Corrigan, John D.

Abstract Objective To conduct a scoping review of models of care for chronic disease management to identify potentially effective components for management of chronic traumatic brain injury (TBI). Methods Information sources : Systematic searches of three databases (Ovid MEDLINE, Embase, and Cochrane Database of Systematic Reviews) from January 2010 to May 2021. Eligibility criteria : Systematic reviews and meta‐analyses reporting on the effectiveness of the Chronic Care Model (CCM), collaborative/integrated care, and other chronic disease management models. Data : Target diseases, model components used ( n = 11), and six outcomes (disease‐specific, generic health‐related quality of life and functioning, adherence, health knowledge, patient satisfaction, and cost/health care use). Synthesis : Narrative synthesis, including proportion of reviews documenting outcome benefits. Results More than half (55%) of the 186 eligible reviews focused on collaborative/integrated care models, with 25% focusing on CCM and 20% focusing on other chronic disease management models. The most common health conditions were diabetes ( n = 22), depression ( n = 16), heart disease ( n = 12), aging ( n = 11), and kidney disease ( n = 8). Other single medical conditions were the focus of 22 reviews, multiple medical conditions of 59 reviews, and other or mixed mental health/behavioral conditions of 20 reviews. Some type of quality rating for individual studies was conducted in 126 (68%) of the reviews. Of reviews that assessed particular outcomes, 80% reported disease‐specific benefits, and 57% to 72% reported benefits for the other five types of outcomes. Outcomes did not differ by the model category, number or type of components, or target disease. Conclusions Although there is a paucity of evidence for TBI per se, care model components proven effective for other chronic diseases may be adaptable for chronic TBI care.

This study aims to characterize the patterns of functional change experienced between 5 and 10 years after moderate-severe traumatic brain injury (TBI). The study included TBI Model Systems national database participants ( N = 372) at six sites who experienced TBI, received inpatient rehabilitation, and were followed at 5 and 10 years post-TBI. Outcome measures included self- or proxy-reported Functional Independence Measure (FIM TM ) structured interview at 5 and 10 years post-TBI and domain change indices (DCIs) at 10 years to assess subjective change over the previous 5 years. When all seven FIM and subjective DCI subscales were considered together, 69% reported improvement in at least one subscale and 41% reported decline in at least one subscale; 51% reported more domains improved than declined, and 20% reported more domains declined than improved. Age at injury, post-traumatic amnesia duration, FIM, and depression and anxiety at year 5 were associated with FIM change and DCI measures. Although most persons with moderate-severe TBI do not experience widespread change from year 5 to 10 on individual FIM subscales or perceived domain-specific subscales, the vast majority do report change in one or more domains, with more improvement than decline and more change in subjective DCI than in FIM. Clinicians and researchers should be alert to the possibility of both positive and deleterious changes many years after TBI.

Medical conditions co-occurring with traumatic brain injury (TBI) are associated with outcomes, and comorbidity indices such as Charlson and Elixhauser are used in TBI research, but they are not TBI specific. The purpose of this research was to develop an index or indices of medical conditions, identified in acute care after moderate to severe TBI, that are associated with outcomes at rehabilitation discharge. Using the TBI Model Systems National Database, the International Classification of Diseases, Ninth Revision (ICD-9) and Tenth Revision (ICD-10) codes of 8988 participants were converted to Healthcare Cost and Utilization Project (HCUP) diagnostic categories. Poisson regression models were built predicting Disability Rating Scale and Functional Independence Measure Cognitive and Motor subscale scores from HCUP categories after controlling for demographic and injury characteristics. Unweighted, weighted, and anchored indices based on the outcome models predicted 7.5–14.3% of the variance in the observed outcomes. When the indices were applied to a new validation sample of 1613 cases, however, only 2.6–6.6% of the observed outcomes were predicted. Therefore, no models or indices were recommended for future use, but several study findings are highlighted suggesting the importance and the potential for future research in this area.

Glial fibrillary acidic protein (GFAP) is cleared by the Food and Drug Administration (FDA) to determine need for head computed tomography (CT) within 12 h after mild traumatic brain injury (TBI) (Glasgow Coma Score [GCS] 13–15); S100 calcium-binding protein B (S100B) serves this function in Europe. This phase 1 biomarker cohort analysis of the multi-center, observational Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study compares GFAP's diagnostic performance, measured on a rapid point-of-care platform, against protein S100B to predict intracranial abnormalities on CT within 24 h post-injury across the spectrum of TBI (GCS 3–15). Head CT scan performed in TBI subjects and blood was collected for all consenting subjects presenting to 18 United States level 1 trauma centers. Plasma was analyzed on a point-of-care device prototype assay for GFAP and serum was analyzed for S100B. In 1359 patients with TBI (GCS 3–15), mean (standard deviation [SD]) age = 40.1 (17.0) years; 68% were male. Plasma GFAP levels were significantly higher in CT+ TBI subjects (median = 1358 pg/mL, interquartile range [IQR]: 472–3803) than in CT- TBI subjects (median = 116 pg/mL, IQR: 26–397) or orthopedic trauma controls ( n = 122; median = 13 pg/mL, IQR: 7–20), p < 0.001. Serum S100B levels were likewise higher in CT+ TBI subjects (median = 0.17 μg/L, IQR: 0.09–0.38) than in CT- TBI subjects (median = 0.10 μg/L, IQR: 0.06–0.18), p < 0.001. Receiver operating characteristic curves were generated for prediction of intracranial injury on admission CT scan; area under the curve (AUC) for GFAP was significantly higher than for S100B in the same cohort (GFAP AUC – 0.85, 95% confidence interval [CI] 0.83–0.87; S100B AUC – 0.67, 95% CI 0.64-0.70; p < 0.001). GFAP, measured on a point-of-care platform prototype assay, has high discriminative ability to predict intracranial abnormalities on CT scan in patients with TBI across the full injury spectrum of GCS 3–15 through 24 h post-injury. GFAP substantially outperforms S100B.