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  • Predicting Posttraumatic Hydrocephalus: Derivation and Validation of a Risk Scoring System Based on Clinical Characteristics

    Final Number:
    188

    Authors:
    Hao Chen MD

    Study Design:
    Other

    Subject Category:

    Meeting: Congress of Neurological Surgeons 2017 Annual Meeting

    Introduction: Posttraumatic hydrocephalus (PTH) is a common complication of traumatic brain injury (TBI) and often has a high risk of clinical deterioration and worse outcomes. The incidence and risk factors for the development of PTH after decompressive craniectomy (DC) has been assessed in previous studies, but rare studies identify patients with higher risk for PTH among all TBI patients. This study aimed to develop and validate a risk scoring system to predict PTH after TBI.

    Methods: Demographics, injury severity, duration of coma, radiologic findings, and DC were evaluated to determine the independent predictors of PTH during hospitalization until 6 months following TBI through logistic regression analysis. A risk stratification system was created by assigning a number of points for each predictor and validated both internally and externally. The model accuracy was assessed by the area under the receiver operating characteristic curve (AUC).

    Results: Of 526 patients in the derivation cohort, 57 (10.84%) developed PTH during 6 months follow up. Age > 50 (Odd ratio [OR]=1.91, 95% confidence interval [CI] 1.09–3.75, 4 points), duration of coma = 1 w (OR=5.68, 95% CI 2.57–13.47, 9 points), Fisher grade III (OR=2.19, 95% CI 1.24–4.36, 5 points) or IV (OR=3.87, 95% CI 1.93–8.43, 7 points), bilateral DC (OR=6.13, 95% CI 2.82–18.14, 9 points), and extra herniation after DC (OR=2.36, 95% CI 1.46–4.92, 5 points) were independently associated with PTH. Rates of PTH for the low- (0-12 points), intermediate- (13-22 points) and high-risk (23-34 points) groups were 1.16%, 35.19% and 78.57% (p < 0.0001). The corresponding rates in the validation cohort, where 17/175 (9.71%) developed PTH, were 1.35%, 37.50% and 81.82% (p < 0.0001). The risk score model exhibited good-excellent discrimination in both cohorts, with AUC of 0.839 versus 0.894 (derivation versus validation) and good calibration (Hosmer-Lemshow p = 0.56 versus 0.68).

    Conclusions: A risk scoring system based on clinical characteristics accurately predicted PTH. This model will be useful to identify patients at high risk for PTH who may be candidates for preventive interventions, and to improve their outcomes.

    Patient Care: Our scoring system may support clinicians in their early prognosis and management of PTH. Patients with a higher risk could potentially benefit from the most aggressive therapies, including promptly repeating a CT scan, early drainage of bloody CSF, and cranioplasty performed as early as possible for patients undergoing DC, which is believed to be effective and capable to reduce overall cost of care by eliminating the need for additional hospitalization.

    Learning Objectives: We hope this study will provide useful clinical decision-making support in the management of TBI.

    References:

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