Back to Authors

Zafonte, Ross

https://orcid.org/0000-0002-1050-796X

Mayo Clinic

Harvard University

Citations 12

Prognostic models for predicting posttraumatic seizures during acute hospitalization, and at 1 and 2 years following traumatic brain injury
Ritter, Anne C., Wagner, Amy K. , Szaflarski, Jerzy P. , Brooks, Maria M. , Zafonte, Ross , Pugh, Mary Jo , Fabio, Anthony , Dreer, Laura E. , Bushnik, Tamara , Brown, Allen W. , Johnson‐Greene, Doug , Shea, Timothy, Krellman, Jason W. , Rosenthal, Joseph , Hammond, Flora M. , Walker, William C. , Dreer, Laura E

Epilepsia | July 19, 2016 | Volume: 57 | Issue: 9 | Pages: 1503-1514

10.1111/epi.13470 Get It

SummaryObjectivePosttraumatic 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.MethodsPrognostic 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).ResultsThe 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.SignificanceThe 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.
Predicting Institutionalization after Traumatic Brain Injury Inpatient Rehabilitation
Eum, Regina S., Seel, Ronald T. , Goldstein, Richard , Brown, Allen W. , Watanabe, Thomas K. , Zasler, Nathan D. , Zafonte, Ross , Glenn, Mel B., Roth, Elliot J.

Journal of Neurotrauma | September 15, 2014 | Volume: 32 | Issue: 4 | Pages: 280-286

10.1089/neu.2014.3351 Get It

Risk factors contributing to institutionalization after inpatient rehabilitation for people with traumatic brain injury (TBI) have not been well studied and need to be better understood to guide clinicians during rehabilitation. We aimed to develop a prognostic model that could be used at admission to inpatient rehabilitation facilities to predict discharge disposition. The model could be used to provide the interdisciplinary team with information regarding aspects of patients' functioning and/or their living situation that need particular attention during inpatient rehabilitation if institutionalization is to be avoided. The study population included 7219 patients with moderate-severe TBI in the Traumatic Brain Injury Model Systems (TBIMS) National Database enrolled from 2002–2012 who had not been institutionalized prior to injury. Based on institutionalization predictors in other populations, we hypothesized that among people who had lived at a private residence prior to injury, greater dependence in locomotion, bed-chair-wheelchair transfers, bladder and bowel continence, feeding, and comprehension at admission to inpatient rehabilitation programs would predict institutionalization at discharge. Logistic regression was used, with adjustment for demographic factors, proxy measures for TBI severity, and acute-care length-of-stay. C-statistic and predictiveness curves validated a five-variable model. Higher levels of independence in bladder management (adjusted odds ratio [OR], 0.88; 95% CI 0.83, 0.93), bed-chair-wheelchair transfers (OR, 0.81 [95% CI, 0.83–0.93]), and comprehension (OR, 0.78 [95% CI, 0.68, 0.89]) at admission were associated with lower risks of institutionalization on discharge. For every 10-year increment in age was associated with a 1.38 times higher risk for institutionalization (95% CI, 1.29, 1.48) and living alone was associated with a 2.34 times higher risk (95% CI, 1.86, 2.94). The c-statistic was 0.780. We conclude that this simple model can predict risk of institutionalization after inpatient rehabilitation for patients with TBI.