Comprehensive predictions of outcome in closed head-injured patients. The development of prognostic equations

Influence of early variables in traumatic brain injury on functional independence measure scores and rehabilitation length of stay and charges

OBJECTIVE

To determine the relationship between early variables (initial Glasgow Coma Scale [GCS] scores, computed tomography [CT] findings, presence of skeletal trauma, age, length of acute hospitalization) and outcome variables (Functional Independence Measure [FIM] scores, rehabilitation length of stay [LOS], rehabilitation charges) in traumatic brain injury (TBI).

DESIGN

Inception cohort.

SETTING

University tertiary care rehabilitation center.

PATIENTS

91 patients with TBI.

INTERVENTIONS

Inpatient rehabilitation.

MAIN OUTCOME MEASURES

FIM, rehabilitation LOS, and rehabilitation charges.

RESULTS

Patients in the severely impaired (GCS = 3 to 7) group showed significantly lower (p = .01) mean admission and discharge motor scores (21.26, 39.83) than patients in the mildly impaired (GCS = 13 to 15) group (38.86, 55.29). Cognitive scores were also significantly lower (p < .01) in the severely impaired group on admission (26.73 vs 54.14) and discharge (42.28 vs 66.48). These findings continued to be statistically significant (p < .01) after regression analysis accounted for the other early variables previously listed. Regression analysis also illustrated that longer acute hospitalization LOS was independently associated with significantly lower admission motor (p < .01) and cognitive (p = .05) scores, and significantly higher (p = .01) rehabilitation charges. Patients with CT findings of intracranial bleed with skull fracture had longer total LOS (70.88 vs 43.08 days; p < .05), rehabilitation LOS (30.01 vs 19.68 days; p < .10), and higher rehabilitation charges ($43,346 vs $25,780; p < .05). Paradoxically, those patients in a motor vehicle crash with an extremity bone fracture had significantly higher (p = .002; p = .04 after regression analysis) FIM cognitive scores on admission (48.30 vs 27.28) and discharge (64.74 vs 45.78) than those without a fracture. Finally, data available on rehabilitation admission were used to predict discharge outcomes. The percentage of explained variance for each outcome variable is as follows: discharge FIM motor score, 69.5%; discharge FIM cognitive score, 71.2%; rehabilitation LOS, 54.1%; rehabilitation charges, 61.1%. The most powerful predictor of LOS and charges was the admission FIM motor score (p < .001), followed by CT findings (p = .02) and age (p = .04).

CONCLUSION

Information readily available on rehabilitation admission, particularly the FIM motor score, may be useful in predicting discharge FIM scores as well as utilization of medical rehabilitation resources. Earlier transfer to rehabilitation may result in higher functional status and lower rehabilitation charges, as well as lower acute hospitalization charges. The presence of extremity fractures encountered during a motor vehicle crash is associated with a more favorable outcome in TBI as evidenced by higher discharge FIM cognitive scores.

Classification and regression trees (CART) for prediction of function at 1 year following head trauma

A cohort of 514 hospitalized head-injury survivors was identified based on their injury and 448 (87%) of them were followed for 1 year. Comprehensive neurobehavioral testing was performed 1 month and 1 year after injury. The authors developed predictions of six neuropsychological and two psychosocial outcomes 1 year after head injury. Prediction trees are presented for verbal IQ, Halstead's Impairment Index, and work status at 1 year. Early predictors of neurobehavioral outcome in survivors are similar to previously reported predictors of mortality. Extent (both depth and length) of coma and age are the medical and demographic variables most predictive of late outcome. Adding 1-month scores substantially improves prediction of neuropsychological variables. The classification and regression tree is a useful technique for predicting long-term outcome in patients with head injury. The trees are simple enough to be used in a clinical setting and, especially with 1-month scores, predictions are accurate enough for clinical utility.

Status of quantitative EEG (QEEG) in clinical practice, 1994

Clinical quantitative EEG (qEEG) is a complex specialty that may include not only standard EEG but also digital ("paperless") EEG, topographic mapping, spectral analysis, spectral coherence, long latency and event related potentials (EP), significance probability mapping (SPM), dipole source localization methodology (DLM), and discriminant function analysis. There are three basic clinical uses: non-specific detection of organicity/encephalopathy, specific categorization of disease or clinical condition, and epileptic source localization. Extreme variations exist in the competency of laboratories practicing clinical qEEG; universally agreed upon standards of practice have not been established but there are a number of efforts to do so. As expected, the clinical value of qEEG to patients varies similarly. Criticisms of qEEG have now been answered: Color displays need not be deceptive. Statistical "capitalization upon chance" can be easily avoided. By training and with newer analytic procedures, artifacts can be recognized and often removed. Data based upon spectral analysis and EP can reliably classify clinical conditions thereby demonstrating a greater sensitivity to EEG/EP data than possible by conventional visual inspection. QEEG is clearly of clinical value when performed in concert with standard EEG and analyzed by clinicians with demonstrated competency in standard EEG followed by specialized training and demonstrated competency in qEEG. QEEG is not a simple substitute for conventional EEG and cannot be seen as a substitute for clinical competence. Although continuing to develop, qEEG technology has matured sufficiently and is now well established. Concerns regarding its clinical use have primarily resulted from its misapplication and misinterpretation stemming, largely, from inadequate personnel training and expertise.

The management of cerebral perfusion pressure and intracranial pressure after severe head injury

Neurosurgical intervention attempts to minimize secondary central nervous system injury after severe head injury through the evacuation of mass lesions with subsequent manipulation of cerebral perfusion pressure and intracranial pressure. The normal brain couples blood flow to metabolic demand through autoregulation of the cerebral vasculature. After severe head trauma and its attendant increase in intracranial pressure, marked alterations in cerebral blood flow and perfusion may occur. Currently, intervention is based on maintenance of coronary perfusion pressure and aggressive management of intracranial pressure. Both may be impacted by manipulation of ventilation, systemic blood pressure and volume status, administration of osmotic diuretics, and head elevation. Such therapy in the patient with severe head injury attempts to maintain coronary perfusion pressure and adequate oxygen delivery in a damaged central nervous system with altered hemodynamics and raised intracranial pressure.