Madonna Rehabilitation Hospital

Introduction: Post-acute care (PAC) facilities across Montana, Nebraska, and North Dakota participated in the American Heart Association’s (AHA) Tri-State Mission: Lifeline Stroke PAC Initiative, a quality improvement initiative focused on improving stroke rehabilitation across Midwest states from 2022 to 2024. Participating facilities agreed to implement evidence-based practice outlined by AHA’s PAC Stroke Program Standards. Purpose: The Tri-State Mission: Lifeline Stroke PAC Initiative aimed to assist facilities to implement evidenced-based care and track key performance measures and outcome metrics to facilitate ongoing quality improvement. 15 skilled nursing facilities, 7 inpatient rehabilitation facilities, and 15 critical access hospitals participated across three states with emphasis on developing programs in rural communities. Methods: Participating facilities collected quarterly data for six clinical measures and three outcome metrics detailed in the PAC stroke program standards. Data was entered on the Quality and Certification Tool (QCT) platform to track progress and compare to other sites in the initiative. Group data was reviewed with facilities each quarter on virtual learning collaboratives. Results: Positive improvements were reported in four measures: percentage of patients with aphasia receiving speech therapy, patients receiving comprehensive stroke education, patients with impaired mobility who are on a VTE prophylaxis plan, and patients receiving a phone call within 3 business days of discharge. Performance remained consistent in two measures: percentage of patients receiving a depression screening and patients that had an admission assessment completed by an MD or APP in the first 24 hours. Outcome metrics of average length of stay, number of patients, and discharge disposition remained consistent. Conclusion: Focused quality improvement efforts can positively impact key measures and metrics in post-acute stroke programs. While positive trends were observed in four measures, further evaluations need to be done with larger patient volumes and extended periods of time.

Exoskeletons offer promising solutions for enhancing human mobility; however, personalizing assistance parameters to optimize physiological outcomes remains challenging. Human-in-the-loop (HIL) optimization has emerged as an effective strategy for tailoring device control, often using electromyography (EMG) as a real-time proxy for metabolic cost. This study simulates HIL optimization using surrogate models built from the average root mean square of the muscles’ activations (EMG-RMS) derived from treadmill walking trials with a robotic waist tether. Nine surrogate models were evaluated for prediction accuracy, including gradient boosting (GB), random forest, support vector regression, and Gaussian process variants. Seven global optimization algorithms were compared based on convergence time, EMG-RMS at optimum, and efficiency metrics. GB achieved the highest predictive accuracy (1.57% RAEP). Among optimizers, the gravitational search algorithm (GSA) produced the lowest EMG-RMS value (0.17 normalized units) and the fastest convergence (0.32 s), while particle swarm optimization (PSO) achieved 0.36 EMG-RMS in 1.61 s. These findings demonstrate the value of EMG-based simulation frameworks in guiding algorithm selection for HIL optimization, ultimately reducing the experimental burden in developing personalized exoskeleton assistance strategies.

Introduction: Peripheral Artery Disease (PAD) is a progressive vascular disorder impairing mobility, raising fall risk, and reducing quality of life. Early detection is key to preventing amputations and cardiovascular events. Current methods, often subjective, invasive, or costly, limit screening. Artificial intelligence and wearable technology enable non-invasive PAD detection via gait analysis. This study uses machine learning to classify PAD with gait stability and nonlinear dynamics. Hypothesis: We hypothesize that machine learning models trained on Margin of Stability (MOS) and nonlinear gait features can classify PAD and Control groups, offering a non-invasive tool for early detection. Goals: Objectives are to analyze gait stability differences between PAD and Control groups, quantify variability with nonlinear metrics, and develop a machine learning model for PAD classification. Methods: Gait data from 139 PAD patients and 52 controls were collected using a motion capture system with passive markers to derive center of mass (COM). MOS was calculated in anterior-posterior (AP) and mediolateral (ML) directions. Spatiotemporal parameters (step duration, width, length, speed) and nonlinear dynamics (Lyapunov Exponent Wolf’s and Rosenstein’s [LyE W , LyE R ], Sample Entropy [SpEn], Detrended Fluctuation Analysis [DFA], Correlation Dimension [CD], Approximate Entropy [ApEn]) were assessed. An Optimized Ensemble Model was trained on position-, velocity-, and acceleration-based features, evaluating MOS, spatiotemporal, and nonlinear contributions. Performance was measured by accuracy and feature importance. Results: The Optimized Ensemble Model classified PAD versus Control groups. The position-based model achieved 92% validation and 92.6% test accuracy, velocity-based 85.3% and 85.2%, and acceleration-based 87.3% and 92.6%. Feature importance identified MOS ML (0.0999), LyE R (0.0953), LyE W (0.0903) for position; Step time (0.7626), Step length (0.5028), CD (0.1920) for velocity; and Step time (0.1991), Step length (0.1938), ApEn (0.0730) for acceleration. Conclusion: The Optimized Ensemble Model classifies PAD using gait stability and nonlinear dynamics. The position-based model (92.6% accuracy) excels, with MOS ML and MOS AP reflecting PAD stability deficits. LyE R , LyE W , and Step time show variability. Velocity (85.2%) and acceleration (92.6%) models highlight Step time and length, with ApEn capturing fluctuations. Future work will validate findings and test sensors.

ABSTRACT Purpose To understand the impact of post-acute sequelae of COVID-19 (PASC) on quality of life (QOL) in a Midwestern community sample. Design Anonymous online cross-sectional community survey. Methods Survey responses collected July 2023-October 2024 were examined from 1,564 individuals reporting prior COVID-19 positive test or diagnosis. Logistic regressions and sensitivity analyses using subset of data were conducted to identify symptoms significantly associated with perceived Current QOL (determined by “Taking everything in your life into account, please rate your current overall QOL”) and Deteriorated QOL (i.e., Current QOL rated lower than QOL prior to SARS CoV-2 infection). Findings Current QOL was predicted by pre-infection QOL and more frequent experiences of work/school difficulties, challenges with shopping/cleaning/driving/meal-prep, anxiety, depression, fatigue/tiredness, light headedness/fainting/rapid heartbeat episodes, and diminished activity/exercise tolerance (C-statistic = 0.84). Compared to the full dataset’s primary analyses, sensitivity analysis revealed all identified predictors except three physical symptoms remained significant Current QOL predictors. Deteriorated QOL after SARS-CoV-2 infection was predicted by pre-infection QOL, and more frequent experiences of work/school difficulties, diminished activity/exercise tolerance, anxiety, depression, trouble completing daily activities, fatigue/tiredness, and slow mental processing (C-statistic = 0.85). In contrast, sensitivity analysis revealed frequency of SARS-CoV-2 infection, pre-infection QOL, and more frequent challenges with shopping/cleaning/driving/meal-prep were the only significant predictors of Deteriorated QOL. Conclusions PASC negatively impacted QOL. Pre-infection QOL may influence perceived post-infection QOL. Clinical Evidence Results make a compelling case for community nurses to identify PASC, rule-out underlying medical causes, and refer patients for interdisciplinary post-COVID rehabilitation to improve health outcomes and QOL.

Abstract ObjectiveThe goal was to explore mechanisms linking cumulative stressors with parent stress during COVID‐19.BackgroundPublic health measures helped contain COVID‐19 spread, but disrupted family life and increased parents' stress. Positive family relationships and beliefs about the impact of challenges can foster psychological resilience during adversity and may influence parents' stress.MethodParticipants included parents from the U.S. sample of the internet‐based Covid Family Life Study survey who indicated they were married or living with a romantic partner (n = 1,386). We tested a moderated mediation model predicting parent stress from the pileup of stressors, family and couple relationship satisfaction, and parent resilience beliefs.ResultsHigh stressor pileup was associated with lower family and couple relationship satisfaction, and higher parent stress. Relationship satisfaction mediated the effect of stressor pileup on parent stress, and the indirect effects were similar across all levels of parent resilience beliefs. Family satisfaction mediated the effect of stressor pileup on parent stress only for parents with low resilience beliefs. Parent resilience beliefs moderated the relations between relational well‐being and parent stress. Higher family satisfaction was associated with lower stress for parents with low and moderate levels of resilience beliefs, but higher stress for parents with high resilience beliefs.ConclusionRelationship satisfaction may explain how stressor pileup affects parent stress. Resilience beliefs may affect the explanatory role of family satisfaction.ImplicationsInterventions to improve family satisfaction may be most impactful for parents who have low confidence in their ability to adapt to change and bounce back from adversity.

BackgroundPatients with severe acute brain injuries (SABI) are at risk of living with long-term disability, frequent medical complications and high rates of mortality. Determining an individual patient’s prognosis and conveying this to family members/caregivers can be challenging. We conducted a webinar with experts in neurosurgery, neurocritical care, neuro-palliative care, neuro-ethics, and rehabilitation as part of the Curing Coma Campaign, which is supported by the Neurocritical Care Society. The webinar discussed topics focused on prognostic uncertainty, communicating prognosis to family members/caregivers, gaps within healthcare systems, and research infrastructure as it relates to patients experiencing SABI. The purpose of this manuscript is to describe the themes that emerged from this virtual discussion.MethodsA qualitative analysis of a webinar “Prognostic Humility and Ethical Dilemmas in Acute Brain Injury” was organized as part of the Neurocritical Care Society’s Curing Coma Campaign. A multidisciplinary group of experts was invited as speakers and moderators of the webinar. The content of the webinar was transcribed verbatim. Two qualitative researchers (NK and BM) read and re-read the transcription, and familiarized themselves with the text. The two coders developed and agreed on a code book, independently coded the transcript, and discussed any discrepancies. The transcript was analyzed using inductive thematic analysis of codes and themes that emerged within the expert discussion.ResultsWe coded 168 qualitative excerpts within the transcript. Two main themes were discussed: (1) the concept of prognostic uncertainty in the acute setting, and (2) lack of access to and evidence for quality rehabilitation and specialized continuum of care efforts specific to coma research. Within these two main themes, we found 5 sub-themes, which were broken down into 23 unique codes. The most frequently described code was the need for clinicians to acknowledge our own uncertainties when we discuss prognosis with families, which was mentioned 13 times during the webinar. Several strategies were described for speaking with surrogates of patients who have had a severe brain injury resulting in SABI. We also identified important gaps in the United States health system and in research to improve the care of patients with severe brain injuries.ConclusionAs a result of this webinar and expert discussion, authors identified and analyzed themes related to prognostic uncertainty with SABI. Recommendations were outlined for clinicians who engage with surrogates of patients with SABI to foster informed decisions for their loved one. Finally, recommendations for changes in healthcare systems and research support are provided in order to continue to propel SABI science forward to improve future prognostic certainty.

Introduction: Urban and rural stroke care disparities are pervasive for post-acute stroke rehabilitation. Mission:Lifeline Stroke conducted a needs assessment to identify needs and gaps in care for stroke rehabilitation throughout rural Nebraska (NE). Purpose: The assessment included surveys of healthcare providers (HCPs) and stroke survivors to inform a robust understanding of stroke rehabilitation needs across NE, addressing barriers and facilitators to care, including outpatient therapy, social support, equipment, and patient-facing resources. Methods: HCPs were recruited through the Nebraska Stroke Advisory Council to complete a 17-question online survey. Survivors in NE were recruited through social media and existing stroke support groups to complete a 26-question online survey. Results: Respondents of the HCP survey (N=260) identified the top barrier to providing care to survivors as lack of insurance (62%), lack of caregiver support (42%), and lack of specialized services (42%). Respondents of the survivor survey (N=30) identified top barriers as lack of insurance (74%), financial burden (64%), and lack of caregiver/social support (50%). Both HCPs’ and survivors identified lack of caregiver and social support as resources missing from their community, and survivors identified communication about support groups or sources of emotional support (n=4) as the top missing resource. In addition, 39% of survivors indicated an interest in attending a support group. HCPs indicated missing resources primarily include specialized rehab equipment, technology, and services (52%), and professional opportunities for staff (37%). Regarding resources provided to survivors, most HCPs indicated community resources (94%) are provided, proceeded by follow-up/continued outpatient therapy (88%). In slight contrast, survivors indicated the top resources they learned of when discharged were outpatient physical therapy (82%), outpatient occupational therapy (70%), and outpatient speech therapy (56%). Conclusion: Although both healthcare providers and survivors identified outpatient therapies are made available, there is a need for more communication about support groups and physical resources such as rehab equipment, technology, and services.

ABSTRACT Following a severe brain injury (BI), some literate individuals who require augmentative and alternative communication (AAC) strategies to support communication may benefit from the use of onscreen keyboards to generate text. A range of layouts are available to these individuals within specialized communication software. However, a paucity of information is available to describe user preferences, user perceptions, as well as the visual-cognitive processing demands of such layouts. Such information is critical to guide clinical decision-making for keyboard selection and to provide patient-centered services. This study: (a) described the preferences and perceptions of two onscreen keyboard layouts (QWERTY and alphabetic) and (b) used eye-tracking analysis to investigate the visual-cognitive processing demands between these onscreen keyboards for individuals with and without BI. Results indicated participants in both groups held a strong preference for QWERTY keyboard interfaces and had extensive prior experience using the QWERTY keyboard layout on mobile devices. Eye-tracking analysis revealed less visual-cognitive processing demands using a QWERTY keyboard layout for both groups but were only statistically significant for those without BI. Results suggest that use of a keyboard layout that aligns with client preferences and prior experiences (i.e., the QWERTY keyboard for these participants) may lead to increased satisfaction with the communication experience and increased communication efficiency.

Objective:Selective serotonin reuptake inhibitors (SSRIs) are the cornerstone of treatment of major depressive disorder (MDD). However, non-response is common, often necessitating combination strategies. The present study assessed the efficacy of vortioxetine as an add-on therapy in patients with SSRI-resistant MDD.Methods:The charts of 36 adult outpatients with DSM-IV-TR MDD who had not achieved a response after at least 8 weeks of treatment with an SSRI were reviewed retrospectively. Subjects were treated with vortioxetine (5-20 mg/day) for 8 weeks added to the current SSRI. The main outcome measures were change from baseline in total Hamilton Scale for Depression (HAM-D) score and the rate of response (a 50% or greater reduction in HAM-D score and a Clinical Global Impression ‐ Improvement module [CGI-I] score of 1 or 2 at endpoint). HAM-D scores ≤ 7 were considered as remission. Additional outcome measures included the Snaith-Hamilton Pleasure Scale (SHAPS) and the Scale for Suicide Ideation (SSI).Results:32 patients completed the 8 weeks of treatment. At 8 weeks, a significant reduction in HAM-D score was observed (p ≤ 0.001), with response obtained by 41.7% and remission by 33.3% of patients. Significant reductions in SHAPS and SSI were also observed (p ≤ 0.001 for both scales).Conclusions:Adjunctive vortioxetine may be useful and well-tolerated in stage I treatment-resistant depression. However, the limitations of this study (such as small sample size, absence of randomization and control group, retrospective design, etc.) must be considered.