Department of Orthopaedic Surgery, William Beaumont Army Medical Center, Texas Tech University Health Sciences Center, 5005 N. Piedras St, El Paso, TX 79920, USA.
Spine J. 2013 Dec;13(12):1766-73. doi: 10.1016/j.spinee.2013.03.024. Epub 2013 Apr 23.
Predictors of complications and mortality after spine trauma are underexplored. At present, no study exists capable of predicting the impact of demographic factors, injury-specific predictors, race, ethnicity, and insurance status on morbidity and mortality after spine trauma.
This study endeavored to describe the impact of patient demographics, comorbidities, injury-specific factors, race/ethnicity, and insurance status on outcomes after spinal trauma using the National Sample Program (NSP) of the National Trauma Data Bank (NTDB).
The weighted sample of 75,351 incidents of spine trauma in the NTDB was used to develop a predictive model for important factors associated with mortality, postinjury complications, length of hospital stay, intensive care unit (ICU) days, and time on a ventilator.
A weighted sample of 75,351 incidents of spine trauma as contained in the NTDB.
Mortality, postinjury complications, length of hospital stay, ICU days, and time on a ventilator as reported in the NTDB.
The 2008 NSP of the NTDB was queried to identify patients sustaining spine trauma. Patient demographics, race/ethnicity, insurance status, comorbidities, injury-specific factors, and outcomes were recorded, and a national estimate model was derived. Unadjusted differences in baseline characteristics between racial/ethnic groups and insurance status were evaluated using the t test for continuous variables and Wald chi-square analysis for categorical variables with Bonferroni correction for multiple comparisons. Weighted logistic regression was performed for categorical variables (mortality and risk of one or more complications), and weighted multiple linear regression analysis was used for continuous variables (length of hospital stay, ICU days, and ventilator time). Initial determinations were checked against a sensitivity analysis using imputed data.
The weighted sample contained 75,351 incidents of spine trauma. The average age was 45.8 years. Sixty-four percent of the population was male, 9% was black/African American, 38% possessed private/commercial insurance, and 12.5% lacked insurance. The mortality rate was 6% and 16% sustained complications. Increased age, male gender, Injury Severity Score (ISS), and blood pressure at presentation were significant predictors of mortality, whereas age, male gender, other mechanism of injury, ISS, and blood pressure at presentation influenced the risk of one or more complications. Nonwhite and black/African American race increased risk of mortality, and lack of insurance increased mortality and decreased the number of hospital days, ICU days, and ventilator time.
This is the first study to postulate predictors of morbidity and mortality after spinal trauma in a national model. Race/ethnicity and insurance status appear to be associated with greater risk of mortality after spine trauma.
脊柱创伤后并发症和死亡率的预测因素尚未得到充分研究。目前，尚无研究能够预测人口统计学因素、损伤特异性预测因素、种族、族裔和保险状况对脊柱创伤后发病率和死亡率的影响。
本研究旨在使用国家创伤数据库（NTDB）的国家样本计划（NSP）描述患者人口统计学、合并症、损伤特异性因素、种族/族裔和保险状况对脊柱创伤后结局的影响。
使用 NTDB 中包含的 75351 例脊柱创伤的加权样本，建立一个预测模型，用于预测与死亡率、创伤后并发症、住院时间、重症监护病房（ICU）天数和呼吸机使用时间相关的重要因素。
来自 NTDB 的 75351 例脊柱创伤的加权样本。
NTDB 中报告的死亡率、创伤后并发症、住院时间、ICU 天数和呼吸机使用时间。
查询 2008 年 NSP 的 NTDB，以确定发生脊柱创伤的患者。记录患者的人口统计学、种族/族裔、保险状况、合并症、损伤特异性因素和结局，并得出全国估计模型。使用 t 检验比较连续变量，使用 Wald 卡方分析比较分类变量，并使用 Bonferroni 校正进行多次比较，评估不同种族/族裔和保险状况之间的基线特征的无调整差异。使用加权逻辑回归进行分类变量（死亡率和一个或多个并发症的风险），使用加权多元线性回归分析连续变量（住院时间、ICU 天数和呼吸机时间）。使用插补数据进行敏感性分析以检查初始确定结果。
加权样本包含 75351 例脊柱创伤。平均年龄为 45.8 岁。64%的人群为男性，9%为黑人/非裔美国人，38%拥有私人/商业保险，12.5%没有保险。死亡率为 6%，16%发生并发症。年龄增加、男性、损伤严重程度评分（ISS）和就诊时的血压是死亡率的显著预测因素，而年龄、男性、其他损伤机制、ISS 和就诊时的血压影响一个或多个并发症的风险。非白人及黑人/非裔美国人种族增加了死亡率风险，而没有保险则增加了死亡率，并减少了住院天数、ICU 天数和呼吸机使用时间。
这是第一项在全国模型中提出脊柱创伤后发病率和死亡率预测因素的研究。种族/族裔和保险状况似乎与脊柱创伤后更高的死亡率风险相关。
