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Abstract
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BACKGROUND: Accurate prognostic evaluation is a key factor in the clinical management of patients affected by severe acute brain injury (ABI) and helps planning focused therapies, better caregiver's support and allocation of resources. Aim of the study was to assess factors independently associated with both the short and long-term outcomes after rehabilitation in patients affected by ABI in the setting of a single Rehabilitation Unit specifically allocated to these patients.
METHODS AND FINDINGS: In all patients (567) with age ≥ 18 years discharged from the Unit in the period 2006/2015 demographic, etiologic, comorbidity indicators, and descriptors of the disability burden (at hospital admission and discharge) were evaluated as potential prognostic factors of both short-term (4 classes of disability status at discharge) and long-term (mortality) outcomes. A comprehensive analytical method was adopted to combine several tasks. Select the factors with a significant independent association with the outcome, assess the relative weights and the "stability" (by bootstrap resampling) of them and estimate the role of the prognostic models in the clinical framework considering "cost" and "benefits". The generalized ordered logistic model for ordinal dependent variables was used for the short-term outcome while the Cox proportional hazard model was used for the long-term outcome. The final short-term model identified 7 factors that independently account for 37% of the outcome variability as shown by pseudo R2 (pR2) = 0.37. The disability status descriptors show the strongest association since they account for more than 60% of the pR2, followed by age (14.8%), the presence of percutaneous endoscopic gastrostomy or nasogastric intubation (14.4%), a longer stay in the acute ward (5.9%) and concomitant coronary disease (1.3%). The final multivariable Cox model identified 4 factors that independently account for 52% of the outcome variability (R2 = 0.52). The disability extent and the disability recovered lead the long-term mortality since they account for the 53% of the global R2. The relevant effect of age (42%) is appreciable only after 2 years given the significant interaction with time. A longer stay in the acute ward explains the remaining fraction (5%). Considering 'cost and benefits', the decision curve analysis shows that the clinical benefit achieved by using both prognostic models is greater than the other possible action strategies, namely 'treat all' and 'treat none. Several less obvious characteristics of the prognostic models are appreciated by integrating the results of multiple analytical methods.
CONCLUSION: The comprehensive analytical tool aimed to integrate statistical significance, weight, "stability" and clinical "net" benefit, gives back a prognostic framework explaining a relevant portion of both outcomes' variability in which the strong association of the disability status with both outcomes is comparable to and followed by a time modulated role of age. Our data do not support a differentiated association of traumatic vs non-traumatic etiology. The results encourage the use of integrated approach to analyze cohort data.
Language: en |