Performance of the IMPACT and CRASH prognostic models for traumatic brain injury in a contemporary multicenter cohort: a TRACK-TBI study

被引:0
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作者
Yue, John K. [1 ,2 ]
Lee, Young M. [1 ,2 ]
Sun, Xiaoying [3 ]
Essen, Thomas A. van [1 ,2 ,4 ]
Elguindy, Mahmoud M. [1 ,2 ]
Belton, Patrick J. [1 ,2 ]
Pisica, Dana [5 ]
Mikolic, Ana [5 ,6 ]
Deng, Hansen [7 ]
Kanter, John H. [1 ,2 ]
McCrea, Michael A. [8 ]
Bodien, Yelena G. [9 ,10 ]
Satris, Gabriela G. [1 ,2 ]
Wong, Justin C. [1 ,2 ]
Ambati, Vardhaan S. [1 ,2 ,12 ]
Grandhi, Ramesh [11 ]
Puccio, Ava M. [7 ]
Mukherjee, Pratik [2 ]
Valadka, Alex B. [13 ]
Tarapore, Phiroz E. [1 ,2 ]
Huang, Michael C. [1 ,2 ]
DiGiorgio, Anthony M. [1 ,2 ,14 ]
Markowitz, Amy J. [1 ,2 ]
Yuh, Esther L. [3 ,12 ]
Okonkwo, David O. [7 ,16 ]
Steyerberg, Ewout W. [15 ]
Lingsma, Hester F. [5 ]
Menon, David K. [16 ]
Maas, Andrew I. R. [17 ,18 ]
Jain, Sonia [3 ]
Manley, Geoffrey T. [1 ,2 ]
机构
[1] Univ Calif San Francisco, Dept Neurol Surg, San Francisco, CA USA
[2] Zuckerberg San Francisco Gen Hosp, Brain & Spinal Injury Ctr, San Francisco, CA USA
[3] Univ Calif San Diego, Biostat Res Ctr, Herbert Wertheim Sch Publ Hlth & Longev Sci, San Diego, CA USA
[4] Leiden Univ, Med Ctr, Univ Neurosurg Ctr Holland, Haaglanden Med Ctr, The Hague, Netherlands
[5] Erasmus MC, Dept Publ Hlth, Rotterdam, Netherlands
[6] Univ British Columbia, Dept Psychol, Vancouver, BC, Canada
[7] Univ Pittsburgh, Med Ctr, Dept Neurol Surg, Pittsburgh, PA USA
[8] Med Coll Wisconsin, Dept Neurol Surg, Milwaukee, WI USA
[9] Univ Utah, Hlth Sci Ctr, Dept Neurol Surg, Salt Lake City, UT USA
[10] Harvard Med Sch, Dept Neurol, Boston, MA USA
[11] Spaulding Rehabil Hosp, Dept Rehabil Med, Boston, MA USA
[12] Univ Calif San Francisco, Dept Radiol & Biomed Imaging, San Francisco, CA USA
[13] Univ Texas Southwestern Med Ctr, Dept Neurol Surg, Dallas, TX USA
[14] Univ Calif San Francisco, Inst Hlth Policy Studies, San Francisco, CA USA
[15] Leiden Univ, Dept Biomed Data Sci, Med Ctr, Leiden, Netherlands
[16] Univ Cambridge, Dept Med, Div Anesthesia, Cambridge, England
[17] Antwerp Univ Hosp, Dept Neurol Surg, Edegem, Belgium
[18] Univ Antwerp, Antwerp, Belgium
关键词
clinical prediction rules; Glasgow Outcome Scale; mortality; prognosis; statistical models; traumatic brain injury; COMMON DATA ELEMENTS; EXTERNAL VALIDATION; CLASSIFICATION; PREDICTION; TOOL;
D O I
暂无
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
OBJECTIVE The International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) and Corticosteroid Randomization After Significant Head Injury (CRASH) prognostic models for mortality and outcome after traumatic brain injury (TBI) were developed using data from 1984 to 2004. This study examined IMPACT and CRASH model performances in a contemporary cohort of US patients. METHODS The prospective 18-center Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) study (enrollment years 2014-2018) enrolled subjects aged >= 17 years who presented to level I trauma centers and received head CT within 24 hours of TBI. Data were extracted from the subjects who met the model criteria (for IMPACT, Glasgow Coma Scale [GCS] score 3-12 with 6-month Glasgow Outcome Scale-Extended [GOSE] data [n = 441]; for CRASH, GCS score 3-14 with 2-week mortality data and 6-month GOSE data [n = 831]). Analyses were conducted in the overall cohort and stratified on the basis of TBI severity (severe/moderate/mild TBI defined as GCS score 3-8/9-12/13-14), age (17-64 years or >= 65 years), and the 5 top enrolling sites. Unfavorable outcome was defined as GOSE score 1-4. Original IMPACT and CRASH model coefficients were applied, and model performances were assessed by calibration (intercept [< 0 indicated overprediction; > 0 indicated underprediction] and slope) and discrimination (c-statistic). RESULTS Overall, the IMPACT models overpredicted mortality (intercept -0.79 [95% CI -1.05 to -0.53], slope 1.37 [1.05-1.69]) and acceptably predicted unfavorable outcome (intercept 0.07 [-0.14 to 0.29], slope 1.19 [0.96-1.42]), with good discrimination (c-statistics 0.84 and 0.83, respectively). The CRASH models overpredicted mortality (intercept -1.06 [-1.36 to -0.75], slope 0.96 [0.79-1.14]) and unfavorable outcome (intercept -0.60 [-0.78 to -0.41], slope 1.20 [1.03-1.37]), with good discrimination (c-statistics 0.92 and 0.88, respectively). IMPACT overpredicted mortality and acceptably predicted unfavorable outcome in the severe and moderate TBI subgroups, with good discrimination (c-statistic >= 0.81). CRASH overpredicted mortality in the severe and moderate TBI subgroups and acceptably predicted mortality in the mild TBI subgroup, with good discrimination (c-statistic >= 0.86); unfavorable outcome was overpredicted in the severe and mild TBI subgroups with adequate discrimination (c-statistic >= 0.78), whereas calibration was nonlinear in the moderate TBI subgroup. In subjects >= 65 years of age, the models performed variably (IMPACT-mortality, intercept 0.28, slope 0.68, and c-statistic 0.68; CRASH-unfavorable outcome, intercept -0.97, slope 1.32, and c-statistic 0.88; nonlinear calibration for IMPACT-unfavorable outcome and CRASH-mortality). Model performance differences were observed across the top enrolling sites for mortality and unfavorable outcome. CONCLUSIONS The IMPACT and CRASH models adequately discriminated mortality and unfavorable outcome. Observed overestimations of mortality and unfavorable outcome underscore the need to update prognostic models to incorporate contemporary changes in TBI management and case-mix. Investigations to elucidate the relationships between increased survival, outcome, treatment intensity, and site-specific practices will be relevant to improve models in specific TBI subpopulations (e.g., older adults), which may benefit from the inclusion of blood-based biomarkers, neuroimaging features, and treatment data.
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页码:417 / 429
页数:13
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