Validity of the Adapted Waterlow Score as a Tool in Predicting Adverse Outcomes in Acute Pancreatitis When Compared With the Ranson Score and Serum CRP Levels

Abstract

IntroductionAcute pancreatitis (AP) is one of the most common emergency room presentations, with an annual worldwide incidence of 150-420 cases per million and a 30-50% mortality rate. Unfortunately, predicting prognosis in AP patients at an early admission phase is difficult. The Waterlow score is a semi-quantitative composite score devised to stratify the risk of developing pressure sores in in-patient settings. Components such as age, gender, nutritional status, body mass index, mobility, smoking status, comorbidities, surgery, use of medications, neurological status, and continence, all combine to generate a single numerical figure between 2 and 64 to overcome the difficulty of the composite scoring systems such as the Ranson score, Glassgow score, Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) and its modification (Portsmouth or P-POSSUM), Simplified Acute Physiology Score (SAPS 2), Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and Bedside index for severity in acute pancreatitis (BISAP). AimThis study aimed to validate the Waterlow score as a surrogate marker in predicting in-patient mortality, length of hospital stay (LOHS), intensive care unit (ICU) admissions, and AP complications compared to the Ranson score and serum CRP levels. MethodA prospective case series analysis was conducted from August 2018 to November 2019 at a tertiary care center in central Gujarat. This study included 51 newly diagnosed patients with AP or acute on chronic pancreatitis on accrual. Out of 51 patients, four were excluded from our study, as three were discharged against medical advice (DAMA) and one other absconded from the ward premises. The study group comprised 47 patients diagnosed with AP, out of which 40 patients were male (85.1%) and seven were females (14.9%). The mean age of the population was 37.5 ± 13.0 years. Microsoft Excel calculated the standard deviation and mean for data entry. All statistical analyses were made with MedCalc software version 19.1.3 (MedCalc Software Ltd., Ostend, Belgium).