Trauma Center, Lancaster General Health, Lancaster, PA 17602, USA.
J Trauma Acute Care Surg. 2012 Aug;73(2):326-31; discussion 331. doi: 10.1097/TA.0b013e31825a7758.
The Trauma and Injury Severity Score (TRISS) has been the approach to trauma outcome prediction during the past 20 years and has been adopted by many commercial registries. Unfortunately, its survival predictions are based upon coefficients that were derived from a data set collected in the 1980s and updated only once using a data set collected in the early 1990s. We hypothesized that the improvements in trauma care during the past 20 years would lead to improved survival in a large database, thus making the TRISS biased.
The TRISSs from the Pennsylvania statewide trauma registry (Collector, Digital Innovations) for the years 1990 to 2010. Observed-to-expected mortality ratios for each year of the study were calculated by taking the ratio of actual deaths (observed deaths, O) to the summation of the probability of mortality predicted by the TRISS taken over all patients (expected deaths, E). For reference, O/E ratio should approach 1 if the TRISS is well calibrated (i.e., has predictive accuracy).
There were 408,489 patients with complete data sufficient to calculate the TRISSs. There was a significant trend toward improved outcome (i.e., decreasing O/E ratio; nonparametric test of trend, p < 0.001) over time in both the total population and the blunt trauma subpopulation. In the penetrating trauma population, there was a trend toward improved outcome (decreasing O/E ratio), but it did not quite reach significance (nonparametric test of trend p = 0.073).
There is a steady trend toward improved O/E survival in the Pennsylvania database with each passing year, suggesting that the TRISS is drifting out of calibration. It is likely that improvements in care account for these changes. For the TRISS to remain an accurate outcome prediction model, new coefficients would need to be calculated periodically to keep up with trends in trauma care. This requirement for occasional updating is likely to be a requirement of any trauma prediction model, but because many other deficiencies in the TRISS have been reported, we think that rather than updating the TRISS, it would be more productive to replace the TRISS with a modern statistical model.
创伤和损伤严重度评分（TRISS）是过去 20 年来预测创伤结果的方法，已被许多商业登记处采用。不幸的是，它的生存预测是基于 20 世纪 80 年代收集的数据集中的系数得出的，并且仅使用 20 世纪 90 年代初收集的数据集中的一次更新。我们假设，在过去的 20 年中，创伤护理的改进将导致大型数据库中生存率的提高，从而使 TRISS 产生偏差。
我们对宾夕法尼亚州创伤登记处（Collector，Digital Innovations）的 TRISS 进行了研究，研究对象为 1990 年至 2010 年的数据。每年的观察到的与预期死亡率比值通过以下方法计算：实际死亡人数（观察到的死亡人数，O）与通过 TRISS 预测的所有患者死亡概率之和（预期死亡人数，E）的比值。作为参考，如果 TRISS 经过良好校准（即具有预测准确性），则 O/E 比值应该接近 1。
共有 408489 名患者具有足够完整的数据来计算 TRISS。在总人群和钝性创伤亚人群中，随着时间的推移，结果均呈明显改善趋势（即 O/E 比值降低；趋势检验非参数检验，p<0.001）。在穿透性创伤人群中，结果呈改善趋势（O/E 比值降低），但尚未达到显著水平（趋势检验非参数检验，p=0.073）。
随着时间的推移，宾夕法尼亚州数据库中的 O/E 生存率呈稳定改善趋势，这表明 TRISS 正在失去校准。这些变化很可能是由于护理的改善所致。为了使 TRISS 保持准确的预后预测模型，需要定期计算新的系数以跟上创伤护理的趋势。这种偶尔更新的要求可能是任何创伤预测模型的要求，但由于已经报道了 TRISS 的许多其他缺陷，我们认为，与其更新 TRISS，不如用现代统计模型替代 TRISS 更具成效。
