School of Veterinary Medicine, University of São Paulo, São Paulo, Brazil.
School of Zootechnics and Food Engineering, University of São Paulo, Pirassununga, Brazil.
Vet Rec. 2021 Sep;189(5):e136. doi: 10.1002/vetr.136. Epub 2021 Feb 19.
Scoring models are useful tools that guide the attending clinician in gauging the severity of disease evolution and in evaluating the efficacy of treatment. There are few tools available with this purpose for the non-human patient, including horses. We aimed (i) to adapt the simplified acute physiology score 3 (SAPS-3) model for the equine species, reaching a margin of accuracy greater than 75% in the calculation of the probability of survival/death and (ii) to build a decision tree that helps the attending veterinarian in assessment of the clinical evolution of the equine patient.
From an initial pool of 5568 medical records from University-based Veterinary Hospitals, a final cohort of 1000 was further mined manually for data extraction. A set of 19 variables were evaluated and tested by five machine learning data mining algorithms.
The final scoring model, named EqSAPS for equine simplified acute physiology score, reached 91.83% of correct estimates (post hoc) for probability of death within 24 hours upon hospitalization. The area under receiver operating characteristic curve for outcome 'death' was 0.742, while for 'survival' was 0.652. The final decision tree was able to refine prognosis of patients whose EqSAPS score suggested 'death'.
EqSAPS is a useful tool to gauge the severity of the clinical presentation of the equine patient.
评分模型是一种有用的工具,可以帮助主治临床医生评估疾病演变的严重程度和评估治疗效果。针对非人类患者(包括马),可用的此类工具很少。我们的目的是:(i)为马科动物改编简化急性生理学评分 3(SAPS-3)模型,使计算生存率/死亡率的准确率超过 75%;(ii)构建决策树,帮助主治兽医评估马科动物患者的临床演变。
从基于大学的兽医医院的 5568 份医疗记录的初始库中,进一步手动挖掘出 1000 份最终队列进行数据提取。评估并测试了一套 19 个变量,这些变量由五种机器学习数据挖掘算法进行评估和测试。
最终的评分模型命名为 EqSAPS(马简化急性生理学评分),在住院后 24 小时内死亡概率的正确估计(事后)达到 91.83%。用于结果“死亡”的接收者操作特征曲线下面积为 0.742,用于“存活”的面积为 0.652。最终的决策树能够细化 EqSAPS 评分提示“死亡”的患者的预后。
EqSAPS 是一种评估马科动物患者临床表现严重程度的有用工具。