%, and 97.5% for the first three outcomes, and MAE of 0.752 and 0.257 days for the last two outcomes. We also identified interaction effects, such as high bicarbonate in arterial blood being associated with longer hospitalization in middle-aged patients. Our models are embedded in a prototype of an online decision support tool that can be used by healthcare providers to make more informed decisions.
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  Post-traumatic stress and future substance use outcomes: leveraging antecedent factors to stratify risk

  Garrison-Desany, Henri M; Meyers, Jacquelyn L; Linnstaedt, Sarah D; House, Stacey L; Beaudoin, Francesca L; An, Xinming; Zeng, Donglin; Neylan, Thomas C; Clifford, Gari D; Jovanovic, Tanja; et al. (2024-03-08)

  Background: Post-traumatic stress disorder (PTSD) and substance use (tobacco, alcohol, and cannabis) are highly comorbid. Many factors affect this relationship, including sociodemographic and psychosocial characteristics, other prior traumas, and physical health. However, few prior studies have investigated this prospectively, examining new substance use and the extent to which a wide range of factors may modify the relationship to PTSD. Methods: The Advancing Understanding of RecOvery afteR traumA (AURORA) study is a prospective cohort of adults presenting at emergency departments (N = 2,943). Participants self-reported PTSD symptoms and the frequency and quantity of tobacco, alcohol, and cannabis use at six total timepoints. We assessed the associations of PTSD and future substance use, lagged by one timepoint, using the Poisson generalized estimating equations. We also stratified by incident and prevalent substance use and generated causal forests to identify the most important effect modifiers of this relationship out of 128 potential variables. Results: At baseline, 37.3% (N = 1,099) of participants reported likely PTSD. PTSD was associated with tobacco frequency (incidence rate ratio (IRR): 1.003, 95% CI: 1.00, 1.01, p = 0.02) and quantity (IRR: 1.01, 95% CI: 1.001, 1.01, p = 0.01), and alcohol frequency (IRR: 1.002, 95% CI: 1.00, 1.004, p = 0.03) and quantity (IRR: 1.003, 95% CI: 1.001, 1.01, p = 0.001), but not with cannabis use. There were slight differences in incident compared to prevalent tobacco frequency and quantity of use; prevalent tobacco frequency and quantity were associated with PTSD symptoms, while incident tobacco frequency and quantity were not. Using causal forests, lifetime worst use of cigarettes, overall self-rated physical health, and prior childhood trauma were major moderators of the relationship between PTSD symptoms and the three substances investigated. Conclusion: PTSD symptoms were highly associated with tobacco and alcohol use, while the association with prospective cannabis use is not clear. Findings suggest that understanding the different risk stratification that occurs can aid in tailoring interventions to populations at greatest risk to best mitigate the comorbidity between PTSD symptoms and future substance use outcomes. We demonstrate that this is particularly salient for tobacco use and, to some extent, alcohol use, while cannabis is less likely to be impacted by PTSD symptoms across the strata.
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  Brain dynamics reflecting an intra-network brain state is associated with increased posttraumatic stress symptoms in the early aftermath of trauma [preprint]

  Sendi, Mohammad; Fu, Zening; Harnett, Nathaniel; van Rooij, Sanne; Vergara, Victor; Pizzagalli, Diego; Daskalakis, Nikolaos; House, Stacey; Beaudoin, Francesca; An, Xinming; et al. (2024-03-08)

  This study examines the association between brain dynamic functional network connectivity (dFNC) and current/future posttraumatic stress (PTS) symptom severity, and the impact of sex on this relationship. By analyzing 275 participants' dFNC data obtained ~2 weeks after trauma exposure, we noted that brain dynamics of an inter-network brain state link negatively with current (r=-0.179, pcorrected= 0.021) and future (r=-0.166, pcorrected= 0.029) PTS symptom severity. Also, dynamics of an intra-network brain state correlated with future symptom intensity (r = 0.192, pcorrected = 0.021). We additionally observed that the association between the network dynamics of the inter-network brain state with symptom severity is more pronounced in females (r=-0.244, pcorrected = 0.014). Our findings highlight a potential link between brain network dynamics in the aftermath of trauma with current and future PTSD outcomes, with a stronger protective effect of inter-network brain states against symptom severity in females, underscoring the importance of sex differences.
• Smartphone and Wearable Device-Based Digital Phenotyping to Understand Substance use and its Syndemics

  Lee, Jasper S; Browning, Emma; Hokayem, Joanne; Albrechta, Hannah; Goodman, Georgia R; Venkatasubramanian, Krishna; Dumas, Arlen; Carreiro, Stephanie; O'Cleirigh, Conall; Chai, Peter R (2024-03-04)

  Digital phenotyping is a process that allows researchers to leverage smartphone and wearable data to explore how technology use relates to behavioral health outcomes. In this Research Concepts article, we provide background on prior research that has employed digital phenotyping; the fundamentals of how digital phenotyping works, using examples from participant data; the application of digital phenotyping in the context of substance use and its syndemics; and the ethical, legal and social implications of digital phenotyping. We discuss applications for digital phenotyping in medical toxicology, as well as potential uses for digital phenotyping in future research. We also highlight the importance of obtaining ground truth annotation in order to identify and establish digital phenotypes of key behaviors of interest. Finally, there are many potential roles for medical toxicologists to leverage digital phenotyping both in research and in the future as a clinical tool to better understand the contextual features associated with drug poisoning and overdose. This article demonstrates how medical toxicologists and researchers can progress through phases of a research trajectory using digital phenotyping to better understand behavior and its association with smartphone usage.
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  Evaluating the Prevalence of Four Recommended Practices for Suicide Prevention Following Hospital Discharge

  Chitavi, Salome O; Patrianakos, Jamie; Williams, Scott C; Schmaltz, Stephen P; Ahmedani, Brian K; Roaten, Kimberly; Boudreaux, Edwin D; Brown, Gregory K (2024-02-23)

  Background: The Joint Commission's National Patient Safety Goal (NPSG) for suicide prevention (NPSG.15.01.01) requires that accredited hospitals maintain policies/procedures for follow-up care at discharge for patients identified as at risk for suicide. The proportion of hospitals meeting these requirements through use of recommended discharge practices is unknown. Methods: This cross-sectional observational study explored the prevalence of suicide prevention activities among Joint Commission-accredited hospitals. A questionnaire was sent to 1,148 accredited hospitals. The authors calculated the percentage of hospitals reporting implementation of four recommended discharge practices for suicide prevention. Results: Of 1,148 hospitals, 346 (30.1%) responded. The majority (n = 212 [61.3%]) of hospitals had implemented formal safety planning, but few of those (n = 41 [19.3%]) included all key components of safety planning. Approximately a third of hospitals provided a warm handoff to outpatient care (n = 128 [37.0%)] or made follow-up contact with patients (n = 105 [30.3%]), and approximately a quarter (n = 97 [28.0%]) developed a plan for lethal means safety. Very few (n = 14 [4.0%]) hospitals met full criteria for implementing recommended suicide prevention activities at time of discharge. Conclusion: The study revealed a significant gap in implementation of recommended practices related to prevention of suicide postdischarge. Additional research is needed to identify factors contributing to this implementation gap.
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  Acceptance of digital phenotyping linked to a digital pill system to measure PrEP adherence among men who have sex with men with substance use

  Albrechta, Hannah; Goodman, Georgia R; Oginni, Elizabeth; Mohamed, Yassir; Venkatasubramanian, Krishna; Dumas, Arlen; Carreiro, Stephanie; Lee, Jasper S; Glynn, Tiffany R; O'Cleirigh, Conall; et al. (2024-02-22)

  Once-daily oral HIV pre-exposure prophylaxis (PrEP) is an effective strategy to prevent HIV, but is highly dependent on adherence. Men who have sex with men (MSM) who use substances face unique challenges maintaining PrEP adherence. Digital pill systems (DPS) allow for real-time adherence measurement through ingestible sensors. Integration of DPS technology with other digital health tools, such as digital phenotyping, may improve understanding of nonadherence triggers and development of personalized adherence interventions based on ingestion behavior. This study explored the willingness of MSM with substance use to share digital phenotypic data and interact with ancillary systems in the context of DPS-measured PrEP adherence. Adult MSM on PrEP with substance use were recruited through a social networking app. Participants were introduced to DPS technology and completed an assessment to measure willingness to participate in DPS-based PrEP adherence research, contribute digital phenotyping data, and interact with ancillary systems in the context of DPS-based research. Medical mistrust, daily worry about PrEP adherence, and substance use were also assessed. Participants who identified as cisgender male and were willing to participate in DPS-based research (N = 131) were included in this subsample analysis. Most were White (76.3%) and non-Hispanic (77.9%). Participants who reported daily PrEP adherence worry had 3.7 times greater odds (95% CI: 1.03, 13.4) of willingness to share biometric data via a wearable device paired to the DPS. Participants with daily PrEP adherence worry were more likely to be willing to share smartphone data (p = 0.006) and receive text messages surrounding their daily activities (p = 0.003), compared to those with less worry. MSM with substance use disorder, who worried about PrEP adherence, were willing to use DPS technology and share data required for digital phenotyping in the context of PrEP adherence measurement. Efforts to address medical mistrust can increase advantages of this technology for HIV prevention.
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  Contactless Monitoring System Versus Gold Standard for Respiratory Rate Monitoring in Emergency Department Patients: Pilot Comparison Study

  Goldfine, Charlotte E; Oshim, Md Farhan Tasnim; Chapman, Brittany P; Ganesan, Deepak; Rahman, Tauhidur; Carreiro, Stephanie (2024-02-16)

  Background: Respiratory rate is a crucial indicator of disease severity yet is the most neglected vital sign. Subtle changes in respiratory rate may be the first sign of clinical deterioration in a variety of disease states. Current methods of respiratory rate monitoring are labor-intensive and sensitive to motion artifacts, which often leads to inaccurate readings or underreporting; therefore, new methods of respiratory monitoring are needed. The PulsON 440 (P440; TSDR Ultra Wideband Radios and Radars) radar module is a contactless sensor that uses an ultrawideband impulse radar to detect respiratory rate. It has previously demonstrated accuracy in a laboratory setting and may be a useful alternative for contactless respiratory monitoring in clinical settings; however, it has not yet been validated in a clinical setting. Objective: The goal of this study was to (1) compare the P440 radar module to gold standard manual respiratory rate monitoring and standard of care telemetry respiratory monitoring through transthoracic impedance plethysmography and (2) compare the P440 radar to gold standard measurements of respiratory rate in subgroups based on sex and disease state. Methods: This was a pilot study of adults aged 18 years or older being monitored in the emergency department. Participants were monitored with the P440 radar module for 2 hours and had gold standard (manual respiratory counting) and standard of care (telemetry) respiratory rates recorded at 15-minute intervals during that time. Respiratory rates between the P440, gold standard, and standard telemetry were compared using Bland-Altman plots and intraclass correlation coefficients. Results: A total of 14 participants were enrolled in the study. The P440 and gold standard Bland-Altman analysis showed a bias of -0.76 (-11.16 to 9.65) and an intraclass correlation coefficient of 0.38 (95% CI 0.06-0.60). The P440 and gold standard had the best agreement at normal physiologic respiratory rates. There was no change in agreement between the P440 and the gold standard when grouped by admitting diagnosis or sex. Conclusions: Although the P440 did not have statistically significant agreement with gold standard respiratory rate monitoring, it did show a trend of increased agreement in the normal physiologic range, overestimating at low respiratory rates, and underestimating at high respiratory rates. This trend is important for adjusting future models to be able to accurately detect respiratory rates. Once validated, the contactless respiratory monitor provides a unique solution for monitoring patients in a variety of settings.
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  Opioid Overdose Recognition: A Survey of Perceived Preparedness and Desire for Curricular Integration Among Current US Medical Students

  Walsh, Lindsay; Chapman, Brittany P; Carey, Jennifer; Loycano, Kayla; Carreiro, Stephanie (2024-01-10)

  Objectives: Opioid overdose deaths remain a major health issue in the United States (US). As future physicians, medical students must receive comprehensive training to recognize and manage opioid overdoses. This study aimed to highlight training gaps at the medical student level and understand students' attitudes toward patients with opioid use disorder (OUD). Methods: We assessed baseline knowledge of and attitudes toward the management of opioid overdoses and naloxone administration among medical students in the US. Two validated survey tools (Opioid Overdose Knowledge Scale and Opioid Overdose Attitude Scale) were administered to medical students training at accredited institutions along with supplemental questions measuring knowledge and attitudes towards opioid overdose management, naloxone administration, and prior training. Results: The final sample had N = 73 participants from US medical schools with a mean age of 25.3 (range of 22-37): 72.6% of respondents were female. Although most respondents reported personal/professional experience with OUD before medical school, they expressed interest in additional training. Knowledge surrounding opioid overdoses increased insignificantly over the 4 years of medical school. However, there was a significant increase in both perceived competence in overdose recognition/management and in concerns about intervening from the first to fourth year of medical school. Female respondents had significantly lower perceived competence and readiness to intervene sub-scores than male counterparts; however, there was no significant difference in overall attitude and knowledge scores when stratified by sex. Incorporating opioid overdose prevention training (OOPT) into early medical education was favorable among respondents, who expressed an overwhelming interest in learning and supporting patients with OUD. Conclusions: Given the ongoing opioid crisis, medical students are ideally placed to identify and manage opioid overdoses. Medical students are ready to receive this training, thus strengthening the argument for OOPT integration into early medical student curricula.

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