Gabbe Belinda J, Simpson Pam M, Lyons Ronan A, Polinder Suzanne, Rivara Frederick P, Ameratunga Shanthi, Derrett Sarah, Haagsma Juanita, Harrison James E
Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia Centre for Improvement of Population Health through E-records Research, Swansea University, Swansea, UK.
Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Inj Prev. 2015 Apr;21(e1):e120-6. doi: 10.1136/injuryprev-2013-041037. Epub 2014 Mar 26.
The application of disability weights by nature of injury is central to the calculation of disability-adjusted life years (DALYs). Such weights should represent injury diagnosis groups that demonstrate homogeneity in disability outcomes. Existing classifications have not used empirical data in their development to inform groups that are homogeneous for disability outcomes, limiting the capacity to make informed recommendations for best practice in measuring injury burden.
The Validating and Improving injury Burden Estimates (Injury-VIBES) Study includes pooled data from over 30 000 injured participants recruited to six cohort studies. The International Classification of Disease 10th Revision (ICD-10) diagnosis codes were mapped to existing injury burden study groupings and prediction models were developed to measure the capacity of the injury groupings and ICD-10 diagnoses to predict disability outcomes at 12 months. Models were adjusted for age, gender and data source and investigated for discrimination using area under the receiver operating characteristic curve (AUC) and calibration using Hosmer-Lemeshow statistics and calibration curves.
Discrimination and calibration of models varied depending on the outcome measured. Models using full four-character ICD-10 diagnosis codes, rather than groupings of codes, demonstrated the highest discrimination ranging from an AUC (95% CI) of 0.627 (0.618 to 0.635) for the pain or discomfort item of the EQ-5D to 0.847 (0.841 to 0.853) for the extended Glasgow Outcome Scale independent living outcome. However, gain over other groupings was marginal.
Prediction performance was best for measures of function such as independent living, mobility and self-care. The classifications were poorer predictors of anxiety/depression and pain/discomfort. There was no clearly superior classification.
根据损伤性质应用残疾权重是计算伤残调整生命年（DALYs）的核心。此类权重应代表在残疾结果方面具有同质性的损伤诊断组。现有分类在其制定过程中未使用实证数据来确定在残疾结果方面具有同质性的组，从而限制了就测量损伤负担的最佳实践提出明智建议的能力。
验证和改进损伤负担估计（Injury-VIBES）研究纳入了从六项队列研究中招募的30000多名受伤参与者的汇总数据。将国际疾病分类第10次修订本（ICD-10）诊断编码映射到现有的损伤负担研究分组，并开发预测模型以测量损伤分组和ICD-10诊断预测12个月时残疾结果的能力。对模型进行年龄、性别和数据来源调整，并使用受试者操作特征曲线下面积（AUC）研究辨别力，使用Hosmer-Lemeshow统计量和校准曲线研究校准情况。
模型的辨别力和校准情况因所测量的结果而异。使用完整的四字符ICD-10诊断编码而非编码分组的模型显示出最高的辨别力，范围从EQ-5D的疼痛或不适项目的AUC（95%CI）为0.627（0.618至0.635）到扩展格拉斯哥预后量表独立生活结果的AUC为0.847（0.841至0.853）。然而，相对于其他分组的优势微不足道。
对于诸如独立生活、活动能力和自我护理等功能测量，预测性能最佳。这些分类对焦虑/抑郁和疼痛/不适的预测效果较差。没有明显优越的分类。
