Browsing by Author "Walker, William C."
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Item Associations of Chronic Pain With Psychosocial Outcomes After Traumatic Brain Injury: A NIDILRR and VA TBI Model Systems Collaborative Project(Wolters Kluwer, 2024) Hanks, Robin; Ketchum, Jessica M.; Peckham, Mackenzie; Sevigny, Mitch; Sander, Angelle M.; Martin, Aaron M.; Agtarap, Stephanie; Beaulieu, Cynthia L.; Callender, Libby; Hammond, Flora M.; Lengenfelder, Jeannie; Rabinowitz, Amanda R.; Walker, William C.; Hoffman, Jeanne M.; Harrison-Felix, Cynthia; Nakase-Richardson, Risa; Physical Medicine and Rehabilitation, School of MedicineObjective: To examine the differences in participation, life satisfaction, and psychosocial outcomes among individuals with traumatic brain injury (TBI) endorsing current, past, or no chronic pain. Setting: Community. Participants: Three thousand eight hundred four TBI Model Systems participants 1 to 30 years of age postinjury classified into 1 of 3 groups based on their pain experience: current pain, past pain, no pain completed a Pain Survey at their usual follow-up appointment which on average was approximately 8 years postinjury. Design: Multisite, cross-sectional observational cohort study. Main outcome measures: Sociodemographic and injury characteristics and psychosocial outcomes (ie, satisfaction with life, depression, anxiety, posttraumatic stress disorder [PTSD], sleep quality, community participation). Results: Persons with current chronic pain demonstrated higher scores on measures of PTSD, anxiety, and depression, and the lower scores on measures of sleep quality, community participation and satisfaction with life. Those with resolved past pain had mean scores for these outcomes that were all between the current and no chronic pain groups, but always closest to the no pain group. After adjusting for sociodemographic and function in multivariate analysis, having current chronic pain was associated with more negative psychosocial outcomes. The largest effect sizes (ES; in absolute value) were observed for the PTSD, depression, anxiety, and sleep quality measures (ES = 0.52-0.81) when comparing current pain to past or no pain, smaller ES were observed for life satisfaction (ES = 0.22-0.37) and out and about participation (ES = 0.16-0.18). When comparing past and no pain groups, adjusted ES were generally small for life satisfaction, PTSD, depression, anxiety, and sleep quality (ES = 0.10-0.23) and minimal for participation outcomes (ES = 0.02-0.06). Conclusions: Chronic pain is prevalent among individuals with TBI and is associated with poorer psychosocial outcomes, especially for PTSD, depression, anxiety, and sleep disturbance. The results from this study highlight the presence of modifiable comorbidities among those with chronic pain and TBI. Persons who experience persistent pain following TBI may be at greater risk for worse psychosocial outcomes.Item Characterizing Extreme Phenotypes for Pain Interference in Persons with Chronic Pain following Traumatic Brain Injury: A NIDILRR and VA TBI Model Systems Collaborative Project(Wolters Kluwer, 2024) Hoffman, Jeanne M.; Ketchum, Jessica M.; Agtarap, Stephanie; Dams-O’Connor, Kristen; Hammond, Flora M.; Martin, Aaron M.; Sevigny, Mitch; Walker, William C.; Harrison-Felix, Cynthia; Zafonte, Ross; Nakase-Richardson, Risa; Physical Medicine and Rehabilitation, School of MedicineObjective: To define and characterize extreme phenotypes based on pain interference for persons with chronic pain following traumatic brain injury (TBI). Setting: Eighteen Traumatic Brain Injury Model System (TBIMS) Centers. Participants: A total of 1762 TBIMS participants 1 to 30 years post-injury reporting chronic pain at their most recent follow-up interview. Primary measures: The Brief Pain Inventory (BPI) interference scale, sociodemographic, injury, functional outcome, pain, and treatment characteristics. Results: Participants were predominantly male (73%), White (75%), middle-aged (mean 46 years), and who were injured in motor vehicle accidents (53%) or falls (20%). Extreme phenotypes were identified based on upper and lower 25th percentiles to create low-interference ( n = 441) and high-interference ( n = 431) extreme phenotypes. Bivariate comparisons found several sociodemographic, injury, function, pain, and treatment differences between extreme phenotype groups, including significant differences ( P < .001) on all measures of concurrent function with those in the low-interference extreme phenotype experiencing better function than those in the high-interference extreme phenotype. Lasso regression combined with logistic regression identified multivariable predictors of low- versus high-interference extreme phenotypes. Reductions in the odds of low- versus high-interference phenotypes were significantly associated with higher pain intensity (odds ratio [OR] = 0.33), having neuropathic pain (OR = 0.40), migraine headache (OR = 0.41), leg/feet pain (OR = 0.34), or hip pain (OR = 0.46), and more pain catastrophizing (OR = 0.81). Conclusion: Results suggest that for those who experience current chronic pain, there is high variability in the experience and impact of pain. Future research is needed to better understand how pain experience impacts individuals with chronic pain and TBI given that pain characteristics were the primary distinguishing factors between phenotypes. The use of extreme phenotypes for pain interference may be useful to better stratify samples to determine efficacy of pain treatment for individuals with TBI.Item Characterizing Extreme Phenotypes for Perceived Improvement from Treatment in Persons with Chronic Pain following Traumatic Brain Injury: A NIDILRR and VA TBI Model Systems Collaborative Project(Wolters Kluwer, 2024) Hoffman, Jeanne M.; Ketchum, Jessica M.; Agtarap, Stephanie; Dams-O’Connor, Kristen; Hammond, Flora M.; Martin, Aaron M.; Sevigny, Mitch; Walker, William C.; Harrison-Felix, Cynthia; Zafonte, Ross; Nakase-Richardson, Risa; Physical Medicine and Rehabilitation, School of MedicineObjective: To define and characterize extreme phenotypes based on perceived improvement in pain for persons with chronic pain following traumatic brain injury (TBI). Setting: Eighteen Traumatic Brain Injury Model System (TBIMS) Centers. Participants: A total of 1762 TBIMS participants 1 to 30 years post-injury reporting chronic pain at their most recent follow-up interview. Primary measures: The Patient's Global Impression of Change (PGIC) related to pain treatment. Sociodemographic, injury, functional outcome, pain, and pain treatment characteristics. Results: Participants were mostly male (73%), White (75%), middle-aged (mean 46 years), injured in motor vehicle accidents (53%), or falls (20%). Extreme phenotypes were created for an extreme improvement phenotype ( n = 512, 29.8%) defined as "moderately better" or above on the PGIC and an extreme no-change group ( n = 290, 16.9%) defined as no change or worse. Least absolute shrinkage and selection operator (LASSO) regression combined with logistic regression identified multivariable predictors of improvement versus no-change extreme phenotypes. Higher odds of extreme improvement phenotype were significantly associated with being female (odds ratio [OR] = 1.85), married versus single (OR = 2.02), better motor function (OR = 1.03), lower pain intensity (OR = 0.78), and less frequent pain, especially chest pain (OR = 0.36). Several pain treatments were associated with higher odds of being in the extreme improvement versus no-change phenotypes including pain medication (OR = 1.85), physical therapy (OR = 1.51), yoga (OR = 1.61), home exercise program (OR = 1.07), and massage (OR = 1.69). Conclusion: Investigation of extreme phenotypes based on perceived improvement with pain treatment highlights the ability to identify characteristics of individuals based on pain treatment responsiveness. A better understanding of the biopsychosocial characteristics of those who respond and do not respond to pain treatments received may help inform better surveillance, monitoring, and treatment. With further research, the identification of risk factors (such as pain intensity and frequency) for treatment response/nonresponse may provide indicators to prompt changes in care for individuals with chronic pain after TBI.Item Distal and Proximal Predictors of Rehospitalization Over 10 Years Among Survivors of TBI: A National Institute on Disability, Independent Living, and Rehabilitation Research Traumatic Brain Injury Model Systems Study(Wolters Kluwer, 2023) Lercher, Kirk; Kumar, Raj G.; Hammond, Flora M.; Zafonte, Ross D.; Hoffman, Jeanne M.; Walker, William C.; Verduzco-Gutierrez, Monica; Dams-O’Connor, Kristen; Physical Medicine and Rehabilitation, School of MedicineObjective: To describe the rates and causes of rehospitalization over a 10-year period following a moderate-severe traumatic brain injury (TBI) utilizing the Healthcare Cost and Utilization Project (HCUP) diagnostic coding scheme. Setting: TBI Model Systems centers. Participants: Individuals 16 years and older with a primary diagnosis of TBI. Design: Prospective cohort study. Main measures: Rehospitalization (and reason for rehospitalization) as reported by participants or their proxies during follow-up telephone interviews at 1, 2, 5, and 10 years postinjury. Results: The greatest number of rehospitalizations occurred in the first year postinjury (23.4% of the sample), and the rates of rehospitalization remained stable (21.1%-20.9%) at 2 and 5 years postinjury and then decreased slightly (18.6%) at 10 years postinjury. Reasons for rehospitalization varied over time, but seizure was the most common reason at 1, 2, and 5 years postinjury. Other common reasons were related to need for procedures (eg, craniotomy or craniectomy) or medical comorbid conditions (eg, diseases of the heart, bacterial infections, or fractures). Multivariable logistic regression models showed that Functional Independence Measure (FIM) Motor score at time of discharge from inpatient rehabilitation was consistently associated with rehospitalization at all time points. Other factors associated with future rehospitalization over time included a history of rehospitalization, presence of seizures, need for craniotomy/craniectomy during acute hospitalization, as well as older age and greater physical and mental health comorbidities. Conclusion: Using diagnostic codes to characterize reasons for rehospitalization may facilitate identification of baseline (eg, FIM Motor score or craniotomy/craniectomy) and proximal (eg, seizures or prior rehospitalization) factors that are associated with rehospitalization. Information about reasons for rehospitalization can aid healthcare system planning. By identifying those recovering from TBI at a higher risk for rehospitalization, providing closer monitoring may help decrease the healthcare burden by preventing rehospitalization.Item 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 MedicineObjective 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.Item 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 MedicinePurpose 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.Item Predictive utility of an adapted Marshall head CT classification scheme after traumatic brain injury(Taylor & Francis, 2019-01-19) Brown, Allen W.; Pretz, Christopher R.; Bell, Kathleen R.; Hammond, Flora M.; Arciniegas, David B.; Bodien, Yelena G.; Dams-O’Connor, Kristen; Giacino, Joseph T.; Hart, Tessa; Johnson-Greene, Douglas; Kowalski, Robert G.; Walker, William C.; Weintraub, Alan; Zafonte, Ross; Physical Medicine and Rehabilitation, School of MedicineObjective: To study the predictive relationship among persons with traumatic brain injury (TBI) between an objective indicator of injury severity (the adapted Marshall computed tomography [CT] classification scheme) and clinical indicators of injury severity in the acute phase, functional outcomes at inpatient rehabilitation discharge, and functional and participation outcomes at 1 year after injury, including death.Participants: The sample involved 4895 individuals who received inpatient rehabilitation following acute hospitalization for TBI and were enrolled in the Traumatic Brain Injury Model Systems National Database between 1989 and 2014.Design: Head CT variables for each person were fit into adapted Marshall CT classification categories I through IV.Main Measures: Prediction models were developed to determine the amount of variability explained by the CT classification categories compared with commonly used predictors, including a clinical indicator of injury severity.Results: The adapted Marshall classification categories aided only in the prediction of craniotomy or craniectomy during acute hospitalization, otherwise making no meaningful contribution to variance in the multivariable models predicting outcomes at any time point after injury.Conclusion: Results suggest that head CT findings classified in this manner do not inform clinical discussions related to functional prognosis or rehabilitation planning after TBI.Item Predictors of Missed Follow-up Visits in the National Traumatic Brain Injury Model Systems Cohort Study(Elsevier, 2022-12) Vos, Leia; Ngan, Esther; Novelo, Luis Leon; Williams , Michael W.; Hammond, Flora M.; Walker, William C.; Clark, Allison N.; Lopez, Andrea P. Ochoa; Juengst, Shannon B.; Sherer, Mark; Physical Medicine and Rehabilitation, School of MedicineObjective To identify key variables that could predict risk of loss to follow-up (LTFU) in a nationally funded longitudinal database of persons with traumatic brain injury. Design Secondary analysis of a prospective longitudinal cohort study. Setting Traumatic Brain Injury Model System (TBIMS) Centers in the US. Participants A total of 17,956 TBIMS participants (N=17,956) with interview status data available were included if eligible for 1-, 2-, 5-, 10-, 15-, or 20-year follow-ups between October 31, 1989, and September 30, 2020. Interventions Not applicable. Main Outcome Measures Follow-up data collection completion status at years 1, 2, 5, 10, 15, and 20. Results Information relevant to participants’ history, injury characteristics, rehabilitation stay, and patterns of follow-up across 20 years were considered using a series of logistic regression models. Overall, LTFU rates were low (consistently <20%). The most robust predictors of LTFU across models were missed earlier follow-ups and demographic factors including Hispanic ethnicity, lower education, and lack of private health insurance. Conclusions Efforts to retain participants in such social disadvantaged or minority groups are encouraged given their disproportionate rate of LTFU. Repeated attempts to reach participants after a previously missed assessment are beneficial because many participants that missed 1 or more follow-ups were later recovered.Item 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 MedicineObjective 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.Item Relationship Between Extreme Pain Phenotypes and Psychosocial Outcomes in Persons With Chronic Pain Following Traumatic Brain Injury: A NIDILRR and VA TBI Model Systems Collaborative Project(Wolters Kluwer, 2024) Ketchum, Jessica M.; Hoffman, Jeanne M.; Agtarap, Stephanie; Hammond, Flora M.; Martin, Aaron M.; Walker, William C.; Zafonte, Ross; Harrison-Felix, Cynthia; Nakase-Richardson, Risa; Physical Medicine and Rehabilitation, School of MedicineObjective: To examine the relationship between extreme pain phenotypes (interference and improvement) and psychosocial outcomes among those with chronic pain after traumatic brain injury (TBI). Setting: Community. Participants: In total, 1762 TBI Model Systems (TBIMS) participants 1 to 30 years postinjury reporting chronic pain. Design: Multisite, cross-sectional, observational cohort study. Primary measures: Life satisfaction, posttraumatic stress, depression and anxiety symptoms, sleep and participation, the Brief Pain Inventory (BPI) interference scale, and the Patient's Global Impression of Change (PGIC). Results: Persons in the extreme high interference phenotype (vs extreme low interference phenotype) and/or extreme no change phenotype (vs extreme improvement phenotype) had poorer psychosocial outcomes, with extreme pain interference phenotypes having a larger effect on outcomes than extreme perceived improvement phenotypes. After controlling for covariates, large effect sizes (ES) related to pain interference were observed for posttraumatic stress symptoms (ES = -1.14), sleep quality (ES = -1.10), depression (ES = -1.08), anxiety (ES = -0.82), and life satisfaction (ES = 0.76); effect sizes for participation outcomes, although significant, were relatively small (ES = 0.21-0.36). Effect sizes related to perceived improvement were small for life satisfaction (ES = 0.20) and participation (ES = 0.16-0.21) outcomes. Pain intensity was identified as a meaningful confounding factor of the relationships between extreme phenotypes and posttraumatic stress, depression, anxiety, and sleep quality. Conclusions: Examination of extreme phenotypes provides important insights into the experience of individuals living with chronic pain and TBI. Results suggest that the relationships among a variety of characteristics of the person, their experience with pain, and treatment of pain are complex. Further research is needed to better understand these complex relationships and how differences in pain interference and perceived improvement from treatment can assist in assessment and treatment of chronic pain after TBI.