Medical conditions co-occurring with traumatic brain injury (TBI) are associated with outcomes, and comorbidity indices such as Charlson and Elixhauser are used in TBI research, but they are not TBI specific. The purpose of this research was to develop an index or indices of medical conditions, identified in acute care after moderate to severe TBI, that are associated with outcomes at rehabilitation discharge. Using the TBI Model Systems National Database, the International Classification of Diseases, Ninth Revision (ICD-9) and Tenth Revision (ICD-10) codes of 8988 participants were converted to Healthcare Cost and Utilization Project (HCUP) diagnostic categories. Poisson regression models were built predicting Disability Rating Scale and Functional Independence Measure Cognitive and Motor subscale scores from HCUP categories after controlling for demographic and injury characteristics. Unweighted, weighted, and anchored indices based on the outcome models predicted 7.5–14.3% of the variance in the observed outcomes. When the indices were applied to a new validation sample of 1613 cases, however, only 2.6–6.6% of the observed outcomes were predicted. Therefore, no models or indices were recommended for future use, but several study findings are highlighted suggesting the importance and the potential for future research in this area.

中文翻译：

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制定与中度至重度创伤性脑损伤后结果相关的医疗状况指数

与创伤性脑损伤 (TBI) 共同发生的医疗状况与结果相关，并且在 TBI 研究中使用了 Charlson 和 Elixhauser 等合并症指数，但它们不是 TBI 特异性的。本研究的目的是制定一个或多个医疗状况指数，在中度至重度 TBI 后的急性护理中确定，这些指数与康复出院的结果相关。使用 TBI 模型系统国家数据库、国际疾病分类、8988 名参与者的第九版 (ICD-9) 和第十版 (ICD-10) 代码被转换为医疗保健成本和利用项目 (HCUP) 诊断类别。在控制人口统计和损伤特征后，建立泊松回归模型来预测 HCUP 类别的残疾评定量表和功能独立测量认知和运动分量表得分。基于结果模型的未加权、加权和锚定指数预测了观察结果方差的 7.5-14.3%。然而，当这些指数应用于 1613 个病例的新验证样本时，仅预测了 2.6-6.6% 的观察结果。因此，没有建议将来使用模型或指数，但强调了一些研究结果，表明该领域未来研究的重要性和潜力。