Accurate triage of lower gastrointestinal bleed (LGIB) – A cohort study

• This study aims to improve clinical decision making in the emergency department for patients presenting with LGIB.
• The HAKA score predicts severe LGIB with a NPV of 88% and PPV of 44%.
• HAKA – Haemoglobin less than 100 mg/dl; Use of Aspirin; history of (K) collapse; and Albumin less than 38 g/l.
• This clinical prediction tool could be used to identify those high risk patients requiring admission while low risk patients could be safely and effectively treated as outpatients.

IntroductionAcute lower gastrointestinal bleeding (LGIB) is a common acute presenting complaint to hospital. Unlike upper gastrointestinal bleeding, the diagnostic and therapeutic approach is not well-standardised. Intensive monitoring and urgent interventions are essential for patients with severe LGIB. The aim of this study is to investigate factors that predict severe LGIB and develop a clinical predictor tool to accurately triage LGIB in the emergency department of a busy metropolitan teaching hospital.MethodsWe retrospectively identified all adult patients who presented to Middlemore Hospital Emergency Department with LGIB over a one year period. We recorded demographic variables, Charlson Co-morbidities Index, use of anticoagulation, examination findings, vital signs on arrival, laboratory test results, treatment plans and further investigations results. We then identified a subgroup of patients who suffered severe LGIB.ResultsA total of 668 patients presented with an initial triage diagnosis of LGIB. 83 of these patients (20%) developed severe LGIB. Binary logistic regression analysis identified four independent risk factors for severe LGIB: use of aspirin, history of collapse, haemoglobin on presentation of less than 100 mg/dl and albumin of less than 38 g/l.ConclusionsWe have developed a clinical prediction tool for severe LGIB in our population with a negative predictive value (NPV) of 88% and a positive predictive value (PPV) of 44% respectively. We aim to validate the clinical prediction tool in a further cohort to ensure stability of the multivariate model.