## 1 Introduction  
Gastrointestinal emergencies pose a high risk of morbidity and mortality, particularly in elderly and comorbid patients, and require prompt and accurate risk stratification [1]. Conditions such as gastrointestinal (GI) bleeding, acute pancreatitis, perforation, and biliary tract disease may deteriorate rapidly [2]. However, the early identification of high-riskpatients remains challenging in emergency settings, as existing scoring systems are often time-consuming or lack validation in acute GI cases [3]. In response to this clinical gap, easily applicable and reliable biomarkers have gained attention [4]. One such tool is the Prognostic Nutritional Index (PNI), which reflects both nutritional and immune status based on serum albumin and lymphocyte counts [5]. Although initially developed for surgical patients, PNI has shown prognostic value in oncology, sepsis, and cardiovascular disease; however, its use in GI emergencies remains limited [6]. Given the role of malnutrition and inflammation in poor outcomes, the PNI may serve as a practical indicator for early risk assessment in patients with GI emergencies [7]. This study aimed to evaluate the predictive value of PNI in determining clinical outcomes and its potential use as a decision support tool in the emergency department. Gastrointestinal emergencies are serious clinical conditions with a high risk of morbidity and mortality, especially in elderly and malnourished patients [1]. Gastrointestinal emergencies, such as acute appendicitis, intestinal hemorrhage, gastric and duodenal perforation, biliary tract diseases, and acute pancreatitis, require rapid intervention and accurate risk assessment [8]. The examination findings in this patient group vary greatly depending on the severity of the disease [2]. Patients with mild disease may present with mild tenderness in the abdomen, whereas those with severe disease may present with findings ranging from severe pain on palpation in the abdomen to the absence of bowel sounds [3]. Serious outcomes are not uncommon in acute gastrointestinal emergencies, and early risk assessment is vital [4]. Delays in diagnosis and treatment increase morbidity by leading to changes such as perforation, sepsis, and multiple organ failure; postoperative intensive care unit and hospital stays are significantly longer in patients with delayed diagnosis [9]. Various scoring systems are used to determine the severity of gastrointestinal diseases. These scoring systems are useful for predicting disease severity using various clinical, laboratory, and imaging parameters [3]. It is critical to predict which patients are at a high risk of gastrointestinal emergencies in the emergency department. For this reason, many clinicians use these scoring systems to evaluate patients. Because rapid, easily applicable, outcome-predictive biomarkers are needed in emergency settings. The Prognostic Nutritional Index (PNI) is a simple scoring method that is remarkable at this point. The PNI was defined by [PERSON] and colleagues in 1980 to assess the prognosis of patients undergoing gastrointestinal surgery [5]. This index is based on two basic laboratory parameters reflecting the nutritional and immunological status of the patient: serum albumin level and peripheral lymphocyte count. Briefly was calculated as follows: PNI = 10 \(\times\) serum albumin (g/dL) + 0.005 \(\times\) total lymphocyte count (mm\({}^{3}\)) [10]. Considering our data, PNI appears to be a cost-effective prognostic tool that can be easily calculated in the emergency department. The fact that it can be calculated using only routine blood tests provides wide applicability in clinical practice. This index, which has been previously used in oncological and cardiovascular diseases, seems to be useful for decision support in emergency medicine, especially in gastrointestinal emergencies. Early recognition of patients with low PNI may allow the management of this high-risk group with interventions such as intensive care follow-up and aggressive fluid and nutritional support.