Browsing by Author "Wagner, Amy K."

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    Comorbid Conditions Among Adults 50 Years and Older With Traumatic Brain Injury: Examining Associations With Demographics, Healthcare Utilization, Institutionalization, and 1-Year Outcomes
    (Wolters Kluwer, 2019) Kumar, Raj G.; Olsen, Jennifer; Juengst, Shannon B.; Dams-OʼConnor, Kristen; OʼNeil-Pirozzi, Therese M.; Hammond, Flora M.; Wagner, Amy K.; Physical Medicine and Rehabilitation, School of Medicine
    Objectives: To assess the relationship of acute complications, preexisting chronic diseases, and substance abuse with clinical and functional outcomes among adults 50 years and older with moderate-to-severe traumatic brain injury (TBI). Design: Prospective cohort study. Participants: Adults 50 years and older with moderate-to-severe TBI (n = 2134). Measures: Clusters of comorbid health conditions empirically derived from non-injury International Classification of Diseases, Ninth Revision codes, demographic/injury variables, and outcome (acute and rehabilitation length of stay [LOS], Functional Independence Measure efficiency, posttraumatic amnesia [PTA] duration, institutionalization, rehospitalization, and Glasgow Outcome Scale-Extended (GOS-E) at 1 year). Results: Individuals with greater acute hospital complication burden were more often middle-aged men, injured in motor vehicle accidents, and had longer LOS and PTA. These same individuals experienced higher rates of 1-year rehospitalization and greater odds of unfavorable GOS-E scores at 1 year. Those with greater chronic disease burden were more likely to be rehospitalized at 1 year. Individuals with more substance abuse burden were most often younger (eg, middle adulthood), black race, less educated, injured via motor vehicle accidents, and had an increased risk for institutionalization. Conclusion: Preexisting health conditions and acute complications contribute to TBI outcomes. This work provides a foundation to explore effects of comorbidity prevention and management on TBI recovery in older adults.
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    Incidence and risk factors of posttraumatic seizures following traumatic brain injury: A Traumatic Brain Injury Model Systems Study
    (Wiley, 2016-12) Ritter, Anne C.; Wagner, Amy K.; Fabio, Anthony; Pugh, Mary Jo; Walker, William C.; Szaflarski, Jerzy P.; Zafonte, Ross D.; Brown, Allen W.; Hammond, Flora M.; Bushnik, Tamara; Johnson-Green, Douglas; Shea, Timothy; Krellman, Jason W.; Rosenthal, Joseph A.; Dreer, Laura E.; Department of Physical Medicine and Rehabilitation, School of Medicine
    Objective Determine incidence of posttraumatic seizure (PTS) following traumatic brain injury (TBI) among individuals with moderate-to-severe TBI requiring rehabilitation and surviving at least 5 years. Methods Using the prospective TBI Model Systems National Database, we calculated PTS incidence during acute hospitalization, and at years 1, 2, and 5 postinjury in a continuously followed cohort enrolled from 1989 to 2000 (n = 795). Incidence rates were stratified by risk factors, and adjusted relative risk (RR) was calculated. Late PTS associations with immediate (<24 h), early (24 h–7 day), or late seizures (>7 day) versus no seizure prior to discharge from acute hospitalization was also examined. Results PTS incidence during acute hospitalization was highest immediately (<24 h) post-TBI (8.9%). New onset PTS incidence was greatest between discharge from inpatient rehabilitation and year 1 (9.2%). Late PTS cumulative incidence from injury to year 1 was 11.9%, and reached 20.5% by year 5. Immediate/early PTS RR (2.04) was increased for those undergoing surgical evacuation procedures. Late PTS RR was significantly greater for individuals who self-identified as a race other than black/white (year 1 RR = 2.22), and for black individuals (year 5 RR = 3.02) versus white individuals. Late PTS was greater for individuals with subarachnoid hemorrhage (year 1 RR = 2.06) and individuals age 23–32 (year 5 RR = 2.43) and 33–44 (year 5 RR = 3.02). Late PTS RR years 1 and 5 was significantly higher for those undergoing surgical evacuation procedures (RR: 3.05 and 2.72, respectively). Significance In this prospective, longitudinal, observational study, PTS incidence was similar to that in studies published previously. Individuals with immediate/late seizures during acute hospitalization have increased late PTS risk. Race, intracranial pathologies, and neurosurgical procedures also influenced PTS RR. Further studies are needed to examine the impact of seizure prophylaxis in high-risk subgroups and to delineate contributors to race/age associations on long-term seizure outcomes.
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    Post-Traumatic Epilepsy Associations with Mental Health Outcomes in the First Two Years after Moderate to Severe TBI: A TBI Model Systems Analysis
    (Elsevier, 2017-08) Juengst, Shannon B.; Wagner, Amy K.; Ritter, Anne C.; Szaflarski, Jerzy P.; Walker, William C.; Zafonte, Ross D.; Brown, Allen W.; Hammond, Flora M.; Pugh, Mary Jo; Shea, Timothy; Krellman, Jason W.; Bushnik, Tamara; Arenth, Patricia M.; Physical Medicine and Rehabilitation, School of Medicine
    Purpose Research suggests that there are reciprocal relationships between mental health (MH) disorders and epilepsy risk. However, MH relationships to post-traumatic epilepsy (PTE) have not been explored. Thus, the objective of this study was to assess associations between PTE and frequency of depression and/or anxiety in a cohort of individuals with moderate-to-severe TBI who received acute inpatient rehabilitation. Methods Multivariate regression models were developed using a recent (2010–2012) cohort (n = 867 unique participants) from the TBI Model Systems (TBIMS) National Database, a time frame during which self-reported seizures, depression [Patient Health Questionnaire (PHQ)-9], and anxiety [Generalized Anxiety Disorder (GAD-7)] follow-up measures were concurrently collected at year-1 and year-2 after injury. Results PTE did not significantly contribute to depression status in either the year-1 or year-2 cohort, nor did it contribute significantly to anxiety status in the year-1 cohort, after controlling for other known depression and anxiety predictors. However, those with PTE in year-2 had 3.34 times the odds (p = .002) of having clinically significant anxiety, even after accounting for other relevant predictors. In this model, participants who self-identified as Black were also more likely to report clinical symptoms of anxiety than those who identified as White. PTE was the only significant predictor of comorbid depression and anxiety at year-2 (Odds Ratio 2.71; p = 0.049). Conclusions Our data suggest that PTE is associated with MH outcomes 2 years after TBI, findings whose significance may reflect reciprocal, biological, psychological, and/or experiential factors contributing to and resulting from both PTE and MH status post-TBI. Future work should consider temporal and reciprocal relationships between PTE and MH as well as if/how treatment of each condition influences biosusceptibility to the other condition.
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    Proceedings of the Second Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness
    (Springer, 2022) Mainali, Shraddha; Aiyagari, Venkatesh; Alexander, Sheila; Bodien, Yelena; Boerwinkle, Varina; Boly, Melanie; Brown, Emery; Brown, Jeremy; Claassen, Jan; Edlow, Brian L.; Fink, Ericka L.; Fins, Joseph J.; Foreman, Brandon; Frontera, Jennifer; Geocadin, Romergryko G.; Giacino, Joseph; Gilmore, Emily J.; Gosseries, Olivia; Hammond, Flora; Helbok, Raimund; Hemphill, J. Claude; Hirsch, Karen; Kim, Keri; Laureys, Steven; Lewis, Ariane; Ling, Geoffrey; Livesay, Sarah L.; McCredie, Victoria; McNett, Molly; Menon, David; Molteni, Erika; Olson, DaiWai; O’Phelan, Kristine; Park, Soojin; Polizzotto, Len; Provencio, Jose Javier; Puybasset, Louis; Venkatasubba Rao, Chethan P.; Robertson, Courtney; Rohaut, Benjamin; Rubin, Michael; Sharshar, Tarek; Shutter, Lori; Silva, Gisele Sampaio; Smith, Wade; Steven, Robert D.; Thibaut, Aurore; Vespa, Paul; Wagner, Amy K.; Ziai, Wendy C.; Zink, Elizabeth; Suarez, Jose I.; Physical Medicine and Rehabilitation, School of Medicine
    This proceedings article presents actionable research targets on the basis of the presentations and discussions at the 2nd Curing Coma National Institutes of Health (NIH) symposium held from May 3 to May 5, 2021. Here, we summarize the background, research priorities, panel discussions, and deliverables discussed during the symposium across six major domains related to disorders of consciousness. The six domains include (1) Biology of Coma, (2) Coma Database, (3) Neuroprognostication, (4) Care of Comatose Patients, (5) Early Clinical Trials, and (6) Long-term Recovery. Following the 1st Curing Coma NIH virtual symposium held on September 9 to September 10, 2020, six workgroups, each consisting of field experts in respective domains, were formed and tasked with identifying gaps and developing key priorities and deliverables to advance the mission of the Curing Coma Campaign. The highly interactive and inspiring presentations and panel discussions during the 3-day virtual NIH symposium identified several action items for the Curing Coma Campaign mission, which we summarize in this article.
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    Prognostic models for predicting posttraumatic seizures during acute hospitalization, and at 1 and 2 years following traumatic brain injury
    (Wiley, 2016-09) Ritter, Anne C.; Wagner, Amy K.; Szaflarski, Jerzy P.; Brooks, Maria M.; Zafonte, Ross D.; Pugh, Mary Jo; Fabio, Anthony; Hammond, Flora M.; Dreer, Laura E.; Bushnik, Tamara; Walker, William C.; Brown, Allen W.; Johnson-Greene, Doug; Shea, Timothy; Krellman, Jason W.; Rosenthal, Joseph A.; Department of Physical Medicine and Rehabilitation, IU School of Medicine
    Objective Posttraumatic seizures (PTS) are well-recognized acute and chronic complications of traumatic brain injury (TBI). Risk factors have been identified, but considerable variability in who develops PTS remains. Existing PTS prognostic models are not widely adopted for clinical use and do not reflect current trends in injury, diagnosis, or care. We aimed to develop and internally validate preliminary prognostic regression models to predict PTS during acute care hospitalization, and at year 1 and year 2 postinjury. Methods Prognostic models predicting PTS during acute care hospitalization and year 1 and year 2 post-injury were developed using a recent (2011–2014) cohort from the TBI Model Systems National Database. Potential PTS predictors were selected based on previous literature and biologic plausibility. Bivariable logistic regression identified variables with a p-value < 0.20 that were used to fit initial prognostic models. Multivariable logistic regression modeling with backward-stepwise elimination was used to determine reduced prognostic models and to internally validate using 1,000 bootstrap samples. Fit statistics were calculated, correcting for overfitting (optimism). Results The prognostic models identified sex, craniotomy, contusion load, and pre-injury limitation in learning/remembering/concentrating as significant PTS predictors during acute hospitalization. Significant predictors of PTS at year 1 were subdural hematoma (SDH), contusion load, craniotomy, craniectomy, seizure during acute hospitalization, duration of posttraumatic amnesia, preinjury mental health treatment/psychiatric hospitalization, and preinjury incarceration. Year 2 significant predictors were similar to those of year 1: SDH, intraparenchymal fragment, craniotomy, craniectomy, seizure during acute hospitalization, and preinjury incarceration. Corrected concordance (C) statistics were 0.599, 0.747, and 0.716 for acute hospitalization, year 1, and year 2 models, respectively. Significance The prognostic model for PTS during acute hospitalization did not discriminate well. Year 1 and year 2 models showed fair to good predictive validity for PTS. Cranial surgery, although medically necessary, requires ongoing research regarding potential benefits of increased monitoring for signs of epileptogenesis, PTS prophylaxis, and/or rehabilitation/social support. Future studies should externally validate models and determine clinical utility.
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    Research Needs for Prognostic Modeling and Trajectory Analysis in Patients with Disorders of Consciousness
    (Springer, 2021) Hammond, Flora M.; Katta-Charles, Sheryl; Russell, Mary Beth; Zafonte, Ross D.; Claassen, Jan; Wagner, Amy K.; Puybasset, Louis; Egawa, Satoshi; Laureys, Steven; Diringer, Michael; Stevens, Robert D.; Curing Coma Campaign and its Contributing Members; Physical Medicine and Rehabilitation, School of Medicine
    Background: The current state of the science regarding the care and prognosis of patients with disorders of consciousness is limited. Scientific advances are needed to improve the accuracy, relevance, and approach to prognostication, thereby providing the foundation to develop meaningful and effective interventions. Methods: To address this need, an interdisciplinary expert panel was created as part of the Coma Science Working Group of the Neurocritical Care Society Curing Coma Campaign. Results: The panel performed a gap analysis which identified seven research needs for prognostic modeling and trajectory analysis ("recovery science") in patients with disorders of consciousness: (1) to define the variables that predict outcomes; (2) to define meaningful intermediate outcomes at specific time points for different endotypes; (3) to describe recovery trajectories in the absence of limitations to care; (4) to harness big data and develop analytic methods to prognosticate more accurately; (5) to identify key elements and processes for communicating prognostic uncertainty over time; (6) to identify health care delivery models that facilitate recovery and recovery science; and (7) to advocate for changes in the health care delivery system needed to advance recovery science and implement already-known best practices. Conclusion: This report summarizes the current research available to inform the proposed research needs, articulates key elements within each area, and discusses the goals and advances in recovery science and care anticipated by successfully addressing these needs.
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    Using Machine Learning to Examine Suicidal Ideation After TBI: A TBI Model Systems National Database Study
    (Wolters Kluwer, 2023) Fisher, Lauren B.; Curtiss, Joshua E.; Klyce, Daniel W.; Perrin, Paul B.; Juengst, Shannon B.; Gary, Kelli W.; Niemeier, Janet P.; McConnell Hammond, Flora; Bergquist, Thomas F.; Wagner, Amy K.; Rabinowitz, Amanda R.; Giacino, Joseph T.; Zafonte, Ross D.; Physical Medicine and Rehabilitation, School of Medicine
    Objective: The aim of the study was to predict suicidal ideation 1 yr after moderate to severe traumatic brain injury. Design: This study used a cross-sectional design with data collected through the prospective, longitudinal Traumatic Brain Injury Model Systems network at hospitalization and 1 yr after injury. Participants who completed the Patient Health Questionnaire-9 suicide item at year 1 follow-up ( N = 4328) were included. Results: A gradient boosting machine algorithm demonstrated the best performance in predicting suicidal ideation 1 yr after traumatic brain injury. Predictors were Patient Health Questionnaire-9 items (except suicidality), Generalized Anxiety Disorder-7 items, and a measure of heavy drinking. Results of the 10-fold cross-validation gradient boosting machine analysis indicated excellent classification performance with an area under the curve of 0.882. Sensitivity was 0.85 and specificity was 0.77. Accuracy was 0.78 (95% confidence interval, 0.77-0.79). Feature importance analyses revealed that depressed mood and guilt were the most important predictors of suicidal ideation, followed by anhedonia, concentration difficulties, and psychomotor disturbance. Conclusions: Overall, depression symptoms were most predictive of suicidal ideation. Despite the limited clinical impact of the present findings, machine learning has potential to improve prediction of suicidal behavior, leveraging electronic health record data, to identify individuals at greatest risk, thereby facilitating intervention and optimization of long-term outcomes after traumatic brain injury.