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Multidimensional Preinjury Health and 6-month Outcome After Traumatic Brain Injury in Older Adults Presenting With
Roy Tzemah-Shahar1, Yael Rosen Lang, Ava M Puccio
1Author Affiliations: Joseph Sagol Neuroscience Center, Sheba Medical Center, Ramat Gan, Israel (Tzemah-Shahar, Rosen Lang, and Gardner); Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania (Puccio, and Okonkwo); Department of Radiology, University of California San Francisco, San Francisco, California (Yuh); Department of Neurological Surgery, University of California San Francisco, San Francisco, California (Lombardi, Huie, Manley); School of Nursing, Community Health Systems, University of California San Francisco, San Francisco, California (Diaz Nelson); Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California (Boscardin, and Yaffe); Departments of Psychiatry and Neurology, University of California San Francisco, San Francisco, California (Yaffe); and Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania (Diaz Arrastia).
Objective:
To test the accuracy of existing traumatic brain injury (TBI) outcome prediction models in older adults with TBI (oaTBI), to determine the independent association of 5 different measures of preinjury health with 6-month outcome, and to investigate whether these preinjury health measures improve outcome prediction.
Setting:
Two level 1 trauma centers.
Participants:
A total of 112 adults aged ≥65 years who underwent head computed tomography after acute TBI (95% with Glasgow Coma Scale (GCS) score 13-15, 66% with acute intracranial trauma on head CT).
Design:
Prospective cohort study.
Main Measures:
Preinjury health was characterized using activities of daily living (ADL), Functional Activities Questionnaire (FAQ), Clinical Dementia Rating (CDR), Charlson Comorbidity Index (CCI), and Groningen Frailty Index (GFI). The primary outcome was poor recovery (Glasgow Outcome Scale-Extended <5: severe disability or death) at 6 months. We compared performance of CRASH and IMPACT models in predicting 6-month outcome. Each preinjury health measure was tested for independent association with outcome and incremental prognostic value when added to the best-performing model. Model accuracy was assessed using area under the curve (AUC).
Results:
Participants' mean ± SD age was 77.8 ± 7.9 years; 42% were women. The CRASH-basic model had the highest accuracy (AUC = 0.74, 95% CI = 0.64-0.83). Poor 6-month outcome was independently associated with preinjury cognitive impairment (CDR OR = 1.38, 95% CI = 1.07-1.76), impaired ADL (ADL OR = 2.45, 95% CI = 1.16-5.15), decreased cognitively mediated function (FAQ OR = 1.17, 95% CI = 1.06-1.29), and higher frailty (GFI OR = 1.30, 95% CI = 1.06-1.59), but not with comorbidities (CCI OR 1.00, 95% CI 0.76-1.32). No measure significantly improved CRASH-basic AUC (all P > 0.05).
Conclusions:
Among older adults with mainly mild TBI, preinjury frailty and cognitive-mediated function were independently associated with poor 6-month outcome, yet these preinjury measures did not significantly improve prediction accuracy. Instruments such as the FAQ and GFI capture clinically meaningful preinjury heterogeneity and may inform the development of more precise oaTBI prognostic models.
