The SHA2PE score: a new score for lower gastrointestinal bleeding that predicts low-risk of hospital-based intervention.

OBJECTIVES: Lower gastrointestinal bleeding (LGIB) risk scores have mainly focused on identifying high-risk patients. A risk score aimed at predicting which patients will not require hospital-based intervention may reduce unnecessary hospital admissions. The aim of the current study was to develop such a risk score. MATERIAL AND METHODS: A retrospective, population-based study that included patients presenting to the emergency room (ER) with LGIB from 2010 to 2013. Hospital-based intervention was defined as blood transfusion, endoscopic hemostasis, arterial embolization or surgery. The study cohort was split into train (70%) and test (30%) data. Train data were used to produce a multiple logistic regression model and a risk score that was validated on the test data. RESULTS: Overall, 581 patients presented 625 times to the ER, mean age 61 (±22), males 49%. Of train data patients, 72% did not require hospital-based intervention. Independent predictors of low-risk patients (did not require hospital-based intervention) were systolic pressure ≥100mmHg (Odds ratio [OR] 4.9), hemoglobin >12g/dL (OR 103), hemoglobin 10.5-12.0g/dL (OR 19), no antiplatelets (OR 3.7), no anticoagulants (OR 2.2), pulse ≤100 (OR 2.9), and visible bleeding in the ER (OR 3.8). When validating the score on the test data, only 2% were wrongly predicted to be low-risk, the negative predictive value was 96% and the area under curve was 0.83. CONCLUSIONS: A new risk score has been developed for LGIB that may help identify low-risk patients in the ER that can be managed in an outpatient setting, thereby lowering unnecessary hospital admissions.

Acute Upper Non-variceal and Lower Gastrointestinal Bleeding.

Acute gastrointestinal (GI) bleeding is a common surgical emergency requiring hospital admission and associated with high morbidity and mortality. Appropriate decision-making is essential to make a prompt diagnosis, accurate risk assessment, and proper resuscitation of patients with gastrointestinal bleeding. Despite multiple randomized trials and meta-analyses, there is still controversy on various management issues like appropriate risk stratification, the timing of endoscopy, choosing an appropriate endoscopic, and radiological intervention in these groups of patients. As the usage of nonsteroidal anti-inflammatory drugs, antiplatelet, and antithrombotic agents is common in patients with gastrointestinal bleeding, the physician is challenged with proper management of these drugs. The present review summarizes the current strategies for risk stratification, localization of bleeding source, endoscopic and radiological intervention in patients with acute nonvariceal upper GI, middle GI, and lower GI bleeding.

Making decisions using radiology in lower GI hemorrhage.

Acute lower gastrointestinal bleeding (LGIB) is a common diagnosis in current practice that may warrant hospitalization and invasive management. There is a shift in the paradigm in the management of this condition away from traditional extensive operative intervention to minimally invasive radiological techniques. These newer modalities offer an opportunity to provide more accurate information on location of bleeding and subsequent management. The increased ease of access to interventional radiology units in major teaching hospitals represents an opportunity to adopt its use in the management of gastrointestinal bleeding. Further, with technological improvements, it is becoming an increasingly favoured option. Traditional endoscopic techniques have been fraught with poor vision in the acute setting, requiring the colon to be purged to aide in better visualization. The use of these newer technologies have been the subject of many reviews which highlight their efficacy in providing a road map to the bleeding site and eventual intervention. We aim to review the literature regarding the use of radiology in the management of LGIB, to provide surgeons with a discourse with regards to the approach in synthesizing the data and applying it when deciding its use.