Effects of Telehealth on Dropout and Retention in Care among Treatment-Seeking Individuals with Substance Use Disorder: A Retrospective Cohort Study

Background: During the COVID-19 pandemic, telehealth became a widely used method of delivering treatment for substance use disorders (SUD), but its impact upon treatment engagement and dropout remains unknown. Methods: We conducted a retrospective analysis of adult SUD patients (n = 544) between October 2020 and June 2022 among a cohort of treatment-seeking patients at a nonprofit community behavioral health center in Southwestern Ohio. We estimated the likelihood of treatment dropout using survival curves and Cox proportional hazard models, comparing patients who used telehealth with video, telephone, or solely in-person services within the first 14 days of diagnosis. We also compared the likelihood of early treatment engagement. Results: Patients who received services through telehealth with video in the initial 14 days of diagnosis had a lower hazard of dropout, compared to patients receiving solely in-person services (0.64, 95% CI [0.46, 0.90]), while there was no difference in hazards of dropout between patients who received telephone and in-person services. Early use of telehealth, both via video (5.40, 95% CI [1.92, 15.20]) and telephone (2.12, 95% CI [1.05, 4.28]), was associated with greater odds of treatment engagement compared to in-person care. Conclusion: This study adds to the existing literature related to telehealth utilization and engagement in care and supports the inclusion of telehealth in SUD treatment programs for treatment-seeking individuals

Motor Cortical Network Plasticity in Patients With Recurrent Brain Tumors

Objective: The adult brain’s potential for plastic reorganization is an important mechanism for the preservation and restoration of function in patients with primary glial neoplasm. Patients with recurrent brain tumors requiring multiple interventions over time present an opportunity to examine brain reorganization. Magnetoencephalography (MEG) is a noninvasive imaging modality that can be used for motor cortical network mapping which, when performed at regular intervals, offers insight into this process of reorganization. Utilizing MEG-based motor mapping, we sought to characterize the reorganization of motor cortical networks over time in a cohort of 78 patients with recurrent glioma. Methods: MEG-based motor cortical maps were obtained by measuring event-related desynchronization (ERD) in ß-band frequency during unilateral index finger flexion. Each patient presented at our Department at least on two occasions for tumor resection due to tumor recurrence, and MEG-based motor mapping was performed as part of preoperative assessment before each surgical resection. Whole-brain activation patterns from first to second MEG scan (obtained before first and second surgery) were compared. Additionally, we calculated distances of activation peaks, which represent the location of the primary motor cortex (MC), to determine the magnitude of movement in motor eloquent areas between the first and second MEG scan. We also explored which demographic, anatomic, and pathological factors influence these shifts. Results: The whole-brain activation motor maps showed a subtle movement of the primary MC from first to second timepoint, as was confirmed by the determination of motor activation peaks. The shift of ipsilesional MC was directly correlated with a frontal-parietal tumor location (p < 0.001), presence of motor deficits (p = 0.021), and with a longer period between MEG scans (p = 0.048). Also, a disengagement of wide areas in the contralesional (ipsilateral to finger movement) hemisphere at the second time point was observed. Conclusions: MEG imaging is a sensitive method for depicting the plasticity of the motor cortical network. Although the location of the primary MC undergoes only subtle changes, appreciable shifts can occur in the setting of a stronger and longer impairment of the tumor on the MC. The ipsilateral hemisphere may serve as a reservoir for functional recovery

Instrumentation for Examining Microbial Response to Changes In Environmental Pressures

The Automated Adaptive Directed Evolution Chamber (AADEC) is a device that allows operators to generate a micro-scale analog of real world systems that can be used to model the local-scale effects of climate change on microbial ecosystems. The AADEC uses an artificial environment to expose cultures of micro-organisms to environmental pressures, such as UV-C radiation, chemical toxins, and temperature. The AADEC autonomously exposes micro-organisms to selection pressures. This improves upon standard manual laboratory techniques: the process can take place over a longer period of time, involve more stressors, implement real-time adjustments based on the state of the population, and minimize the risk of contamination. We currently use UV-C radiation as the main selection pressure, UV-C is well studied both for its cell and DNA damaging effects as a type of selection pressure and for its related effectiveness as a mutagen; having these functions united makes it a good choice for a proof of concept. The AADEC roadmap includes expansion to different selection pressures, including heavy metal toxicity, temperature, and other forms of radiation.The AADEC uses closed-loop control to feedback the current state of the culture to the AADEC controller that modifies selection pressure intensity during experimentation, in this case culture density and growth rate. Culture density and growth rate are determined by measuring the optical density of the culture using 600 nm light. An array of 600 nm LEDs illuminate the culture and photodiodes are used to measure the shadow on the opposite side of the chamber.Previous experiments showed that we can produce a million fold increase to UV-C radiation over seven iterations. The most recent implements a microfluidic system that can expose cultures to multiple different selection pressures, perform non-survival based selection, and autonomously perform hundreds of exposure cycles. A scalable pump system gives the ability to pump in various different growth media to individual cultures and introduce chemical toxins during experimentation; AADEC can perform freeze and thaw cycles. We improved our baseline characterization by building a custom UV-C exposure hood, a shutter operates on a preset timer allowing the user to set exposure intensity consistently for multiple iterations

Effects of Telehealth on Dropout and Retention in Care among Treatment-Seeking Individuals with Substance Use Disorder: A Retrospective Cohort Study

Background: During the COVID-19 pandemic, telehealth became a widely used method of delivering treatment for substance use disorders (SUD), but its impact upon treatment engagement and dropout remains unknown. Methods: We conducted a retrospective analysis of adult SUD patients (n = 544) between October 2020 and June 2022 among a cohort of treatment-seeking patients at a nonprofit community behavioral health center in Southwestern Ohio. We estimated the likelihood of treatment dropout using survival curves and Cox proportional hazard models, comparing patients who used telehealth with video, telephone, or solely in-person services within the first 14 days of diagnosis. We also compared the likelihood of early treatment engagement. Results: Patients who received services through telehealth with video in the initial 14 days of diagnosis had a lower hazard of dropout, compared to patients receiving solely in-person services (0.64, 95% CI [0.46, 0.90]), while there was no difference in hazards of dropout between patients who received telephone and in-person services. Early use of telehealth, both via video (5.40, 95% CI [1.92, 15.20]) and telephone (2.12, 95% CI [1.05, 4.28]), was associated with greater odds of treatment engagement compared to in-person care. Conclusion: This study adds to the existing literature related to telehealth utilization and engagement in care and supports the inclusion of telehealth in SUD treatment programs for treatment-seeking individuals

MEG imaging of recurrent gliomas reveals functional plasticity of hemispheric language specialization

In patients with gliomas, changes in hemispheric specialization for language determined by magnetoencephalography (MEG) were analyzed to elucidate the impact of treatment and tumor recurrence on language networks. Demonstration of reorganization of language networks in these patients has significant implications on the prevention of postoperative functional loss and recovery. Whole-brain activity during an auditory verb generation task was estimated from MEG recordings in a group of 73 patients with recurrent gliomas. Hemisphere of language dominance was estimated using the language laterality index (LI), a measure derived from the task. The initial scan was performed prior to resection; patients subsequently underwent surgery and adjuvant treatment. A second scan was performed upon recurrence prior to repeat resection. The relationship between the shift in LI between scans and demographics, anatomic location, pathology, and adjuvant treatment was analyzed. Laterality shifts were observed between scans; the median percent change was 29.1% across all patients. Laterality shift magnitude and relative direction were associated with the initial position of language dominance; patients with increased lateralization experienced greater shifts than those presenting more bilateral representation. A change in LI from left or right to bilateral (or vice versa) occurred in 23.3% of patients; complete switch occurred in 5.5% of patients. Patients with tumors within the language-dominant hemisphere experienced significantly greater shifts than those with contralateral tumors. The majority of patients with glioma experience shifts in language network organization over time which correlate with the relative position of language lateralization and tumor location