A new scoring system for upper gastrointestinal bleeding: Too simple or still complicated? (2020)

Risk stratification for patients with upper gastrointestinal bleeding (UGIB) is recommended by international care guidelines and thought to be part of the standard of care.1-3 In particular, pre-endoscopic risk scores are useful because they provide earlier risk assessment compared to scores that use endoscopic findings. However, most of these scores involve multiple clinical and biochemical parameters and are too complicated to be used in a busy emergency medicine or gastroenterology unit on a regular basis. In this issue of the Journal of Gastroenterology and Hepatology, Redondo-Cerezo et al. have developed a “simple” risk score named MAP (ASH) score (using six parameters namely mental status, American Society of Anesthesiologists score, pulse and blood pressure, and albumin and hemoglobin levels and a simple calculator) that performs well and is easily implementable at the point of care.4 This score was developed from an international cohort of patients with UGIB and validated in a single tertiary referral center. It performed similarly to the best performing risk score (Glasgow-Blatchford Score) in predicting need for hospital-based intervention (area under the curve [AUC] 0.83), 30-day mortality (AUC 0.74), endoscopic intervention (AUC 0.61), and rebleeding (AUC 0.73). MAP (ASH) is simpler than the Glasgow-Blatchford Score and easier to calculate, which may help busy practitioners apply the score in practice. MAP (ASH) was developed for risk stratification in patients presenting to the hospital prior to endoscopic evaluation to guide provider decision making. The score uses mostly clinical variables, including a global physician assessment with the American Society of Anesthesiologists score. The current study demonstrates a valiant effort to reduce the mental load in calculating risk for patients with UGIB, but the inherent difficulty of performing a complex calculation during a busy clinical workflow remains unsolved particularly because the ideal use would be making the calculation directly from memory rather than having to break the workflow to enter data into an online calculator. The simplified point system still requires remembering which elements represent higher point totals, and there are two A's (American Society of Anesthesiologists score and albumin level) that have different point values that may create confusion. Furthermore, specific cutoffs (e.g. albumin < 2.5 and hemoglobin < 10) still must be memorized. While MAP (ASH) and other clinical scores will continue to shed light on meaningful factors that can be used for prognostic modeling, the challenges of clinical uptake by clinicians and good performance of outcome prediction will be difficult to surmount. One solution to improve clinical uptake is through automatic deployment using the electronic health record that is available in many established healthcare systems. This would minimize manual data entry and potentially provide the score at the point of care for clinical decision support. More computationally complex solutions such as machine learning has shown promise in improving performance beyond that of existing clinical risk scores. Recently, a pre-endoscopic risk score was developed using a machine learning gradient-boosted model with improved performance overall and better ability to identify very low risk patients compared with the Glasgow-Blatchford Score.5 The potential of machine learning also includes the ability of the model to “learn” over time and for models to be customized for each center by retraining the model on center-specific data. Hence, this AI-assisted prediction model will continue to improve with time and experience. However, machine learning models increase the burden of data entry because they include of more variables, require computational infrastructure that is not widely available, and are not easily interpretable. Much work has to be done in this area, but we are starting to see new light at the end of tunnel. In summary, the development of MAP (ASH) represents a new simplified model that can be used to prognosticate in patients with UGIB. Hopefully, the addition of this score to the array of risk scores in UGIB will provide another option for busy providers to triage patients appropriately as part of timely and high-quality care.