Evaluation of simplified acute physiology score 3 performance: a systematic review of external validation studies
Evaluation of simplified acute physiology score 3 performance: a systematic review of external validation studies
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DOI：
10.1186/cc13911
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发表时间：
2014-01-01
期刊：
影响因子：
15.1
通讯作者：
Moreno, Rui
中科院分区：
文献类型：
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作者：
Nassar Junior, Antonio Paulo;Sa Malbouisson, Luiz Marcelo;Moreno, Rui
简介：简化急性生理学评分3(SAPS 3)是根据全球数据开发的第一个危重病预后模型。我们旨在系统地回顾评估SAPS 3通用模型和定制模型预测ICU成年患者住院死亡率的预后性能的研究。方法：检索Medline、Lilacs、SciELO和Google Scholar，以确定评估通用和定制SAPS 3方程的校正和区分的研究。此外，我们决定评估试验规模(纳入患者数量)与SAPS3模型的Hosmer-Lemesshow(H-L)统计值之间的相关性。结果：共纳入28项研究。在这些研究中，11项研究(42.8%)没有发现SAPS 3一般方程有统计学意义的错误校准。纳入的患者数量与较高的H-L统计量呈正相关，即模型存在显著的误校准(r=0.747，P<；0.001)。在19项研究中，有9项针对主要地理区域的定制方程与完美校准没有统计学上的显著差异。5项研究(17.9%)发展了区域定制，在所有这些研究中，这一新模型在统计上与针对其人群的完美校准没有什么不同。有24项研究(85.7%)的判别力至少非常好。结论：SAPS3一般方程在统计学上显著偏离完美校正的情况在验证性研究中很常见，并与更大规模的研究相关，这是应该预料的，因为H-L统计量(C和H)强烈依赖于样本量。这一发现在评估主要的地理定制方程时也存在。另一方面，本地定制改进了SAPS 3校准。歧视几乎总是非常好或很好，这为需要精确的本地估计时的本地定制提供了极好的前景。
Introduction: Simplified Acute Physiology Score 3 (SAPS 3) was the first critical care prognostic model developed from worldwide data. We aimed to systematically review studies that assessed the prognostic performance of SAPS 3 general and customized models for predicting hospital mortality in adult patients admitted to the ICU.Methods: Medline, Lilacs, Scielo and Google Scholar were searched to identify studies which assessed calibration and discrimination of general and customized SAPS 3 equations. Additionally, we decided to evaluate the correlation between trial size (number of included patients) and the Hosmer-Lemeshow (H-L) statistics value of the SAPS 3 models.Results: A total of 28 studies were included. Of these, 11 studies (42.8%) did not find statistically significant mis-calibration for the SAPS 3 general equation. There was a positive correlation between number of included patients and higher H-L statistics, that is, a statistically significant mis-calibration of the model (r = 0.747, P < 0.001). Customized equations for major geographic regions did not have statistically significant departures from perfect calibration in 9 of 19 studies. Five studies (17.9%) developed a regional customization and in all of them this new model was not statistically different from a perfect calibration for their populations. Discrimination was at least very good in 24 studies (85.7%).Conclusions: Statistically significant departure from perfect calibration for the SAPS 3 general equation was common in validation studies and was correlated with larger studies, as should be expected, since H-L statistics (both C and H) are strongly dependent on sample size This finding was also present when major geographic customized equations were evaluated. Local customizations, on the other hand, improved SAPS 3 calibration. Discrimination was almost always very good or excellent, which gives excellent perspectives for local customization when a precise local estimate is needed.