Tribuddharat Sirirat, Sathitkarnmanee Thepakorn, Sappayanon Pavit
Department of Anesthesiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand.
Department of Anesthesia, Khon Kaen Hospital, Khon Kaen, Thailand.
Anesthesiol Res Pract. 2019 Sep 23;2019:6760470. doi: 10.1155/2019/6760470. eCollection 2019.
Emergency surgery has poor outcomes with high mortality. Numerous studies have reported the risk factors for postoperative death in order to stratify risk and improve perioperative care; nevertheless, a predictive model based upon these risk factors is lacking.
We aimed to identify the risk factors of postoperative mortality and to construct a new model for predicting mortality and improving patient care.
We included adult patients undergoing emergency surgery at Srinagarind Hospital between January 2012 and December 2014. The patients were randomized: 80% to the Training group for model construction and 20% to the Validation group. Patient data were extracted from medical records and then analyzed using univariate and multivariate logistic regression.
We recruited 758 patients, and the mortality rate was 14.5%. The Training group comprised 596 patients, and the Validation group comprised 162. Based upon a multivariate analysis in the Training group, we constructed a model to predict postoperative mortality-an Emergency Surgery Mortality (ESM) score based on the coefficient of each risk factor from the multivariate analysis. The ESM score comprised 7 risk factors, i.e., coagulopathy, ASA class 5, bicarbonate <15 mEq/L, heart rate >100/min, systolic blood pressure <90 mmHg, renal comorbidity, and general surgery, for a total score of 11. An ESM score ≥4 was predictive of postoperative mortality with an AUC of 0.83. The respective sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, positive predictive value, negative predictive value, and accuracy for an ESM score ≥4 predictive of postoperative mortality was 70.2%, 94.9%, 13.8, 0.3, 69.4%, 95.1%, and 91.4%. The performance of the ESM score in the Validation group was comparable.
An ESM score comprises 7 risk factors for a total score of 11. An ESM score ≥4 is predictive of postoperative mortality with a high AUC (0.83), sensitivity (70.2%), and specificity (94.9%). Four risk factors are preoperatively manageable for decreasing the probability of postoperative mortality and improving quality of patient care.
急诊手术预后较差,死亡率较高。众多研究报告了术后死亡的风险因素,以便对风险进行分层并改善围手术期护理;然而,基于这些风险因素的预测模型尚不存在。
我们旨在确定术后死亡的风险因素,并构建一个新的模型来预测死亡率并改善患者护理。
我们纳入了2012年1月至2014年12月在诗里拉吉医院接受急诊手术的成年患者。患者被随机分组:80%进入模型构建训练组,20%进入验证组。从病历中提取患者数据,然后使用单因素和多因素逻辑回归进行分析。
我们招募了758名患者,死亡率为14.5%。训练组包括596名患者,验证组包括162名患者。基于训练组的多因素分析,我们构建了一个预测术后死亡率的模型——急诊手术死亡率(ESM)评分,该评分基于多因素分析中每个风险因素的系数。ESM评分包括7个风险因素,即凝血功能障碍、美国麻醉医师协会(ASA)5级、碳酸氢盐<15 mEq/L、心率>100次/分钟、收缩压<90 mmHg、肾脏合并症和普通外科手术,总分11分。ESM评分≥4可预测术后死亡,曲线下面积(AUC)为0.83。ESM评分≥4预测术后死亡的敏感性、特异性、阳性似然比、阴性似然比、阳性预测值、阴性预测值和准确性分别为70.2%、94.9%、13.8、0.3、69.4%、95.1%和91.4%。ESM评分在验证组中的表现相当。
ESM评分包括7个风险因素,总分11分。ESM评分≥4可预测术后死亡,AUC较高(0.83),敏感性(70.2%)和特异性(94.9%)较高。四个风险因素在术前可进行管理,以降低术后死亡概率并提高患者护理质量。