Department of Biobehavioral Nursing and Health Systems, Harborview Injury Prevention and Research Center, The University of Washington School of Nursing, Seattle, WA, USA.
Ann Surg. 2010 Aug;252(2):370-5. doi: 10.1097/SLA.0b013e3181df03d6.
The aim of this study was to develop and validate a comorbidity index to predict the risk of mortality associated with chronic health conditions following a traumatic injury.
Currently available comorbidity adjustment tools do not account for certain chronic conditions, which may influence outcome following traumatic injury or they have not been fully validated for trauma. Controlling for comorbidity in trauma patients is becoming increasingly important as the population ages and elderly patients are more active, as well as to adjust for bias in trauma mortality studies.
Cohort study using data from the National Study on the Costs and Outcome of Trauma. Subject pool (N = 4644/Weighted Number = 14,069) was randomly divided in half; the first half of subjects was used to derive the risk scale, the second to validate the instrument. To construct the Mortality Risk Score for Trauma (MoRT), univariate analysis and odds ratios were performed to determine relative risk of mortality at hospital discharge comparing those persons with a comorbid condition to those without. Conditions significantly associated with mortality (P < 0.05) were included in the multivariate model. The variables in the final model were used to build the MoRT. The predictive ability of the MoRT and the Charlson Comorbidity Index (CCI) for discharge and 1-year mortality were estimated using the c-statistic in the validation sample.
Six comorbidity factors were independently associated with the risk of mortality and formed the basis for the MoRT: severe liver disease, myocardial infarction, cerebrovascular disease, cardiac arrhythmias, dementia, and depression. The MoRT had a similar overall discrimination as the CCI for mortality at hospital discharge in injured adults (c-statistic: 0.56 vs. 0.56) although neither by itself performed well. The addition of age and gender improved the predictive ability of the MoRT (0.59; 95% CI: 0.56, 0.62) and the CCI (0.59; 0.56, 0.62). Similar results were seen at 1-year postinjury. The further addition of Injury Severity Score significantly improved the predictive ability of the MoRT (0.77, 95% CI: 0.74, 0.79) and the CCI (0.77, 95% CI: 0.75, 0.80).
The MoRTs primary advantage over current instruments is its parsimony, containing only 6 items. In the present study, the comorbid conditions found to be predictive of mortality had some overlap with the CCI, but this study identified 2 novel predictors: cardiac arrhythmias and depression. Inclusion and reporting of these items within trauma registries would therefore be an important step to allow further validation and use of the MoRT.
本研究旨在开发和验证一种合并症指数,以预测创伤后与慢性健康状况相关的死亡风险。
目前可用的合并症调整工具没有考虑到某些慢性疾病,这些疾病可能会影响创伤后的结果,或者它们尚未针对创伤进行充分验证。随着人口老龄化和老年患者更加活跃,以及为了调整创伤死亡率研究中的偏差,对创伤患者进行合并症控制变得越来越重要。
使用国家创伤成本和结果研究的数据进行队列研究。受试者池(N=4644/加权人数=14069)随机分为两半;前一半用于推导风险评分,后一半用于验证该工具。为了构建创伤死亡率风险评分(MoRT),对单变量分析和优势比进行了分析,以确定比较有合并症的患者与无合并症的患者在出院时的死亡率的相对风险。与死亡率显著相关的(P<0.05)的条件被纳入多变量模型。最终模型中的变量用于构建 MoRT。在验证样本中,使用 C 统计量估计 MoRT 和 Charlson 合并症指数(CCI)对出院和 1 年死亡率的预测能力。
有 6 个合并症因素与死亡率的风险独立相关,并构成 MoRT 的基础:严重肝病、心肌梗死、脑血管疾病、心律失常、痴呆和抑郁症。MoRT 在受伤成年人的出院时死亡率方面具有与 CCI 相似的整体判别能力(C 统计量:0.56 与 0.56),尽管两者本身都表现不佳。年龄和性别增加了 MoRT(0.59;95%CI:0.56,0.62)和 CCI(0.59;95%CI:0.56,0.62)的预测能力。在受伤后 1 年也观察到类似的结果。进一步增加损伤严重程度评分显著提高了 MoRT(0.77,95%CI:0.74,0.79)和 CCI(0.77,95%CI:0.75,0.80)的预测能力。
MoRT 相对于现有工具的主要优势在于其简洁性,仅包含 6 个项目。在本研究中,发现与死亡率相关的合并症与 CCI 有一定重叠,但本研究确定了 2 个新的预测因子:心律失常和抑郁症。因此,在创伤登记处纳入和报告这些项目将是允许进一步验证和使用 MoRT 的重要一步。