Department of General Surgery, Singapore General Hospital, 20 College Rd, Singapore, 169856, Singapore.
Health Services Research Centre, Singapore Health Services, Singapore, Singapore.
World J Emerg Surg. 2021 Nov 22;16(1):58. doi: 10.1186/s13017-021-00402-y.
Lower gastrointestinal bleeding (LGIB) is a common presentation of surgical admissions, imposing a significant burden on healthcare costs and resources. There is a paucity of standardised clinical predictive tools available for the initial assessment and risk stratification of patients with LGIB. We propose a simple clinical scoring model to prognosticate patients at risk of severe LGIB and an algorithm to guide management of such patients.
A retrospective cohort study was conducted, identifying consecutive patients admitted to our institution for LGIB over a 1-year period. Baseline demographics, clinical parameters at initial presentation and treatment interventions were recorded. Multivariate logistic regression was performed to identify factors predictive of severe LGIB. A clinical management algorithm was developed to discriminate between patients requiring admission, and to guide endoscopic, angiographic and/or surgical intervention.
226/649 (34.8%) patients had severe LGIB. Six variables were entered into a clinical predictive model for risk stratification of LGIB: Tachycardia (HR ≥ 100), hypotension (SBP < 90 mmHg), anaemia (Hb < 9 g/dL), metabolic acidosis, use of antiplatelet/anticoagulants, and active per-rectal bleeding. The optimum cut-off score of ≥ 1 had a sensitivity of 91.9%, specificity of 39.8%, and positive and negative predictive Values of 45% and 90.2%, respectively, for predicting severe LGIB. The area under curve (AUC) was 0.77.
Early diagnosis and management of severe LGIB remains a challenge for the acute care surgeon. The predictive model described comprises objective clinical parameters routinely obtained at initial triage to guide risk stratification, disposition and inpatient management of patients.
下消化道出血（LGIB）是外科住院患者的常见表现，给医疗保健成本和资源带来了巨大负担。目前缺乏用于 LGIB 患者初始评估和风险分层的标准化临床预测工具。我们提出了一种简单的临床评分模型，以预测有发生严重 LGIB 风险的患者，并提出了一种指导此类患者管理的算法。
进行了一项回顾性队列研究，确定了在我院接受 LGIB 治疗的连续患者在一年内。记录了基线人口统计学资料、初始表现时的临床参数和治疗干预措施。进行多变量逻辑回归以确定预测严重 LGIB 的因素。开发了一种临床管理算法，以区分需要住院治疗的患者，并指导内镜、血管造影和/或手术干预。
226/649（34.8%）患者有严重 LGIB。有 6 个变量被纳入 LGIB 风险分层的临床预测模型：心动过速（HR≥100）、低血压（SBP<90mmHg）、贫血（Hb<9g/dL）、代谢性酸中毒、使用抗血小板/抗凝剂和直肠出血活跃。临界值≥1 的最佳得分对预测严重 LGIB 的敏感性为 91.9%、特异性为 39.8%，阳性和阴性预测值分别为 45%和 90.2%。曲线下面积（AUC）为 0.77。
急性护理外科医生在早期诊断和治疗严重 LGIB 方面仍面临挑战。所描述的预测模型包括在初始分诊时常规获得的客观临床参数，以指导风险分层、患者的处置和住院管理。
