Ottawa Hospital Research Institute, The Ottawa Hospital, Ottawa, Ontario.
University of Ottawa, School of Epidemiology, Epidemiology and Public Health, Ottawa, Ontario.
West J Emerg Med. 2020 Feb 24;21(2):343-347. doi: 10.5811/westjem.2020.1.45420.
There are currently no robust tools available for risk stratification of emergency department (ED) patients with lower gastrointestinal bleed (LGIB). Our aim was to identify risk factors and develop a preliminary model to predict 30-day serious adverse events among ED LGIB patients.
We conducted a health records review including adult ED patients with acute LGIB. We used a composite outcome of 30-day all-cause death, recurrent LGIB, need for intervention to control the bleeding, and severe adverse events resulting in intensive care unit admission. One researcher collected data for variables and a second researcher independently collected 10% of the variables for inter-observer reliability. We used backward multivariable logistic regression analysis and SELECTION=SCORE option to create a preliminary risk-stratification tool. We assessed the diagnostic accuracy of the final model.
Of 372 patients, 48 experienced an adverse outcome. We found that age ≥75 years, hemoglobin ≤100 g/L, international normalized ratio ≥2.0, ongoing bleed in the ED, and a medical history of colorectal polyps were statistically significant predictors in the multivariable regression analysis. The area under the curve (AUC) for the model was 0.83 (95% confidence interval, 0.77-0.89). We developed a scoring system based on the logistic regression model and found a sensitivity 0.96 (0.90-1.00) and specificity 0.53 (0.48-0.59) for a cut-off score of 1.
This model showed good ability to differentiate patients with and without serious outcomes as evidenced by the high AUC and sensitivity. The results of this study could be used in the prospective derivation of a clinical decision tool.
目前尚无用于急诊科（ED）下消化道出血（LGIB）患者风险分层的可靠工具。我们的目的是确定风险因素并建立预测 ED LGIB 患者 30 天严重不良事件的初步模型。
我们对包括急性 LGIB 在内的成年 ED 患者进行了病历回顾。我们使用 30 天全因死亡、复发性 LGIB、需要干预控制出血、导致重症监护病房入院的严重不良事件的复合结局。一名研究人员收集变量数据，另一名研究人员独立收集 10%的变量用于观察者间可靠性。我们使用向后多变量逻辑回归分析和 SELECTION=SCORE 选项创建初步风险分层工具。我们评估了最终模型的诊断准确性。
在 372 名患者中，有 48 名发生不良结局。我们发现年龄≥75 岁、血红蛋白≤100g/L、国际标准化比值≥2.0、ED 持续出血和结直肠息肉病史是多变量回归分析中的统计学显著预测因素。该模型的曲线下面积（AUC）为 0.83（95%置信区间，0.77-0.89）。我们根据逻辑回归模型开发了一个评分系统，发现截断值为 1 时的敏感性为 0.96（0.90-1.00），特异性为 0.53（0.48-0.59）。
该模型的 AUC 和敏感性较高，表明其具有良好的区分有严重结局和无严重结局患者的能力。该研究的结果可用于前瞻性推导临床决策工具。
