title: Predicting outcomes after traumatic brain injury: the development and validation of prognostic models based on admission characteristics.
abstract: BACKGROUND
  Early estimation of prognosis for the patient with traumatic brain injury is an important factor in making treatment decisions, resource allocation, classify patients, or communicating with family. We aimed to develop and validate practical prognostic models for mortality at 30 days and for 6 months unfavorable outcome after moderate and severe traumatic brain injury.
  
  
  METHODS
  Retrospectively collected data from our department were used to develop prognostic models for outcome. We developed four prognostic models based on admission predictors with logistic regression analysis. The performance of models was assessed with respect to discrimination and calibration. Discriminative ability was evaluated with C statistic, equal to the area under the receiver operating characteristic curve. Calibrative ability was assessed with the Hosmer-Lemeshow test (H-L test). The internal validity of models was evaluated with the bootstrap re-sampling technique. We validated three of the models in an external series of 203 patients that collected from another research center. Discrimination and calibration were further assessed to indicate the performance of the models in external patients.
  
  
  RESULTS
  Logistic regression showed that age, pupillary reactivity, motor Glasgow Coma Score, computed tomography characters, glucose, hemoglobin, D-dimer, serum calcium, and intracranial pressure were independent prognostic factors of outcome. The models discriminated well in the development patients (C statistic 0.709-0.939). We extensively validate three of the models. Internal validation showed no overoptimism in any of the models' predictive C statistics. External validity was much better (C statistic 0.844-0.902). Calibration was also good (H-L tests, p > 0.05). Computer-based calculator that based on prognostic models was developed for clinical use.
  
  
  CONCLUSIONS
  Our validated prognostic models have good performance and are generalizable to be used to predict outcome of new patients. We recommend the use of prognostic models to complement clinical decision making.
authors: Department of Neurosurgery, Shanghai Sixth People Hospital, Shanghai Jiaotong University, Shanghai, China.
authors: Fang
authors: F
authors: Yuan
authors: Jun
authors: J
authors: Ding
authors: Hao
authors: H
authors: Chen
authors: Yan
authors: Y
authors: Guo
authors: Gan
authors: G
authors: Wang
authors: Wen-Wei
authors: WW
authors: Gao
authors: Shi-Wen
authors: SW
authors: Chen
authors: Heng-Li
authors: HL
authors: Tian
mesh_terms: D000328:Adult; D000367:Age Factors; D001786:Blood Glucose / Q000032:analysis; D001930:Brain Injuries / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000401:mortality; D002118:Calcium / Q000097:blood; D005260:Female; D005338:Fibrin Fibrinogen Degradation Products / Q000032:analysis; D015600:Glasgow Coma Scale; D006454:Hemoglobins / Q000032:analysis; D006801:Humans; D007427:Intracranial Pressure; D016015:Logistic Models; D008297:Male; D008962:Models, Theoretical; D011237:Predictive Value of Tests; D011379:Prognosis; D012372:ROC Curve; D012025:Reflex, Pupillary; D015203:Reproducibility of Results; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed
chemical_list: D001786:Blood Glucose; D005338:Fibrin Fibrinogen Degradation Products; D006454:Hemoglobins; C036309:fibrin fragment D; D002118:Calcium