Red cell distribution width to serum albumin ratio as an early prognostic marker for severe acute pancreatitis: A retrospective study

Acute pancreatitis (AP) refers to a condition in which the pancreatic enzyme is activated due to various factors, including the presence of gallstones, excessive alcohol consumption, and hyperlipidemia, followed by local inflammation of the pancreas and systemic inflammatory response, accompanied with or without another organ failure. According to the 2012 Revised Atlanta Classification, AP can be classified as mild AP (MAP), moderately severe AP (MSAP), and severe AP (SAP) [1]. The prognosis of AP largely depends on its severity, wherein SAP is a critical condition with >30% mortality rate reported in recent years [2]. Fisher et al. assert that early diagnosis and treatment of SAP can reduce the development of complications and chances of mortality [3]. Over the past few decades, predictive scoring systems, such as the Ranson score, BISAP, and MCTSI, have played important roles in assessing the severity of AP [4]. However, due to the complexity of these scoring systems, their predictive value has remained limited to the early stage of the disease. To date, no single prognostic indicator has been proposed to predict SAP within 24 h of admission.

The red cell distribution width (RDW) is a quantitative, sensitive, and accurate biochemical parameter that reflects the heterogeneity in the size of circulating erythrocytes under different inflammatory conditions [5], [6]. RDW has emerged as an excellent diagnostic indicator of inflammation in predicting SAP [7], [8], [9]. Serum albumin (ALB) is usually referred to as a nutritional marker that indicates the nutritional status of a patient. Li et al. suggested that ALB can be used as an independent risk factor for predicting persistent organ failure (POF) in AP [10]. However, no study to date has confirmed whether the combined detection of RDW and ALB can predict SAP on patient’s admission. Therefore, in this study, we retrospectively analyzed the hospitalization data of patients with AP and compared the RDW-to-ALB ratio with the corresponding Ranson, BISAP, and MCTSI scores to create a simple and accurate method of predicting SAP at the early stage.

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