Comparative Performance of ALBI score versus MELD-Na Score in Predicting Postoperative Outcomes Following Elective Major Abdominal Surgery in Cirrhotic Patients

Comparative Performance of ALBI score versus MELD-Na Score in Predicting Postoperative Outcomes Following Elective Major Abdominal Surgery in Cirrhotic Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative Performance of ALBI score versus MELD-Na Score in Predicting Postoperative Outcomes Following Elective Major Abdominal Surgery in Cirrhotic Patients Tasneem Khaled, M A Mekky, Mohamed Omar Abdelmalek, Mostafa A Hamad, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9457480/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Perioperative risk stratification in cirrhotic patients remains a significant clinical challenge. While the Albumin–Bilirubin (ALBI) and MELD-Na scores have emerged as objective alternatives to traditional systems, their comparative performance in elective surgery is not fully established. We aimed to compare the predictive accuracy of ALBI and MELD-Na for postoperative morbidity in cirrhotic patients undergoing elective major abdominal surgery. Methods : This prospective observational cohort study enrolled 57 cirrhotic patients undergoing elective major abdominal interventions between January 2024 and August 2025. Preoperative ALBI and MELD-Na scores were calculated. The primary endpoint was 30-day overall morbidity (surgical complications or hepatic decompensation, graded by the Clavien-Dindo classification. Predictive performance was evaluated using AUROC analysis, DeLong tests, multivariate logistic regression, and Kaplan-Meier survival analysis. Results : The cohort was predominantly Child-Pugh A (89.5%) with a median age of 61.0 years. Postoperative morbidity occurred in 31.6% of patients; complications were primarily hepatic/medical (83.3%) and minor (Clavien-Dindo I–II, 72.2%). The ALBI score demonstrated significantly higher predictive accuracy for morbidity compared to MELD-Na (AUC: 0.835 vs. 0.683; P= 0.001). This superiority persisted in a subgroup analysis excluding patients with obstructive jaundice ( P= 0.001). An ALBI cut-off ≥2.42 yielded a sensitivity of 88.9% and a negative predictive value of 93.5%. In multivariate analysis, ALBI was the sole independent predictor of complications (OR: 24.0; 95% CI: 1.8–322.1; P= 0.016). Kaplan-Meier analysis confirmed significantly shorter complication-free survival in the high-risk ALBI group (Log-rank P= 0.005), whereas MELD-Na failed to stratify risk effectively (Log-rank P= 0.168). Conclusion : The ALBI score is a more robust and reliable tool than MELD-Na for preoperative risk stratification in cirrhotic patients. Its high negative predictive value and objective nature make it superior for identifying patients at risk of postoperative morbidity following major elective abdominal surgery. Risk stratification cirrhotic elective abdominal surgery ALBI MELD Na Figures Figure 1 Figure 2 Background Patients with liver cirrhosis undergoing surgery represent a high-risk population due to the complex physiological derangements associated with the disease, including portal hypertension, coagulopathy, and impaired synthetic and immune function. These factors contribute to substantially increased perioperative morbidity and mortality ( 1 , 2 , 3 ). Several prognostic scoring systems have been developed to stratify surgical risk in this population. The Child-Turcotte-Pugh (CTP) classification and the Model for End-Stage Liver Disease (MELD) score are among the most widely cited tools for perioperative risk assessment ( 4 ). However, their predictive accuracy and clinical utility may vary across different clinical contexts and geographic regions. More recently, the Albumin-Bilirubin (ALBI) score and the MELD-Na score have emerged as objective, liver-specific alternatives for preoperative risk stratification ( 5 , 6 , 7 ). Although multiple studies have compared the performance of ALBI and MELD-Na against CTP and MELD scores in predicting postoperative morbidity, mortality, and liver failure ( 5 , 8 ), there remains a lack of consensus—particularly from a hepatology perspective—regarding which score offers superior reliability and accuracy in predicting outcomes following abdominal surgery in cirrhotic patients ( 8 ). The present study was designed to address this gap by conducting a comprehensive evaluation of the predictive performance of ALBI and MELD-Na scores in cirrhotic patients undergoing elective major abdominal surgery. Methods Study Design and Setting This was a single-center, prospective observational cohort study conducted at Assiut University Hospitals, Egypt. The study enrolled cirrhotic patients admitted for elective major abdominal surgery under anesthesia. Participants A total of 57 cirrhotic patients undergoing elective major abdominal surgery between January 2024 and August 2025 were included. Written informed consent was obtained from all participants. All surgical procedures were performed by a single surgical team to ensure consistency. **Inclusion criteria** were adult patients (≥ 18 years) with confirmed liver cirrhosis scheduled for elective major intra-abdominal surgery. The diagnosis of liver cirrhosis was established if any one of the following findings was present (i) compatible intraoperative gross findings. (ii) evidence of portal hypertension (ascites, gastroesophageal varices, or hepatic encephalopathy) in patients with liver disease, (iii) compatible radiologic findings. Cirrhosis severity was classified according to the D’Amico classification, with all patients being compensated ( 9 ). **Major surgical procedures ** were defined according to the Delphi consensus definition of the European Surgical Association as operations involving significant physiological stress, entry into a body cavity, extensive tissue dissection, or expected substantial perioperative risk ( 10 ). Procedures included hepatocellular carcinoma (HCC) resection, laparoscopic and open cholecystectomy, common bile duct (CBD) exploration, bilio-enteric shunts, pancreatic surgery (Whipple and distal pancreatectomy), splenectomy, and repair of recurrent ventral and inguinal hernias. **Exclusion criteria** were acute liver failure without underlying cirrhosis, prior liver transplantation, malignancies other than HCC and missing preoperative laboratory data. Data Collection **Preoperative assessment** included a standardized clinical examination, vital signs, and evaluation of liver dysfunction manifestations. Laboratory investigations comprised complete blood count, liver function tests (total protein, albumin, bilirubin, and transaminases), coagulation profile (international normalized ratio [INR]), renal function tests (serum urea, creatinine), serum electrolytes (sodium, potassium, calcium, and magnesium). Neurological status was assessed using the Glasgow Coma Scale. Physical status was classified using the American Society of Anesthesiologists (ASA) classification ( 11 ). ALBI and MELD-Na scores were calculated preoperatively to evaluate liver function and predict postoperative outcomes. **Intraoperative data** included surgical procedure type, duration, anesthesia type, estimated blood loss, transfusion requirements, and occurrence of intraoperative organ injury. **Postoperative follow-up** was conducted at day 1, day 7, and day 30. The primary outcomes were overall morbidity and 30-day mortality. Morbidity was defined as any surgical complication or hepatic decompensation occurring during follow-up. Hepatic decompensation was defined as the concurrent presence of clinical deterioration and biochemical evidence of worsening liver function. Surgical complications included surgical site infection (superficial, deep, or organ space), wound dehiscence, bile leak, and postoperative bleeding requiring transfusion. Complications were graded according to the Clavien-Dindo classification, with grades I-II defined as minor and grades III-V as major ( 12 ). Scoring Systems **MELD-Na score** was calculated using the formula: (0.957 × ln [creatinine mg/dL] + 0.378 × ln [total bilirubin mg/dL] + 1.120 × ln [INR] + 0.643) × 10, with sodium values capped between 125 and 137 mmol/L ( 14 , 15 ). Risk categories were defined as low (≤ 9), moderate ( 10 – 19 ), and high (≥ 20) ( 16 ). **ALBI score** was calculated as: (log10 bilirubin [µmol/L] × 0.66) + (albumin [g/L] × − 0.085). Grades were defined as grade 1 (≤ − 2.60, good liver function), grade 2 (> − 2.60 to ≤ − 1.39, moderate impairment), and grade 3 (> − 1.39, poor function) ( 16 , 17 ). Statistical Analysis Analyses were performed using SPSS (version 26). Data presented as Median (IQR) for continuous and % for categorical variables. Mann–Whitney U for continuous data; Chi-square/Fisher’s exact for categorical data. ROC curves (AUC) to measure performance, Youden index for cut-offs, and DeLong test for comparisons. Logistic Regression for Odds Ratios (OR) and Cox Proportional Hazards for Hazard Ratios (HR). Kaplan–Meier curves with Log-rank test to compare complication-free survival. p-value < 0.05 was considered statistically significant. Results Baseline Characteristics A total of 57 patients were included, with a median age of 61.0 years (IQR: 54.0–67.0). The majority were male (63.2%). Hepatitis C virus (HCV) infection was the predominant etiology of cirrhosis (61.4%). Most patients were classified as Child-Pugh class A (89.5%). There were 6 patients who were classified as Child-Pugh Class B and C due to higher levels of bilirubin (biliary obstruction) not due to liver cell failure. The most common surgical procedures were HCC resection and cholecystectomy, each accounting for 38.6% of cases ( Table 1 ). Table 1 Baseline demographic, clinical characteristics, and postoperative outcomes of cirrhotic patients undergoing abdominal surgery (N = 57). Variable n (%) or Median (IQR) Age (years) Median (IQR) 61.0 (57.0–68.5) Gender Male: Female 36 (63.2%) : 21 (36.8%) Etiology of Cirrhosis HCV: HBV: Others 35 (61.4%): 11 (19.3%): 11 (19.3%) Child–Pugh Score Child A: Child B: Child C 51 (89.5%): 5 (8.8%) :1 (1.8%) Liver Scores (Median [IQR]) MELD-Na Score 9.0 (8.0–11.4) ALBI Score −2.52 (− 2.93 to − 2.09) Type of Surgery HCC Resection 22 (38.6%) Cholecystectomy (+- CBD exploration) 22 (38.6%) Pancreatic Surgery 4 (7.0%) Others (Splenectomy/bilio-enteric shunts / Hernia repair) 9 (15.8%) Operative characteristics and outcome Duration of Surgery (minutes) Median (IQR) 125.0 (67.0–160.0) Intraoperative Bleeding required Blood Transfusion 28 (49.1%) Postoperative Bleeding 4 (7.1%) * Hospital Stay (days) Median (IQR) 3.0 (2.0–7.0) Postoperative complications 18 (31.58%) - Nature of Complications Hepatic/ medical complications: surgical complications 15 (83.3%) : 3 (16.7%) - Complications Severity (Clavien–Dindo Classification) Minor (Grade I–II) : Major (Grade III–IV): Death (Grade V) 13 (72.2%) : 4 (27.8%) : 1(5.5%) - Clinical Presentation of Complications (N = 18 ) New onset / Worsening Ascites 12 (66.7%) Hepatic Encephalopathy (HE) 5 (27.8%) Gastrointestinal (GIT) Bleeding 4 (22.2%) Persistent Jaundice (30-day) 7 (22.2%) Death (at day 7) 1(5.5%) Data are presented as number (%) or median (interquartile range, IQR). Postoperative complications were classified according to the Clavien–Dindo classification system. Hepatic/medical complications included new-onset or worsening ascites, hepatic encephalopathy, gastrointestinal bleeding, and persistent jaundice within 30 days after surgery. Abbreviations: HCV, hepatitis C virus; HBV, hepatitis B virus; MELD-Na, Model for End-Stage Liver Disease–Sodium; ALBI, Albumin–Bilirubin score; HCC, hepatocellular carcinoma; CBD, common bile duct; SSI, surgical site infection; GIT, gastrointestinal tract; IQR, interquartile range. Postoperative Outcomes The median postoperative hospital stay was 3.0 days (IQR: 2.0–7.0). Postoperative bleeding occurred in 7.1% of patients. Overall morbidity was observed in 31.6% of patients. According to the Clavien-Dindo classification, 72.2% of complications were minor (grades 1–2) and 27.8% were major (grades 3–5). The majority of complications were hepatic or medical in nature (83.3%), with surgical complications accounting for 16.7%. All complications occurred within 30 days postoperatively except for the patient who died, whose complications were noted on day 7. The most common clinical presentations were new-onset or worsening ascites (66.7%), hepatic encephalopathy (27.8%), gastrointestinal bleeding (22.2%), and persistent jaundice (22.2%). The patient who died experienced both hepatic encephalopathy and persistent jaundice. Recorded surgical complications included colonic injury, surgical site infection, and bile leak ( Table 2 ). Table 2 ROC-derived diagnostic performance of MELD-Na and ALBI scores for prediction of postoperative morbidity in cirrhotic patients undergoing abdominal surgery. Parameter MELD-Na score (≥ 8.90) ALBI score ( ≥ − 2.42) AUC (95% CI) 0.683 (0.536–0.830) 0.835 (0.710–0.960) P-value (AUC) 0.027* < 0.001* DeLong Test (Comparison) 0.001* AUC after exclusion of OJ (95% CI) 0.629 (0.459–0.800) 0.823 (0.667–0.979) p-value after exclusion of OJ (95% CI) .171 . 001* Youden Index 0.286 0.633 Sensitivity (%) 72.2% 88.9% Specificity (%) 56.4% 74.4% Positive Predictive Value (PPV) (%) 43.3% 61.5% Negative Predictive Value (NPV) (%) 81.5% 93.5% Overall Accuracy (%) 61.4% 78.9% Positive Likelihood Ratio (LR+) 1.66 3.47 Negative Likelihood Ratio (LR−) 0.49 0.15 Odds Ratio (95% CI) 3.37 (1.00–11.29) 23.20 (4.51–119.34) P-value (Chi-Square) .052 < 0.001* Cut-off values were determined using the Youden index from ROC curve analysis. Diagnostic performance parameters including sensitivity, specificity, predictive values, likelihood ratios, and overall accuracy were calculated for the optimal cut-off points. DeLong’s test was used to compare the area under the ROC curves (AUC) between MELD-Na and ALBI scores. Additional analysis was performed after exclusion of patients with obstructive jaundice (OJ) to assess the stability of the predictive performance. Abbreviations: MELD-Na, Model for End-Stage Liver Disease–Sodium; ALBI, Albumin–Bilirubin score; AUC, area under the receiver operating characteristic curve; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; LR+, positive likelihood ratio; LR−, negative likelihood ratio; OJ, obstructive jaundice; ROC, receiver operating characteristic. Predictive Performance of ALBI and MELD-Na The ALBI score demonstrated significantly higher predictive accuracy for in-hospital morbidity compared to MELD-Na (AUC: 0.835 vs. 0.683; DeLong *p* = 0.001) ( Fig. 1 ). After excluding patients with obstructive jaundice, ALBI remained a significant predictor (*p* = 0.001), whereas MELD-Na did not (*p* = 0.171). At the optimal cut-off value of ≥ − 2.42 (Youden index: 0.633), ALBI achieved a sensitivity of 88.9%, specificity of 74.4%, and negative predictive value of 93.5%. The incidence of postoperative complications was significantly higher in the ALBI high-risk group compared to the low-risk group (61.5% vs. 6.5%; *p* < 0.001). In contrast, no significant difference was observed across MELD-Na risk groups (*p* = 0.052) ( Table 3 ). Table 3 Postoperative complication rates, severity (Clavien–Dindo classification), and hospital stay according to MELD-Na and ALBI risk groups Variable No Complications n (%) Complicated n (%) Minor (Grade I–II) n (%) Major (Grade III–IV-V) n (%) P-value* Hospital stay median IQR P-value* MELD-Na Score Low Risk (< 8.90 ) n = 27 22 (81.5%) 5 (18.5%) 4 (14.8%) 1 (3.7%) 0.052 4.0(2.0–7.0) 0.735 High Risk (≥ 8.90 ) n = 30 17 (56.7%) 13 (43.3%) 9 (30.0%) 4 (13.3%) 3.0(2.0–7.0) ALBI Score Low Risk ( < − 2.42) n = 31 29 (93.5%) 2 (6.5%) 2 (6.5%) 0 (0.0) < 0.001* 3.0(2.0–7.0) 0.165 High Risk ( ≥ − 2.42) n = 26 10 (38.5%) 16 (61.5%) 11 (42.3%) 5 (19.2%) 4.0(2.0-7.425) * Statistically significant at P < 0.05. *P-values calculated using Chi-square or Mann-Whitney U test as appropriate Abbreviations: MELD-Na, Model for End-Stage Liver Disease–Sodium; ALBI, Albumin–Bilirubin score; IQR, interquartile range Regression and Survival Analyses In univariate logistic regression, ALBI was associated with a substantially higher odds of complications (OR: 23.20) compared to MELD-Na (OR: 3.37). However, both scores remain statistically significant predictors In the multivariate analysis adjusting for age, with ALBI demonstrating stronger associations with in-hospital morbidity (OR: 24.0; 95% CI: 1.8–322.1; *p* = 0.016), compared to MELD-Na score (OR: 3.399; 95% CI: 1.010–11.437; p = 0.048) ( Table 5 ) , highlighting ALBI score potential as a more discriminative risk stratification tool. Age was not a significant predictor in either model ( Table 4 ). Table 4 Multivariable Cox Proportional Hazards Models for Predictors of Complication-Free survival Factor Model 1 (ALBI) Model 2 (MELD-NA) HR (95%Cl) P-value HR (95%Cl) P-value Patient Age 1.015 (.967-1.065) .546 1.013 (.956-1.062) .605 Liver score 6.307(1.418–28.053) .016 2.065 (.720-5.925) .178 Liver Score refers to Child B/C, MELD (≥ 8.90), or ALBI ( ≥ − 2.42) respectively in each model. Each model included patient age and one liver scoring system to avoid multicollinearity Note: Multivariable Cox proportional hazards regression models were used to assess predictors of outcome. Hazard ratios (HR) with 95% confidence intervals (CI) were calculated. Separate models were constructed for MELD-Na and ALBI scores to avoid collinearity. A p-value < 0.05 was considered statistically significant. Abbreviations: HR, hazard ratio; CI, confidence interval; ALBI, Albumin–Bilirubin score; MELD-Na, Model for End-Stage Liver Disease–Sodium. Table 5 Univariate and Multivariate Logistic Regression Analysis for Predictors of In-hospital Morbidity Predictor Group Univariate OR (95% CI) p-value Multivariate OR (95% CI) p-value Age (years) — 1.007 (.954-1.063) .810 1.010 (.955-1.067) .739 Duration of surgery (minutes) — .996 (.986-1.006) .435 — — Presence of portal hypertension and varices No r( 1 ) r( 1 ) — — Yes 1.115 (0.317–3.921) 0.865 — — Type of anesthesia — 1.417 (0.137–14.641) 0.770 — — Ascites No r( 1 ) r( 1 ) — — Yes 1.450 (0.430–4.888) 0.549 — — ALBI score ( < − 2.42) r( 1 ) r( 1 ) r( 1 ) r( 1 ) ( ≥ − 2.42) 19.773 (3.872-100.967) < .001* 24.017 (4.616-124.968) < .001* MELD-Na score < 8.90 r( 1 ) r( 1 ) r( 1 ) r( 1 ) ≥ 8.90 3.365(1.003–11.285) .049 3.399 (1.010–11.437) 0.048 Presence of Jaundice No r( 1 ) r( 1 ) — — Yes 2.400(.462-12.471) .298 — — Note: Univariate and multivariate logistic regression analyses were performed to identify predictors of in-hospital morbidity. Odds ratios (OR) with 95% confidence intervals (CI) were calculated. Variables with p < 0.05 were considered statistically significant. Reference categories are indicated as r(1( OR = odds ratio; CI = confidence interval; r( 1 )= reference category. Kaplan-Meier analysis demonstrated a significant difference in complication-free survival between ALBI risk groups (log-rank *p* = 0.005), with shorter survival observed in the high-risk group ( Fig. 2 b ). No significant difference was observed for MELD-Na risk groups (log-rank *p* = 0.168 ) ( Fig. 2 a ). In Cox proportional hazards analysis, ALBI was significantly associated with time to complication (HR: 6.307; 95% CI: 1.418–28.053; *p* = 0.016), while MELD-Na was not (HR: 2.065; 95% CI: 0.720–5.925; *p* = 0.178) ( Table 6 ). Table 6 Kaplan-Meier curves for complication-free survival according to ALBI and MELD-Na risk groups. Prognostic Model Total (N) Events (n) Censored n (%) Mean Survival Time (Days) [95% CI] Median Survival (Days) [95% CI] Log-Rank P-value ALBI Risk 57 18 39 (68.4%) 0.005 * Low Risk ( < − 2.42) 31 2 29 (93.5%) 9.36 (8.51–10.22) Not reached High Risk ( ≥ − 2.42) 26 16 10 (38.5%) 7.07 (5.37–8.78) 7.00 (2.76–11.24) MELD-Na Risk 57 18 39 (68.4%) 0.168 Low Risk (< 8.90) 27 5 22 (81.5%) 8.44 (7.23–9.65) Not reached High Risk (≥ 8.90) 30 13 17 (56.7%) 7.63 (5.95–9.32) 8.70 (5.25–12.16) Kaplan–Meier survival analysis was performed to evaluate complication-free survival according to liver function risk groups based on ALBI and MELD-Na scores. Event was defined as the occurrence of postoperative complications. The log-rank test was used to compare survival distributions between risk groups. Data are presented as number (%) or mean survival time with 95% confidence intervals (CI). Median survival time was reported when estimable. “Not reached” indicates that the median survival time could not be calculated because fewer than 50% of patients experienced the event during follow-up. Abbreviations: ALBI, Albumin–Bilirubin score; MELD-Na, Model for End-Stage Liver Disease–Sodium; CI, confidence interval. Discussion The revolutionary improvement in long-term survival in cirrhotic patients, due to new management guidelines and antiviral therapies over the last two decades, has made predictions of perioperative morbidity and mortality in cirrhotic patients undergoing non-transplant surgery as a clinical necessity ( 18 , 19 ). In addition, clinicians increasingly face the dilemma of balancing surgical necessity against hepatic risk. Establishing reliable, objective, and easily applicable prognostic tools is therefore critical to stratify risks, improve surgical decision-making and optimize surgical outcome ( 20 ). Recently, the Albumin–Bilirubin (ALBI) score and MELD-Na have emerged as a more accurate and reliable prognostic score than traditional scoring systems such as the Child-Pugh-Turcotte (CTP) score, the Model for End-Stage Liver Disease (MELD) ( 22 , 23 ). Although non-transplant abdominal surgeries represent nearly 50% of surgical procedures performed in cirrhotic patients, direct comparison between ALBI and MELD-Na has not been performed regarding major elective abdominal surgeries ( 22 , 23 , 24 ). This prospective cohort study provides a comparative evaluation of the ALBI and MELD-Na scores for predicting postoperative outcomes in cirrhotic patients undergoing elective major abdominal surgery. The principal finding is that the ALBI score demonstrated superior predictive accuracy for postoperative morbidity compared to the MELD-Na score, as evidenced by a higher AUC in ROC analysis, stronger independent association in multivariate regression, and better discrimination of complication-free survival on Kaplan-Meier analysis. These findings suggest that ALBI may represent a more reliable tool for preoperative risk stratification in this specific clinical context. The superior discriminative ability of the ALBI score observed in this study aligns with a growing body of evidence supporting its utility in surgical populations. The AUC of 0.835 for ALBI indicates good to excellent predictive performance, whereas the AUC of 0.683 for MELD-Na falls within the range considered poor to fair. This difference was statistically significant by DeLong test (p = 0.001), reinforcing the notion that ALBI may be a more sensitive indicator of hepatic functional reserve in the perioperative setting. Several factors may account for this difference. First, ALBI relies exclusively on albumin and bilirubin, two direct measures of hepatic synthetic capacity and excretory function, without being influenced by extra hepatic factors such as renal function or coagulation parameters. ( 25 ). Second, the persistence of ALBI’s predictive power after excluding patients with obstructive jaundice—a scenario in which MELD-Na lost significance—further supports its robustness as a liver-specific tool less susceptible to biliary pathology. In a retrospective analytic study from the NSQIP database, Taylor et al reported that ALBI was an excellent predictor of the overall post-operative mortality (AUC 0.80) and morbidity (AUC 0.66) in cirrhotic patients particularly in gastrointestinal surgery. However, both scores were equal in prediction of post-operative morbidity in non-gastrointestinal surgery. Notably, ALBI was superior to MELD-Na in predicting outcomes despite involving other types of surgeries like lung resections, elective colectomy, and adrenalectomy, which support the applicability of ALBI across different surgical procedures ( 8 ). In an Observational Cohort Study, Zaharia et al demonstrated that ALBI is the most accurate and objective score for identifying high-risk patients undergoing liver resection for HCC ( 26 ). For instance, a multicenter study by Wang et al. reported superior performance of ALBI over MELD in predicting post-hepatectomy liver failure ( 27 ). Similarly, a meta-analysis by Liu et al. concluded that ALBI demonstrated comparable or better prognostic accuracy than MELD across various surgical and nonsurgical settings ( 6 ). In addition, other studies demonstrated that the ALBI score not only associated with postoperative hepatic decompensation and in-hospital mortality, but comparable to both MELD and CTP scores with optimum balance between sensitivity and specificity for predicting mortality and morbidity ( 23 , 24 , 28 ). The present study extends this evidence to a heterogeneous cohort of cirrhotic patients undergoing diverse major abdominal procedures, reinforcing the generalizability of these observations. Kaltenbach et al advocated, in their review, the MELD-Na as a strong predictor morbidity and mortality in all hepatic and non-hepatic surgeries in cirrhotic patients. In addition, Schlosser et al demonstrate that MELD-Na is an accurate reliable prognostic score for morbidity and mortality in ventral hernias repair in cirrhotic patients. both studies included patients in emergency conditions in which hyponatremia and hypoalbuminemia significantly impact postoperative prognosis ( 5 , 29 ). The overall postoperative morbidity rate reported in our study (31.6%) is comparable to previous literature which reported postoperative complication rates in cirrhotic patients undergoing abdominal surgery from 25% to 40%, depending on the liver functional reservoir and surgical complexity ( 4 , 30 , 25 ). On the other hand, other studies reported higher rates of complications due to involving emergency patients in their retrospective data analysis ( 22 , 31 ). The predominance of hepatic/medical complications (83.3%) over surgical complications (16.7%) in this cohort highlights the central role of underlying liver disease in shaping postoperative outcomes. New-onset or worsening ascites was the most common manifestation of hepatic decompensation, occurring in 66.7% of patients with complications. This finding underscores the importance of preoperative assessment of portal hypertension and synthetic function—domains directly captured by the ALBI score through its albumin and bilirubin components. In contrast, MELD-Na’s inclusion of INR and creatinine may be more relevant to coagulopathic or renal complications, which were less frequent in this cohort. The optimal ALBI cut-off value of ≥ − 2.42 identified in this cohort achieved a negative predictive value of 93.5%, indicating that patients below this threshold are at very low risk for postoperative complications. This high NPV has direct clinical utility: it may help identify a subset of compensated cirrhotic patients who can proceed to elective surgery with minimal additional perioperative intervention. Conversely, the high-risk ALBI group experienced a markedly higher complication rate (61.5% vs. 6.5%, p < 0.001), suggesting that these patients warrant intensified perioperative optimization, closer monitoring, or consideration of alternative treatment strategies. The lack of significant differentiation across MELD-Na risk groups (p = 0.052) in this cohort merits careful interpretation. While the marginal trend toward significance may reflect limited statistical power due to sample size, it also raises the possibility that MELD-Na’s performance is attenuated in well-compensated populations. The majority of patients in this study were Child-Pugh class A (89.5%), representing a lower-risk subset where subtle differences in liver function may not be captured by MELD-Na, which was originally developed to predict mortality in end-stage liver disease. ALBI’s ability to stratify risk even within this predominantly compensated cohort underscores its potential advantage in surgical populations with milder liver dysfunction. Many prospective and retrospective studies agree to the present study that the ALBI score represents a simple reliable tool to stratify the risk of post hepatectomy liver failure which agrees with our study results ( 32 , 33 ). However, Kaltenbach et al concluded that liver scores such as the CTP Score, MELD-Na scores, MRS, and the VOCAL-Penn Score are powerful tools to help risk stratify patients based on preoperative factors. This could be justified by the presence of hypoalbuminemia and hyponatremia, which are strong indicators for sarcopenia and frailty that increase perioperative risks. However, these scores should be used parallel to good clinical judgment ( 5 ). With respect to ventral hernias, Schlosser et al advocated MELD-Na score as a significant reliable risk stratifying score in a retrospective NSQIP data analysis. In contrast, Yasri et al concluded in their review that MELD Na score could not be used as a reliable score for risk stratification or as areal reflection for liver functional reservoir because of its great affection of by laboratory investigation, INR and creatinine, which may be impaired even with compensated liver condition ( 29 , 34 ). Ahmed et al concluded that MELD, PALBI, and ALBI are reliable scores for risk stratification in cirrhotic patients with emergent surgery. This is due to hypoalbuminemia related to emergency conditions which enhance clinicians’ insight into postoperative morbidity and mortality ( 22 ). Multivariate analysis confirmed ALBI as an independent predictor of in-hospital morbidity (OR 24.0; 95% CI: 1.8–322.1; p = 0.016), and also does the MELD-Na score but with lower association (OR: 3.399; 95% CI: 1.010–11.437; p = 0.048). The wide confidence interval for ALBI reflects the limited sample size but does not detract from the strength of the point estimate. Importantly, age was not a significant confounder in either model, suggesting that the observed associations are primarily driven by liver-specific physiology rather than patient demographics. Cox proportional hazards analysis further substantiated these findings, demonstrating a significant difference in complication-free survival between ALBI risk groups (log-rank p = 0.005) and an independently associated hazard ratio of 6.307. The absence of a similar survival difference for MELD-Na risk groups reinforces the conclusion that ALBI provides superior prognostic discrimination for time-to-event outcomes in this population. In some analytic studies, ALBI score was considered an independent predictor for post hepatectomy bile leak ( 22 , 35 ). However, The British Society of Gastroenterology (BSG) guidance addresses that portal hypertension is an independent predictor for morbidity and 30-day mortality in cirrhotic patients undergoing colorectal surgery; they explained that the higher risk in the presence of portal hypertension is due to altered intraoperative hemodynamics, ascites, and coagulopathy ( 36 , 37 ). In a Propensity-Matched Study, Tsai et al concluded that Hypoalbuminemia (< 3.5 g/dL) was identified as an independent predictor of mortality, underscoring the importance of preoperative nutritional assessment and optimization. In addition, this explains the superiority of ALBI as an accurate predictor and risk stratification score ( 38 ). Moreover, Zhu et al , in their retrospective study which included 71 patients, concluded that baseline characteristics, such as ALBI grade and age, were cornerstones to assess perioperative risks and benefits of splenectomy for cirrhotic ( 39 ). The principal strengths of this study include its prospective design, standardized surgical and anesthetic protocols, use of validated outcome definitions (Clavien-Dindo classification, Delphi consensus for major surgery), and rigorous statistical methodology including ROC analysis with DeLong comparison, multivariate regression, and time-to-event analysis. Several limitations should be acknowledged. First, the single-center design and relatively small sample size (n = 57) limit the precision of effect estimates and may restrict generalizability to other populations or healthcare settings. Second, the predominance of patients with Child-Pugh class A cirrhosis and HCV-related disease reflects the local epidemiology but may not represent the broader spectrum of cirrhosis seen in other regions. Third, the limited number of events constrained the number of variables that could be included in multivariate models, potentially leaving residual confounding unaddressed. Fourth, the study did not assess inter-rater reliability for clinical outcome adjudication, although standardized definitions were used to minimize variability. Finally, longer-term outcomes beyond 30 days were not evaluated, and the impact of preoperative interventions (e.g., nutritional optimization, portal pressure reduction) was not captured. The findings of this study support the use of the ALBI score as a primary risk stratification tool in cirrhotic patients being considered for elective major abdominal surgery. Its high negative predictive value may facilitate the safe identification of low-risk patients, while its ability to discriminate against risk within compensated cirrhosis populations addresses a key gap in current perioperative assessment. Future research should focus on external validation of the ALBI cut-off value identified in this study across diverse geographic and etiologic populations. Prospective multicenter studies with larger sample sizes are needed to confirm the independent prognostic value of ALBI relative to MELD-Na and other emerging biomarkers. Additionally, the integration of ALBI with dynamic measures of portal hypertension (e.g., hepatic venous pressure gradient) or frailty assessments may further refine risk prediction. Finally, interventional studies evaluating whether ALBI-guided perioperative optimization protocols can improve outcomes would be a logical next step toward translating these findings into clinical practice. Conclusion In this prospective cohort of predominantly compensated cirrhotic patients undergoing elective major abdominal surgery, the ALBI score demonstrated superior predictive accuracy for postoperative morbidity compared to the MELD-Na score. Its strong negative predictive value, independent association with complications, and ability to discriminate survival differences support its utility as a reliable and clinically actionable risk stratification tool. These findings advocate for the integration of ALBI into preoperative assessment protocols and warrant further validation in larger, multicenter cohorts. Abbreviations ALBI Albumin–Bilirubin score ASA American Society of Anesthesiologists AUC Area under the curve BSG British Society of Gastroenterology CBC Complete blood count CBD Common bile duct CD Clavien-Dindo CI Confidence interval CTP Child-Turcotte-Pugh GCS Glasgow Coma Scale GIT Gastrointestinal tract HBV Hepatitis B virus HCC Hepatocellular carcinoma HCV Hepatitis C virus HRs Hazard ratios INR International Normalized Ratio IQR Interquartile range LR− Negative likelihood ratio LR+ Positive likelihood ratio MELD Model for End- Stage Liver Disease MELD-Na Model for End-Stage Liver Disease–Sodium NPV Negative predictive value OJ Obstructive jaundice ORs Odds ratios PPV Positive predictive value ROC Receiver operating characteristic SPSS Statistical Package for the Social Sciences SSI Surgical site infection Declarations Ethical Considerations This study was approved by the Institutional Review Board of Assiut University Faculty of Medicine (IRB No. 17200794) and was conducted in accordance with the principles of the Declaration of Helsinki (7th revision, 2013) and the Declaration of Istanbul (2018). The study was registered at ClinicalTrials.gov (NCT05503836). Consent for publication All patients included in this research gave written informed consent to publish the data contained within this study. Availability of data and material The data set used and analyzed during the current study has been submitted for review and available upon request. Competing interests The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or non-profit sectors. Authors' contributions Authors contributed equally to the writing of this paper Acknowledgements Not applicable. References European Association for the Study of the Liver (EASL)(2025). EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma. Journal of Hepatology . 69(1):182–236. Mahmud N, Fricker ZP, McElroy LM, Qayed E, Wong RJ, Ioannou GN(2025). ACG clinical guideline: perioperative risk assessment and management in patients with cirrhosis. Official journal of the American College of Gastroenterology| ACG . 120(9):1968–1984. Wong M, Busuttil RW(2019). Surgery in patients with portal hypertension. Clinics in liver disease . 23(4):755–780. Ostojic A, Mahmud N, Reddy KR(2024). Surgical risk stratification in patients with cirrhosis. Hepatology international . 18(3):876–891. Kaltenbach MG, Mahmud N(2023). Assessing the risk of surgery in patients with cirrhosis. Hepatology Communications . 7(4):e0086. Liu J, Wei Y- s(2026). Prognostic value of easy Albumin-Bilirubin score in liver cirrhosis: a comparison with established scoring systems. European Journal of Gastroenterology & Hepatology . 10.1097. Goudsmit BF, Putter H, Tushuizen ME, de Boer J, Vogelaar S, Alwayn I, et al( 2021). Validation of the Model for End-stage Liver Disease sodium (MELD-Na) score in the Eurotransplant region. American Journal of Transplantation . 21(1):229–240. Taylor GA, Fagenson AM, Kuo LE, Pitt HA, Lau KN (2021). Predicting operative outcomes in patients with liver disease: albumin-bilirubin score vs model for end-stage liver disease-sodium score. Journal of the American College of Surgeons . 232(4):470–480. e472. D' Amico G, Garcia-Tsao G, Pagliaro L(2006). Natural history and prognostic indicators of survival in cirrhosis: a systematic review of 118 studies. Journal of hepatology . 44(1):217–231. Martin D, Mantziari S, Demartines N, Hübner M(2020). Defining major surgery: a Delphi consensus among European Surgical Association (ESA) members. World journal of surgery . 44(7):2211–2219. American Society of Anesthesiologists(2026). American Society of Anesthesiologists statement on ASA physical status classification system. Anesthesiol Open . 1(3):e0002-e0006. Dindo D, Demartines N, Clavien P-A(2024). Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Annals of surgery . 240(2):205–213. Kim WR, Biggins SW, Kremers WK, Wiesner RH, Kamath PS, Benson JT, et al(2008). Hyponatremia and mortality among patients on the liver-transplant waiting list. New England Journal of Medicine . 359(10):1018–1026. Alcorn J (2015). Changes to OPTN bylaws and policies from actions at OPTN/UNOS Executive Committee meetings July 2015–November 2015: clerical changes for implementation of adding serum sodium to the MELD score. Available from : https://optntransplanthrsagov/media/1575/policynotice_1101pdf. 2015. Al Abbas AI, Borrebach JD, Bellon J, Zureikat AH(2020). Does preoperative MELD score predict adverse outcomes following pancreatic resection: an ACS NSQIP analysis. Journal of Gastrointestinal Surgery . 24(10):2259–2268. Johnson PJ, Berhane S, Toyoda H, Johnson PJ(2022). The ALBI score: from liver function in patients with HCC to a general measure of liver function. JHEP Reports . 4(10):100557. Chan AW, Chan RC, Wong GL, Wong VW, Choi PC, Chan HL, et al( 2015). New simple prognostic score for primary biliary cirrhosis: albumin-bilirubin score. Journal of gastroenterology and hepatology . 30(9):1391–1396. Park HJ, Seo KI, Kim SJ, Lee SU, Yun BC, Han BH, et al( 2021). Effectiveness of albumin-bilirubin score as a predictor of post-hepatectomy liver failure in patients with hepatocellular carcinoma. The Korean Journal of Gastroenterology . 77(3):115–122. Klein J, Spigel Z, Kalil J, Friedman L, Chan E (2022). Postoperative mortality in patients with cirrhosis: reconsidering expectations. The American Surgeon . 88(2):181–186. Romeo M, Dallio M, Cipullo M, Coppola A, Mazzarella C, Mammone S, et al( 2025). Nutritional and Psychological Support as a Multidisciplinary Coordinated Approach in the Management of Chronic Liver Disease: A Scoping Review. Nutrition Reviews .nuaf001. Rashid A, Gupta A, Adiamah A, West J, Grainge M, Humes DJ(2022). Mortality following appendicectomy in patients with liver cirrhosis: a systematic review and meta-analysis. World Journal of Surgery .46(3):531–541. Ahmed MM, Elfauomy M, ElZohry HA, Ammar K, Elfauomy M, Helal A(2023). Risk Stratification in Cirrhotic Patients with Emergent Surgery. The Egyptian Journal of Hospital Medicine .90(2):2406–2412. Daga LKD, Jamias JD(2025). Association of ALBI Grade, APRI Score, and ALBI-APRI Score with Postoperative Outcomes among Patients with Liver Cirrhosis after Non-hepatic Surgery. Acta Medica Philippina . 59(10):74. Salah EM, Marwan IK, Badawy MT, El Disoki AI, Sallam AN(2025). The Ability of the Albumin-Bilirubin Grade to Predict the Short-Term Outcomes & Complications Following Hepatic Resection. The Egyptian Journal of Surgery . 44(1):91–97. Newman KL, Johnson KM, Cornia PB, Wu P, Itani K, Ioannou GN(2020). Perioperative Evaluation and Management of Patients With Cirrhosis: Risk Assessment, Surgical Outcomes, and Future Directions. Clinical Gastroenterology and Hepatology . 18(11):2398–2414.e2393. Zaharia R, Morarasu S, Ivanov AA, Dimofte GM, Lunca S(2025). Predicting Outcomes in Hepatocellular Carcinoma Surgery: ALBI is the Better Tool. An Observational Cohort Study. Chirurgia (Bucharest, Romania: 1990) . 120(5):555–565. Wong WG, Perez Holguin RA, Tarren AY, Shen C, Vining C, Peng JS, et al (2022). Albumin-bilirubin score is superior to platelet‐albumin‐bilirubin score and model for end‐state liver disease sodium for predicting posthepatectomy liver failure. Journal of surgical oncology . 126(4):667–679. Fragaki M, Sifaki-Pistolla D, Orfanoudaki E, Kouroumalis E (2019). Comparative evaluation of ALBI, MELD, and Child-Pugh scores in prognosis of cirrhosis: is ALBI the new alternative? Annals of Gastroenterology . 32(6):626. Schlosser K, Kao A, Zhang Y, Prasad T, Kasten K, Davis B, et al( 2023). MELD-Na score associated with postoperative complications in hernia repair in non-cirrhotic patients. Hernia . 2019; 23(1):51–59. Ng ZQ, Tan P, Theophilus M. Colorectal surgery in patients with liver cirrhosis: a systematic review. World Journal of Surgery . 47(10):2519–2531. Wetterkamp M, van Beekum CJ, Willis MA, Glowka TR, Manekeller S, Fimmers R, et al(2020). Risk factors for postoperative morbidity and mortality after small bowel surgery in patients with cirrhotic liver disease—A retrospective analysis of 76 cases in a tertiary center. Biology. 9(11):349. Marasco G, Alemanni LV, Colecchia A, Festi D, Bazzoli F, Mazzella G, et al( 2021). Prognostic value of the albumin-bilirubin grade for the prediction of post-hepatectomy liver failure: a systematic review and meta-analysis. Journal of clinical medicine . 10(9):2011. Ruzzenente A, De Angelis M, Conci S, Campagnaro T, Isa G, Bagante F, et al( 2019). The albumin-bilirubin score stratifies the outcomes of Child-Pugh class A patients after resection of hepatocellular carcinoma. Translational Cancer Research . 8(Suppl 3):S233. Yasri S, Wiwanitkit V(2019). MELD-Na score and postoperative complications in hernia repair. Hernia . 23(4):823–823. Andraus W, Pinheiro RS, Lai Q, Haddad LB, Nacif LS, D’Albuquerque LAC, et al( 2017). Abdominal wall hernia in cirrhotic patients: emergency surgery results in higher morbidity and mortality. BMC surgery . 15(1):65. Abbas N, Fallowfield J, Patch D, Stanley AJ, Mookerjee R, Tsochatzis E, et al( 2023). Guidance document: risk assessment of patients with cirrhosis prior to elective non-hepatic surgery. Frontline Gastroenterology . 14(5):359–370. Mansour D, Masson S, Hammond J, Leithead JA, Johnson J, Rahim MN, et al( 2023). British Society of Gastroenterology Best Practice Guidance: outpatient management of cirrhosis–part 3: special circumstances. Frontline Gastroenterology . 14(6):474–482. Tsai T-J, Syu K-J, Huang X-Y, Liu YS, Chen C-W, Chang Y-Y, et al(2026). Postoperative Survival Analysis of Elective Colorectal Cancer Surgery with Liver Cirrhosis: A Propensity-Matched Study. Current Oncology . 33(1):29. Zhu Q, Chen D, Lou Y, Xie X, Wu Y, Wang Z, et al( 2023). Baseline ALBI grade predicts benefits after splenectomy for cirrhotic patients with hypersplenism. Journal of Gastrointestinal Surgery . 27(6):1130–1140. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9457480","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":630044687,"identity":"c9e9f84f-8031-4a24-9999-69592e7d7884","order_by":0,"name":"Tasneem Khaled","email":"data:image/png;base64,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","orcid":"","institution":"Assiut University","correspondingAuthor":true,"prefix":"","firstName":"Tasneem","middleName":"","lastName":"Khaled","suffix":""},{"id":630044688,"identity":"11c4f6fc-654d-492d-a6ee-625abc6b858e","order_by":1,"name":"M A Mekky","email":"","orcid":"","institution":"Assiut University","correspondingAuthor":false,"prefix":"","firstName":"M","middleName":"A","lastName":"Mekky","suffix":""},{"id":630044689,"identity":"f2d887f1-d24b-4f99-8964-42899ccc1215","order_by":2,"name":"Mohamed Omar Abdelmalek","email":"","orcid":"","institution":"Assiut University","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"Omar","lastName":"Abdelmalek","suffix":""},{"id":630044690,"identity":"060a1b6d-42a0-41f3-9e63-053a3dac9452","order_by":3,"name":"Mostafa A Hamad","email":"","orcid":"","institution":"Assiut University","correspondingAuthor":false,"prefix":"","firstName":"Mostafa","middleName":"A","lastName":"Hamad","suffix":""},{"id":630044691,"identity":"90052a95-1e75-41fc-9e30-7ad351f1a42c","order_by":4,"name":"Mohammed Zakaria Abu Rahma","email":"","orcid":"","institution":"Assiut University","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"Zakaria Abu","lastName":"Rahma","suffix":""},{"id":630044692,"identity":"de1dd8b6-7448-423f-9fda-fc2e29c8270d","order_by":5,"name":"Ahmed MM Elkoussy","email":"","orcid":"","institution":"Assiut University","correspondingAuthor":false,"prefix":"","firstName":"Ahmed","middleName":"MM","lastName":"Elkoussy","suffix":""}],"badges":[],"createdAt":"2026-04-18 18:24:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9457480/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9457480/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108383814,"identity":"b8c06ed5-c88e-40e8-896f-990947d11f04","added_by":"auto","created_at":"2026-05-04 05:48:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":294804,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver operating characteristic (ROC) curves comparing the predictive performance of ALBI and MELD-Na scores for postoperative complications in cirrhotic patients undergoing abdominal surgery\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eThe ROC curve demonstrates the diagnostic performance of the Albumin–Bilirubin (ALBI) score and the Model for End-Stage Liver Disease–Sodium (MELD-Na) score in predicting postoperative complications. The ALBI score showed superior discriminative ability compared with the MELD-Na score, with a higher area under the curve (AUC 0.835 vs 0.683). The diagonal reference line represents the performance of a non-informative classifier (AUC = 0.5).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eROC, receiver operating characteristic; AUC, area under the curve; ALBI, Albumin–Bilirubin score; MELD-Na, Model for End-Stage Liver Disease–Sodium.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9457480/v1/13743e8f63bcfb6a31b74a7c.png"},{"id":108383815,"identity":"b1188b0c-ae53-4b88-badd-ca3e937deccf","added_by":"auto","created_at":"2026-05-04 05:48:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":386398,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan–Meier curves of complication-free survival according to MELD-Na (a)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eand ALBI (b) scores risk stratification in cirrhotic patients undergoing abdominal surgery.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients were stratified into low- and high-risk groups based on the optimal cut-off values for each scoring system. The curves demonstrate a lower complication-free survival probability among high-risk patients compared to low-risk patients. Tick marks indicate censored observations, and differences between groups were evaluated using the log-rank test.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMELD-Na, Model for End-Stage Liver Disease–Sodium; ALBI, Albumin–Bilirubin score.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9457480/v1/068958d17527c26246fba80c.png"},{"id":108803784,"identity":"9949a4ef-ba96-4264-850a-26d9d612ffbd","added_by":"auto","created_at":"2026-05-08 15:06:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1207653,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9457480/v1/6f8d6f81-3ed5-4d72-85e8-10cd5a94eb2d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative Performance of ALBI score versus MELD-Na Score in Predicting Postoperative Outcomes Following Elective Major Abdominal Surgery in Cirrhotic Patients","fulltext":[{"header":"Background","content":"\u003cp\u003ePatients with liver cirrhosis undergoing surgery represent a high-risk population due to the complex physiological derangements associated with the disease, including portal hypertension, coagulopathy, and impaired synthetic and immune function. These factors contribute to substantially increased perioperative morbidity and mortality (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral prognostic scoring systems have been developed to stratify surgical risk in this population. The Child-Turcotte-Pugh (CTP) classification and the Model for End-Stage Liver Disease (MELD) score are among the most widely cited tools for perioperative risk assessment (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). However, their predictive accuracy and clinical utility may vary across different clinical contexts and geographic regions. More recently, the Albumin-Bilirubin (ALBI) score and the MELD-Na score have emerged as objective, liver-specific alternatives for preoperative risk stratification (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough multiple studies have compared the performance of ALBI and MELD-Na against CTP and MELD scores in predicting postoperative morbidity, mortality, and liver failure (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), there remains a lack of consensus\u0026mdash;particularly from a hepatology perspective\u0026mdash;regarding which score offers superior reliability and accuracy in predicting outcomes following abdominal surgery in cirrhotic patients (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). The present study was designed to address this gap by conducting a comprehensive evaluation of the predictive performance of ALBI and MELD-Na scores in cirrhotic patients undergoing elective major abdominal surgery.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis was a single-center, prospective observational cohort study conducted at Assiut University Hospitals, Egypt. The study enrolled cirrhotic patients admitted for elective major abdominal surgery under anesthesia.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eA total of \u003cb\u003e57\u003c/b\u003e cirrhotic patients undergoing elective major abdominal surgery between January 2024 and August 2025 were included. Written informed consent was obtained from all participants. All surgical procedures were performed by a single surgical team to ensure consistency.\u003c/p\u003e \u003cp\u003e \u003cb\u003e**Inclusion criteria**\u003c/b\u003e were adult patients (\u0026ge;\u0026thinsp;18 years) with confirmed liver cirrhosis scheduled for elective major intra-abdominal surgery.\u003c/p\u003e \u003cp\u003eThe diagnosis of liver cirrhosis was established if any one of the following findings was present (i) compatible intraoperative gross findings. (ii) evidence of portal hypertension (ascites, gastroesophageal varices, or hepatic encephalopathy) in patients with liver disease, (iii) compatible radiologic findings. Cirrhosis severity was classified according to the D\u0026rsquo;Amico classification, with all patients being compensated (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003e**Major surgical procedures\u003c/b\u003e** were defined according to the Delphi consensus definition of the European Surgical Association as operations involving significant physiological stress, entry into a body cavity, extensive tissue dissection, or expected substantial perioperative risk (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Procedures included hepatocellular carcinoma (HCC) resection, laparoscopic and open cholecystectomy, common bile duct (CBD) exploration, bilio-enteric shunts, pancreatic surgery (Whipple and distal pancreatectomy), splenectomy, and repair of recurrent ventral and inguinal hernias.\u003c/p\u003e \u003cp\u003e \u003cb\u003e**Exclusion criteria**\u003c/b\u003e were acute liver failure without underlying cirrhosis, prior liver transplantation, malignancies other than HCC and missing preoperative laboratory data.\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003e \u003cb\u003e**Preoperative assessment**\u003c/b\u003e included a standardized clinical examination, vital signs, and evaluation of liver dysfunction manifestations. Laboratory investigations comprised complete blood count, liver function tests (total protein, albumin, bilirubin, and transaminases), coagulation profile (international normalized ratio [INR]), renal function tests (serum urea, creatinine), serum electrolytes (sodium, potassium, calcium, and magnesium). Neurological status was assessed using the Glasgow Coma Scale. Physical status was classified using the American Society of Anesthesiologists (ASA) classification (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). ALBI and MELD-Na scores were calculated preoperatively to evaluate liver function and predict postoperative outcomes.\u003c/p\u003e \u003cp\u003e \u003cb\u003e**Intraoperative data**\u003c/b\u003e included surgical procedure type, duration, anesthesia type, estimated blood loss, transfusion requirements, and occurrence of intraoperative organ injury.\u003c/p\u003e \u003cp\u003e \u003cb\u003e**Postoperative follow-up**\u003c/b\u003e was conducted at day 1, day 7, and day 30. The primary outcomes were overall morbidity and 30-day mortality. Morbidity was defined as any surgical complication or hepatic decompensation occurring during follow-up. Hepatic decompensation was defined as the concurrent presence of clinical deterioration and biochemical evidence of worsening liver function. Surgical complications included surgical site infection (superficial, deep, or organ space), wound dehiscence, bile leak, and postoperative bleeding requiring transfusion. Complications were graded according to the Clavien-Dindo classification, with grades I-II defined as minor and grades III-V as major (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eScoring Systems\u003c/h3\u003e\n\u003cp\u003e**MELD-Na score** was calculated using the formula:\u003c/p\u003e \u003cp\u003e(0.957 \u0026times; ln [creatinine mg/dL]\u0026thinsp;+\u0026thinsp;0.378 \u0026times; ln [total bilirubin mg/dL]\u0026thinsp;+\u0026thinsp;1.120 \u0026times; ln [INR]\u0026thinsp;+\u0026thinsp;0.643) \u0026times; 10, with sodium values capped between 125 and 137 mmol/L (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Risk categories were defined as low (\u0026le;\u0026thinsp;9), moderate (\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), and high (\u0026ge;\u0026thinsp;20) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e**ALBI score** was calculated as:\u003c/p\u003e \u003cp\u003e(log10 bilirubin [\u0026micro;mol/L] \u0026times; 0.66) + (albumin [g/L] \u0026times; \u0026minus;\u0026thinsp;0.085). Grades were defined as grade 1 (\u0026le; \u0026minus;\u0026thinsp;2.60, good liver function), grade 2 (\u0026gt; \u0026minus;\u0026thinsp;2.60 to \u0026le; \u0026minus;\u0026thinsp;1.39, moderate impairment), and grade 3 (\u0026gt; \u0026minus;\u0026thinsp;1.39, poor function) (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAnalyses were performed using SPSS (version 26).\u003c/p\u003e \u003cp\u003eData presented as Median (IQR) for continuous and % for categorical variables.\u003c/p\u003e \u003cp\u003eMann\u0026ndash;Whitney U for continuous data; Chi-square/Fisher\u0026rsquo;s exact for categorical data.\u003c/p\u003e \u003cp\u003eROC curves (AUC) to measure performance, Youden index for cut-offs, and DeLong test for comparisons.\u003c/p\u003e \u003cp\u003eLogistic Regression for Odds Ratios (OR) and Cox Proportional Hazards for Hazard Ratios (HR). Kaplan\u0026ndash;Meier curves with Log-rank test to compare complication-free survival. p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Characteristics\u003c/h2\u003e \u003cp\u003eA total of 57 patients were included, with a median age of 61.0 years (IQR: 54.0\u0026ndash;67.0). The majority were male (63.2%). Hepatitis C virus (HCV) infection was the predominant etiology of cirrhosis (61.4%). Most patients were classified as Child-Pugh class A (89.5%). There were 6 patients who were classified as Child-Pugh Class B and C due to higher levels of bilirubin (biliary obstruction) not due to liver cell failure. The most common surgical procedures were HCC resection and cholecystectomy, each accounting for 38.6% of cases \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline demographic, clinical characteristics, and postoperative outcomes of cirrhotic patients undergoing abdominal surgery (N\u0026thinsp;=\u0026thinsp;57).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%) or Median (IQR)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (years) Median (IQR)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.0 (57.0\u0026ndash;68.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eMale: Female\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (63.2%) : 21 (36.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEtiology of Cirrhosis\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eHCV: HBV: Others\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (61.4%): 11 (19.3%): 11 (19.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild\u0026ndash;Pugh Score\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eChild A: Child B: Child C\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 (89.5%): 5 (8.8%) :1 (1.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiver Scores (Median [IQR])\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMELD-Na Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.0 (8.0\u0026ndash;11.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALBI Score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026minus;2.52 (\u0026minus;\u0026thinsp;2.93 to \u0026minus;\u0026thinsp;2.09)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of Surgery\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCC Resection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (38.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCholecystectomy (+- CBD exploration)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (38.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePancreatic Surgery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (7.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers (Splenectomy/bilio-enteric shunts / Hernia repair)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (15.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOperative characteristics and outcome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of Surgery (minutes)\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125.0 (67.0\u0026ndash;160.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntraoperative Bleeding required Blood Transfusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (49.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostoperative Bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (7.1%) *\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital Stay (days) Median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.0 (2.0\u0026ndash;7.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePostoperative complications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (31.58%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- \u003cb\u003eNature of Complications\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eHepatic/ medical complications: surgical complications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (83.3%) : 3 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- \u003cb\u003eComplications Severity (Clavien\u0026ndash;Dindo Classification)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eMinor (Grade I\u0026ndash;II) : Major (Grade III\u0026ndash;IV): Death (Grade V)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (72.2%) : 4 (27.8%) : 1(5.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e- \u003cb\u003eClinical Presentation of Complications\u003c/b\u003e (N\u0026thinsp;=\u0026thinsp;18 )\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNew onset / Worsening Ascites\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (66.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatic Encephalopathy (HE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGastrointestinal (GIT) Bleeding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePersistent Jaundice (30-day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeath (at day 7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(5.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eData are presented as number (%) or median (interquartile range, IQR). Postoperative complications were classified according to the Clavien\u0026ndash;Dindo classification system. Hepatic/medical complications included new-onset or worsening ascites, hepatic encephalopathy, gastrointestinal bleeding, and persistent jaundice within 30 days after surgery.\u003c/p\u003e \u003cp\u003eAbbreviations:\u003c/p\u003e \u003cp\u003eHCV, hepatitis C virus; HBV, hepatitis B virus; MELD-Na, Model for End-Stage Liver Disease\u0026ndash;Sodium; ALBI, Albumin\u0026ndash;Bilirubin score; HCC, hepatocellular carcinoma; CBD, common bile duct; SSI, surgical site infection; GIT, gastrointestinal tract; IQR, interquartile range.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePostoperative Outcomes\u003c/h3\u003e\n\u003cp\u003eThe median postoperative hospital stay was 3.0 days (IQR: 2.0\u0026ndash;7.0). Postoperative bleeding occurred in 7.1% of patients. Overall morbidity was observed in 31.6% of patients. According to the Clavien-Dindo classification, 72.2% of complications were minor (grades 1\u0026ndash;2) and 27.8% were major (grades 3\u0026ndash;5). The majority of complications were hepatic or medical in nature (83.3%), with surgical complications accounting for 16.7%. All complications occurred within 30 days postoperatively except for the patient who died, whose complications were noted on day 7. The most common clinical presentations were new-onset or worsening ascites (66.7%), hepatic encephalopathy (27.8%), gastrointestinal bleeding (22.2%), and persistent jaundice (22.2%). The patient who died experienced both hepatic encephalopathy and persistent jaundice. Recorded surgical complications included colonic injury, surgical site infection, and bile leak \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eROC-derived diagnostic performance of MELD-Na and ALBI scores for prediction of postoperative morbidity in cirrhotic patients undergoing abdominal surgery.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMELD-Na score (\u0026ge;\u0026thinsp;8.90)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eALBI score (\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;2.42)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUC (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.683 (0.536\u0026ndash;0.830)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.835 (0.710\u0026ndash;0.960)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value (AUC)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.027*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDeLong Test (Comparison)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUC after exclusion of OJ (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.629 (0.459\u0026ndash;0.800)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.823 (0.667\u0026ndash;0.979)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep-value after exclusion of OJ (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.171\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.\u003cb\u003e001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYouden Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.633\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive Predictive Value (PPV) (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e43.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative Predictive Value (NPV) (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e93.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall Accuracy (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e78.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePositive Likelihood Ratio (LR+)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNegative Likelihood Ratio (LR\u0026minus;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.37 (1.00\u0026ndash;11.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e23.20 (4.51\u0026ndash;119.34)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP-value (Chi-Square)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eCut-off values were determined using the Youden index from ROC curve analysis. Diagnostic performance parameters including sensitivity, specificity, predictive values, likelihood ratios, and overall accuracy were calculated for the optimal cut-off points. DeLong\u0026rsquo;s test was used to compare the area under the ROC curves (AUC) between MELD-Na and ALBI scores. Additional analysis was performed after exclusion of patients with obstructive jaundice (OJ) to assess the stability of the predictive performance.\u003c/p\u003e \u003cp\u003eAbbreviations:\u003c/p\u003e \u003cp\u003eMELD-Na, Model for End-Stage Liver Disease\u0026ndash;Sodium; ALBI, Albumin\u0026ndash;Bilirubin score; AUC, area under the receiver operating characteristic curve; CI, confidence interval; PPV, positive predictive value; NPV, negative predictive value; LR+, positive likelihood ratio; LR\u0026minus;, negative likelihood ratio; OJ, obstructive jaundice; ROC, receiver operating characteristic.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePredictive Performance of ALBI and MELD-Na\u003c/h2\u003e \u003cp\u003eThe ALBI score demonstrated significantly higher predictive accuracy for in-hospital morbidity compared to MELD-Na (AUC: 0.835 vs. 0.683; DeLong *p* = 0.001) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e After excluding patients with obstructive jaundice, ALBI remained a significant predictor (*p* = 0.001), whereas MELD-Na did not (*p* = 0.171). At the optimal cut-off value of \u0026ge; \u0026minus;\u0026thinsp;2.42 (Youden index: 0.633), ALBI achieved a sensitivity of 88.9%, specificity of 74.4%, and negative predictive value of 93.5%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe incidence of postoperative complications was significantly higher in the ALBI high-risk group compared to the low-risk group (61.5% vs. 6.5%; *p* \u0026lt; 0.001). In contrast, no significant difference was observed across MELD-Na risk groups (*p* = 0.052) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePostoperative complication rates, severity (Clavien\u0026ndash;Dindo classification), and hospital stay according to MELD-Na and ALBI risk groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Complications n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eComplicated\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMinor (Grade I\u0026ndash;II) n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMajor (Grade III\u0026ndash;IV-V) n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHospital stay median IQR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP-value*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eMELD-Na Score\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Risk (\u0026lt;\u0026thinsp;\u003cb\u003e8.90\u003c/b\u003e)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e22 (81.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (18.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (14.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.052\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.0(2.0\u0026ndash;7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.735\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh Risk (\u0026ge;\u0026thinsp;\u003cb\u003e8.90\u003c/b\u003e) n\u0026thinsp;=\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e17 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (43.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (30.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.0(2.0\u0026ndash;7.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALBI Score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Risk (\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2.42)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e29 (93.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.0(2.0\u0026ndash;7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh Risk (\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;2.42)\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e10 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (61.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (42.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 (19.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4.0(2.0-7.425)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e* Statistically significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e*P-values calculated using Chi-square or Mann-Whitney U test as appropriate\u003c/p\u003e \u003cp\u003eAbbreviations:\u003c/p\u003e \u003cp\u003eMELD-Na, Model for End-Stage Liver Disease\u0026ndash;Sodium; ALBI, Albumin\u0026ndash;Bilirubin score; IQR, interquartile range\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRegression and Survival Analyses\u003c/h2\u003e \u003cp\u003eIn univariate logistic regression, ALBI was associated with a substantially higher odds of complications (OR: 23.20) compared to MELD-Na (OR: 3.37). However, both scores remain statistically significant predictors In the multivariate analysis adjusting for age, with ALBI demonstrating stronger associations with in-hospital morbidity (OR: 24.0; 95% CI: 1.8\u0026ndash;322.1; *p* = 0.016), compared to MELD-Na score (OR: 3.399; 95% CI: 1.010\u0026ndash;11.437; p\u0026thinsp;=\u0026thinsp;0.048) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e, highlighting ALBI score potential as a more discriminative risk stratification tool. Age was not a significant predictor in either model \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable Cox Proportional Hazards Models for Predictors of Complication-Free survival\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel 1 (ALBI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel 2 (MELD-NA)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR (95%Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95%Cl)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient Age\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.015 (.967-1.065)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.546\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.013 (.956-1.062)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.605\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiver score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6.307(1.418\u0026ndash;28.053)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2.065 (.720-5.925)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e.178\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eLiver Score refers to Child B/C, MELD (\u0026ge;\u0026thinsp;8.90), or ALBI (\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;2.42) respectively in each model.\u003c/p\u003e \u003cp\u003eEach model included patient age and one liver scoring system to avoid multicollinearity\u003c/p\u003e \u003cp\u003eNote: Multivariable Cox proportional hazards regression models were used to assess predictors of outcome. Hazard ratios (HR) with 95% confidence intervals (CI) were calculated. Separate models were constructed for MELD-Na and ALBI scores to avoid collinearity. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eAbbreviations:\u003c/p\u003e \u003cp\u003eHR, hazard ratio; CI, confidence interval; ALBI, Albumin\u0026ndash;Bilirubin score; MELD-Na, Model for End-Stage Liver Disease\u0026ndash;Sodium.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and Multivariate Logistic Regression Analysis for Predictors of In-hospital Morbidity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnivariate OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMultivariate OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.007 (.954-1.063)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.010 (.955-1.067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of surgery (minutes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.996 (.986-1.006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePresence of portal hypertension and varices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.115 (0.317\u0026ndash;3.921)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of anesthesia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.417 (0.137\u0026ndash;14.641)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAscites\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.450 (0.430\u0026ndash;4.888)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.549\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eALBI score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;2.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.773 (3.872-100.967)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.017 (4.616-124.968)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMELD-Na score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;8.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;8.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.365(1.003\u0026ndash;11.285)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.399 (1.010\u0026ndash;11.437)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePresence of Jaundice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.400(.462-12.471)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eNote: Univariate and multivariate logistic regression analyses were performed to identify predictors of in-hospital morbidity. Odds ratios (OR) with 95% confidence intervals (CI) were calculated. Variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant. Reference categories are indicated as r(1(\u003c/p\u003e \u003cp\u003eOR\u0026thinsp;=\u0026thinsp;odds ratio; CI\u0026thinsp;=\u0026thinsp;confidence interval; r(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)= reference category.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eKaplan-Meier analysis demonstrated a significant difference in complication-free survival between ALBI risk groups (log-rank *p* = 0.005), with shorter survival observed in the high-risk group \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb\u003cb\u003e).\u003c/b\u003e No significant difference was observed for MELD-Na risk groups (log-rank *p* = 0.168\u003cb\u003e) (\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea\u003cb\u003e).\u003c/b\u003e In Cox proportional hazards analysis, ALBI was significantly associated with time to complication (HR: 6.307; 95% CI: 1.418\u0026ndash;28.053; *p* = 0.016), while MELD-Na was not (HR: 2.065; 95% CI: 0.720\u0026ndash;5.925; *p* = 0.178) \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKaplan-Meier curves for complication-free survival according to ALBI and MELD-Na risk groups.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrognostic Model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEvents (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCensored n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean Survival Time (Days) [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMedian Survival (Days) [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLog-Rank P-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALBI Risk\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (68.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Risk (\u0026thinsp;\u0026lt;\u0026thinsp;\u0026minus;\u0026thinsp;2.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (93.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.36\u003c/p\u003e \u003cp\u003e(8.51\u0026ndash;10.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNot reached\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh Risk (\u0026thinsp;\u0026ge;\u0026thinsp;\u0026minus;\u0026thinsp;2.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (38.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.07\u003c/p\u003e \u003cp\u003e(5.37\u0026ndash;8.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.00\u003c/p\u003e \u003cp\u003e(2.76\u0026ndash;11.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMELD-Na Risk\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (68.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.168\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow Risk (\u0026lt;\u0026thinsp;8.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (81.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.44 (7.23\u0026ndash;9.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNot reached\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh Risk (\u0026ge;\u0026thinsp;8.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.63\u003c/p\u003e \u003cp\u003e(5.95\u0026ndash;9.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.70\u003c/p\u003e \u003cp\u003e(5.25\u0026ndash;12.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eKaplan\u0026ndash;Meier survival analysis was performed to evaluate complication-free survival according to liver function risk groups based on ALBI and MELD-Na scores. Event was defined as the occurrence of postoperative complications. The log-rank test was used to compare survival distributions between risk groups. Data are presented as number (%) or mean survival time with 95% confidence intervals (CI). Median survival time was reported when estimable. \u0026ldquo;Not reached\u0026rdquo; indicates that the median survival time could not be calculated because fewer than 50% of patients experienced the event during follow-up.\u003c/p\u003e \u003cp\u003eAbbreviations:\u003c/p\u003e \u003cp\u003eALBI, Albumin\u0026ndash;Bilirubin score; MELD-Na, Model for End-Stage Liver Disease\u0026ndash;Sodium; CI, confidence interval.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe revolutionary improvement in long-term survival in cirrhotic patients, due to new management guidelines and antiviral therapies over the last two decades, has made predictions of perioperative morbidity and mortality in cirrhotic patients undergoing non-transplant surgery as a clinical necessity (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). In addition, clinicians increasingly face the dilemma of balancing surgical necessity against hepatic risk. Establishing reliable, objective, and easily applicable prognostic tools is therefore critical to stratify risks, improve surgical decision-making and optimize surgical outcome (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRecently, the Albumin\u0026ndash;Bilirubin (ALBI) score and MELD-Na have emerged as a more accurate and reliable prognostic score than traditional scoring systems such as the Child-Pugh-Turcotte (CTP) score, the Model for End-Stage Liver Disease (MELD) (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Although non-transplant abdominal surgeries represent nearly 50% of surgical procedures performed in cirrhotic patients, direct comparison between ALBI and MELD-Na has not been performed regarding major elective abdominal surgeries (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis prospective cohort study provides a comparative evaluation of the ALBI and MELD-Na scores for predicting postoperative outcomes in cirrhotic patients undergoing elective major abdominal surgery. The principal finding is that the ALBI score demonstrated superior predictive accuracy for postoperative morbidity compared to the MELD-Na score, as evidenced by a higher AUC in ROC analysis, stronger independent association in multivariate regression, and better discrimination of complication-free survival on Kaplan-Meier analysis. These findings suggest that ALBI may represent a more reliable tool for preoperative risk stratification in this specific clinical context.\u003c/p\u003e \u003cp\u003eThe superior discriminative ability of the ALBI score observed in this study aligns with a growing body of evidence supporting its utility in surgical populations. The AUC of 0.835 for ALBI indicates good to excellent predictive performance, whereas the AUC of 0.683 for MELD-Na falls within the range considered poor to fair. This difference was statistically significant by DeLong test (p\u0026thinsp;=\u0026thinsp;0.001), reinforcing the notion that ALBI may be a more sensitive indicator of hepatic functional reserve in the perioperative setting.\u003c/p\u003e \u003cp\u003eSeveral factors may account for this difference. First, ALBI relies exclusively on albumin and bilirubin, two direct measures of hepatic synthetic capacity and excretory function, without being influenced by extra hepatic factors such as renal function or coagulation parameters. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Second, the persistence of ALBI\u0026rsquo;s predictive power after excluding patients with obstructive jaundice\u0026mdash;a scenario in which MELD-Na lost significance\u0026mdash;further supports its robustness as a liver-specific tool less susceptible to biliary pathology.\u003c/p\u003e \u003cp\u003eIn a retrospective analytic study from the NSQIP database, \u003cb\u003eTaylor et al\u003c/b\u003e reported that ALBI was an excellent predictor of the overall post-operative mortality (AUC 0.80) and morbidity (AUC 0.66) in cirrhotic patients particularly in gastrointestinal surgery. However, both scores were equal in prediction of post-operative morbidity in non-gastrointestinal surgery. Notably, ALBI was superior to MELD-Na in predicting outcomes despite involving other types of surgeries like lung resections, elective colectomy, and adrenalectomy, which support the applicability of ALBI across different surgical procedures (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn an Observational Cohort Study, \u003cb\u003eZaharia et al\u003c/b\u003e demonstrated that ALBI is the most accurate and objective score for identifying high-risk patients undergoing liver resection for HCC (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). For instance, a multicenter study by Wang et al. reported superior performance of ALBI over MELD in predicting post-hepatectomy liver failure (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Similarly, a meta-analysis by \u003cb\u003eLiu\u003c/b\u003e et al. concluded that ALBI demonstrated comparable or better prognostic accuracy than MELD across various surgical and nonsurgical settings (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition, other studies demonstrated that the ALBI score not only associated with postoperative hepatic decompensation and in-hospital mortality, but comparable to both MELD and CTP scores with optimum balance between sensitivity and specificity for predicting mortality and morbidity (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). The present study extends this evidence to a heterogeneous cohort of cirrhotic patients undergoing diverse major abdominal procedures, reinforcing the generalizability of these observations.\u003c/p\u003e \u003cp\u003e\u003cb\u003eKaltenbach et al\u003c/b\u003e advocated, in their review, the MELD-Na as a strong predictor morbidity and mortality in all hepatic and non-hepatic surgeries in cirrhotic patients. In addition, \u003cb\u003eSchlosser et al\u003c/b\u003e demonstrate that MELD-Na is an accurate reliable prognostic score for morbidity and mortality in ventral hernias repair in cirrhotic patients. both studies included patients in emergency conditions in which hyponatremia and hypoalbuminemia significantly impact postoperative prognosis (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe overall postoperative morbidity rate reported in our study (31.6%) is comparable to previous literature which reported postoperative complication rates in cirrhotic patients undergoing abdominal surgery from 25% to 40%, depending on the liver functional reservoir and surgical complexity (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). On the other hand, other studies reported higher rates of complications due to involving emergency patients in their retrospective data analysis (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe predominance of hepatic/medical complications (83.3%) over surgical complications (16.7%) in this cohort highlights the central role of underlying liver disease in shaping postoperative outcomes. New-onset or worsening ascites was the most common manifestation of hepatic decompensation, occurring in 66.7% of patients with complications. This finding underscores the importance of preoperative assessment of portal hypertension and synthetic function\u0026mdash;domains directly captured by the ALBI score through its albumin and bilirubin components. In contrast, MELD-Na\u0026rsquo;s inclusion of INR and creatinine may be more relevant to coagulopathic or renal complications, which were less frequent in this cohort.\u003c/p\u003e \u003cp\u003eThe optimal ALBI cut-off value of \u0026ge; \u0026minus;\u0026thinsp;2.42 identified in this cohort achieved a negative predictive value of 93.5%, indicating that patients below this threshold are at very low risk for postoperative complications. This high NPV has direct clinical utility: it may help identify a subset of compensated cirrhotic patients who can proceed to elective surgery with minimal additional perioperative intervention. Conversely, the high-risk ALBI group experienced a markedly higher complication rate (61.5% vs. 6.5%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting that these patients warrant intensified perioperative optimization, closer monitoring, or consideration of alternative treatment strategies.\u003c/p\u003e \u003cp\u003eThe lack of significant differentiation across MELD-Na risk groups (p\u0026thinsp;=\u0026thinsp;0.052) in this cohort merits careful interpretation. While the marginal trend toward significance may reflect limited statistical power due to sample size, it also raises the possibility that MELD-Na\u0026rsquo;s performance is attenuated in well-compensated populations. The majority of patients in this study were Child-Pugh class A (89.5%), representing a lower-risk subset where subtle differences in liver function may not be captured by MELD-Na, which was originally developed to predict mortality in end-stage liver disease. ALBI\u0026rsquo;s ability to stratify risk even within this predominantly compensated cohort underscores its potential advantage in surgical populations with milder liver dysfunction.\u003c/p\u003e \u003cp\u003eMany prospective and retrospective studies agree to the present study that the ALBI score represents a simple reliable tool to stratify the risk of post hepatectomy liver failure which agrees with our study results (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). However, \u003cb\u003eKaltenbach et al\u003c/b\u003e concluded that liver scores such as the CTP Score, MELD-Na scores, MRS, and the VOCAL-Penn Score are powerful tools to help risk stratify patients based on preoperative factors. This could be justified by the presence of hypoalbuminemia and hyponatremia, which are strong indicators for sarcopenia and frailty that increase perioperative risks. However, these scores should be used parallel to good clinical judgment (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWith respect to ventral hernias, \u003cb\u003eSchlosser et al\u003c/b\u003e advocated MELD-Na score as a significant reliable risk stratifying score in a retrospective NSQIP data analysis. In contrast, \u003cb\u003eYasri et al\u003c/b\u003e concluded in their review that MELD Na score could not be used as a reliable score for risk stratification or as areal reflection for liver functional reservoir because of its great affection of by laboratory investigation, INR and creatinine, which may be impaired even with compensated liver condition (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAhmed et al\u003c/b\u003e concluded that MELD, PALBI, and ALBI are reliable scores for risk stratification in cirrhotic patients with emergent surgery. This is due to hypoalbuminemia related to emergency conditions which enhance clinicians\u0026rsquo; insight into postoperative morbidity and mortality (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMultivariate analysis confirmed ALBI as an independent predictor of in-hospital morbidity (OR 24.0; 95% CI: 1.8\u0026ndash;322.1; p\u0026thinsp;=\u0026thinsp;0.016), and also does the MELD-Na score but with lower association (OR: 3.399; 95% CI: 1.010\u0026ndash;11.437; p\u0026thinsp;=\u0026thinsp;0.048). The wide confidence interval for ALBI reflects the limited sample size but does not detract from the strength of the point estimate. Importantly, age was not a significant confounder in either model, suggesting that the observed associations are primarily driven by liver-specific physiology rather than patient demographics.\u003c/p\u003e \u003cp\u003eCox proportional hazards analysis further substantiated these findings, demonstrating a significant difference in complication-free survival between ALBI risk groups (log-rank p\u0026thinsp;=\u0026thinsp;0.005) and an independently associated hazard ratio of 6.307. The absence of a similar survival difference for MELD-Na risk groups reinforces the conclusion that ALBI provides superior prognostic discrimination for time-to-event outcomes in this population.\u003c/p\u003e \u003cp\u003eIn some analytic studies, ALBI score was considered an independent predictor for post hepatectomy bile leak (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). However, The British Society of Gastroenterology (BSG) guidance addresses that portal hypertension is an independent predictor for morbidity and 30-day mortality in cirrhotic patients undergoing colorectal surgery; they explained that the higher risk in the presence of portal hypertension is due to altered intraoperative hemodynamics, ascites, and coagulopathy (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn a Propensity-Matched Study, \u003cb\u003eTsai et al\u003c/b\u003e concluded that Hypoalbuminemia (\u0026lt;\u0026thinsp;3.5 g/dL) was identified as an independent predictor of mortality, underscoring the importance of preoperative nutritional assessment and optimization. In addition, this explains the superiority of ALBI as an accurate predictor and risk stratification score (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Moreover, \u003cb\u003eZhu et al\u003c/b\u003e, in their retrospective study which included 71 patients, concluded that baseline characteristics, such as ALBI grade and age, were cornerstones to assess perioperative risks and benefits of splenectomy for cirrhotic (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe principal strengths of this study include its prospective design, standardized surgical and anesthetic protocols, use of validated outcome definitions (Clavien-Dindo classification, Delphi consensus for major surgery), and rigorous statistical methodology including ROC analysis with DeLong comparison, multivariate regression, and time-to-event analysis.\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. First, the single-center design and relatively small sample size (n\u0026thinsp;=\u0026thinsp;57) limit the precision of effect estimates and may restrict generalizability to other populations or healthcare settings. Second, the predominance of patients with Child-Pugh class A cirrhosis and HCV-related disease reflects the local epidemiology but may not represent the broader spectrum of cirrhosis seen in other regions. Third, the limited number of events constrained the number of variables that could be included in multivariate models, potentially leaving residual confounding unaddressed. Fourth, the study did not assess inter-rater reliability for clinical outcome adjudication, although standardized definitions were used to minimize variability. Finally, longer-term outcomes beyond 30 days were not evaluated, and the impact of preoperative interventions (e.g., nutritional optimization, portal pressure reduction) was not captured.\u003c/p\u003e \u003cp\u003eThe findings of this study support the use of the ALBI score as a primary risk stratification tool in cirrhotic patients being considered for elective major abdominal surgery. Its high negative predictive value may facilitate the safe identification of low-risk patients, while its ability to discriminate against risk within compensated cirrhosis populations addresses a key gap in current perioperative assessment.\u003c/p\u003e \u003cp\u003eFuture research should focus on external validation of the ALBI cut-off value identified in this study across diverse geographic and etiologic populations. Prospective multicenter studies with larger sample sizes are needed to confirm the independent prognostic value of ALBI relative to MELD-Na and other emerging biomarkers. Additionally, the integration of ALBI with dynamic measures of portal hypertension (e.g., hepatic venous pressure gradient) or frailty assessments may further refine risk prediction. Finally, interventional studies evaluating whether ALBI-guided perioperative optimization protocols can improve outcomes would be a logical next step toward translating these findings into clinical practice.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this prospective cohort of predominantly compensated cirrhotic patients undergoing elective major abdominal surgery, the ALBI score demonstrated superior predictive accuracy for postoperative morbidity compared to the MELD-Na score. Its strong negative predictive value, independent association with complications, and ability to discriminate survival differences support its utility as a reliable and clinically actionable risk stratification tool. These findings advocate for the integration of ALBI into preoperative assessment protocols and warrant further validation in larger, multicenter cohorts.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eALBI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAlbumin\u0026ndash;Bilirubin score\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eASA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAmerican Society of Anesthesiologists\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eAUC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eArea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBSG\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBritish Society of Gastroenterology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCBC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eComplete blood count\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCBD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommon bile duct\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eClavien-Dindo\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eCTP\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChild-Turcotte-Pugh\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGCS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlasgow Coma Scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eGIT\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGastrointestinal tract\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHBV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHepatitis B virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHCC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHepatocellular carcinoma\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHCV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHepatitis C virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eHRs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHazard ratios\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eINR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInternational Normalized Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eIQR\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eInterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLR\u0026minus;\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNegative likelihood ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eLR+\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePositive likelihood ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMELD\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eModel for End- Stage Liver Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMELD-Na\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eModel for End-Stage Liver Disease\u0026ndash;Sodium\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNPV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNegative predictive value\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eOJ\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eObstructive jaundice\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eORs\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOdds ratios\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003ePPV\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePositive predictive value\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eROC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSPSS\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStatistical Package for the Social Sciences\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eSSI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSurgical site infection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eEthical Considerations\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of Assiut University Faculty of Medicine \u003cstrong\u003e(IRB No. 17200794)\u003c/strong\u003e and was conducted in accordance with the principles of the Declaration of Helsinki (7th revision, 2013) and the Declaration of Istanbul (2018). The study was registered at \u003cstrong\u003eClinicalTrials.gov (NCT05503836).\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAll patients included in this research gave written informed consent to publish the data contained within this study.\u003c/p\u003e\n\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe data set used and analyzed during the current study has been submitted for review and available upon request.\u003c/p\u003e\n\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or non-profit sectors.\u003c/p\u003e\n\n\u003cul type=\"disc\"\u003e\n\u003cli\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAuthors contributed equally to the writing of this paper\u003c/p\u003e\n\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e\u003cem\u003eEuropean Association for the Study of the Liver (EASL)(2025).\u003c/em\u003e EASL Clinical Practice Guidelines: Management of hepatocellular carcinoma. \u003cem\u003eJournal of Hepatology\u003c/em\u003e. 69(1):182\u0026ndash;236.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMahmud N, Fricker ZP, McElroy LM, Qayed E, Wong RJ, \u003cem\u003eIoannou GN(2025).\u003c/em\u003e ACG clinical guideline: perioperative risk assessment and management in patients with cirrhosis. \u003cem\u003eOfficial journal of the American College of Gastroenterology| ACG\u003c/em\u003e. 120(9):1968\u0026ndash;1984.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWong M, \u003cem\u003eBusuttil RW(2019).\u003c/em\u003e Surgery in patients with portal hypertension. \u003cem\u003eClinics in liver disease\u003c/em\u003e. 23(4):755\u0026ndash;780.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOstojic A, \u003cem\u003eMahmud N, Reddy KR(2024).\u003c/em\u003e Surgical risk stratification in patients with cirrhosis. \u003cem\u003eHepatology international\u003c/em\u003e. 18(3):876\u0026ndash;891.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaltenbach MG, \u003cem\u003eMahmud N(2023).\u003c/em\u003e Assessing the risk of surgery in patients with cirrhosis. \u003cem\u003eHepatology Communications\u003c/em\u003e. 7(4):e0086.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu J, Wei Y-\u003cem\u003es(2026).\u003c/em\u003e Prognostic value of easy Albumin-Bilirubin score in liver cirrhosis: a comparison with established scoring systems. \u003cem\u003eEuropean Journal of Gastroenterology \u0026amp; Hepatology\u003c/em\u003e. 10.1097.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoudsmit BF, Putter H, Tushuizen ME, de Boer J, Vogelaar S, Alwayn I, \u003cem\u003eet al(\u003c/em\u003e2021). Validation of the Model for End-stage Liver Disease sodium (MELD-Na) score in the Eurotransplant region. \u003cem\u003eAmerican Journal of Transplantation\u003c/em\u003e. 21(1):229\u0026ndash;240.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaylor GA, Fagenson AM, Kuo LE, Pitt HA, Lau KN (2021). Predicting operative outcomes in patients with liver disease: albumin-bilirubin score vs model for end-stage liver disease-sodium score. \u003cem\u003eJournal of the American College of Surgeons\u003c/em\u003e. 232(4):470\u0026ndash;480. e472.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eD'\u003c/em\u003eAmico G, Garcia-Tsao G, \u003cem\u003ePagliaro L(2006).\u003c/em\u003e Natural history and prognostic indicators of survival in cirrhosis: a systematic review of 118 studies. \u003cem\u003eJournal of hepatology\u003c/em\u003e. 44(1):217\u0026ndash;231.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartin D, Mantziari S, \u003cem\u003eDemartines N, H\u0026uuml;bner M(2020).\u003c/em\u003e Defining major surgery: a Delphi consensus among European Surgical Association (ESA) members. \u003cem\u003eWorld journal of surgery\u003c/em\u003e. 44(7):2211\u0026ndash;2219.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eAmerican Society of Anesthesiologists(2026).\u003c/em\u003e American Society of Anesthesiologists statement on ASA physical status classification system. \u003cem\u003eAnesthesiol Open\u003c/em\u003e. 1(3):e0002-e0006.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDindo D, Demartines N, \u003cem\u003eClavien P-A(2024).\u003c/em\u003e Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. \u003cem\u003eAnnals of surgery\u003c/em\u003e. 240(2):205\u0026ndash;213.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim WR, Biggins SW, Kremers WK, Wiesner RH, Kamath PS, \u003cem\u003eBenson JT, et al(2008).\u003c/em\u003e Hyponatremia and mortality among patients on the liver-transplant waiting list. \u003cem\u003eNew England Journal of Medicine\u003c/em\u003e. 359(10):1018\u0026ndash;1026.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlcorn J (2015). Changes to OPTN bylaws and policies from actions at OPTN/UNOS Executive Committee meetings July 2015\u0026ndash;November 2015: clerical changes for implementation of adding serum sodium to the MELD score. \u003cem\u003eAvailable from\u003c/em\u003e: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://optntransplanthrsagov/media/1575/policynotice_1101pdf.\u003c/span\u003e\u003cspan address=\"https://optntransplanthrsagov/media/1575/policynotice_1101pdf.\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e 2015.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl Abbas AI, Borrebach JD, Bellon J, \u003cem\u003eZureikat AH(2020).\u003c/em\u003e Does preoperative MELD score predict adverse outcomes following pancreatic resection: an ACS NSQIP analysis. \u003cem\u003eJournal of Gastrointestinal Surgery\u003c/em\u003e. 24(10):2259\u0026ndash;2268.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnson PJ, Berhane S, Toyoda H, \u003cem\u003eJohnson PJ(2022).\u003c/em\u003e The ALBI score: from liver function in patients with HCC to a general measure of liver function. \u003cem\u003eJHEP Reports\u003c/em\u003e. 4(10):100557.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChan AW, Chan RC, Wong GL, Wong VW, Choi PC, Chan HL, \u003cem\u003eet al(\u003c/em\u003e2015). New simple prognostic score for primary biliary cirrhosis: albumin-bilirubin score. \u003cem\u003eJournal of gastroenterology and hepatology\u003c/em\u003e. 30(9):1391\u0026ndash;1396.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePark HJ, Seo KI, Kim SJ, Lee SU, Yun BC, Han BH, \u003cem\u003eet al(\u003c/em\u003e2021). Effectiveness of albumin-bilirubin score as a predictor of post-hepatectomy liver failure in patients with hepatocellular carcinoma. \u003cem\u003eThe Korean Journal of Gastroenterology\u003c/em\u003e. 77(3):115\u0026ndash;122.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlein J, Spigel Z, Kalil J, Friedman L, Chan E (2022). Postoperative mortality in patients with cirrhosis: reconsidering expectations. \u003cem\u003eThe American Surgeon\u003c/em\u003e. 88(2):181\u0026ndash;186.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRomeo M, Dallio M, Cipullo M, Coppola A, Mazzarella C, Mammone S, \u003cem\u003eet al(\u003c/em\u003e2025). Nutritional and Psychological Support as a Multidisciplinary Coordinated Approach in the Management of Chronic Liver Disease: A Scoping Review. \u003cem\u003eNutrition Reviews\u003c/em\u003e.nuaf001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRashid A, Gupta A, Adiamah A, West J, \u003cem\u003eGrainge M, Humes DJ(2022).\u003c/em\u003e Mortality following appendicectomy in patients with liver cirrhosis: a systematic review and meta-analysis. \u003cem\u003eWorld Journal of Surgery\u003c/em\u003e.46(3):531\u0026ndash;541.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed MM, Elfauomy M, ElZohry HA, Ammar K, \u003cem\u003eElfauomy M, Helal A(2023).\u003c/em\u003e Risk Stratification in Cirrhotic Patients with Emergent Surgery. \u003cem\u003eThe Egyptian Journal of Hospital Medicine\u003c/em\u003e.90(2):2406\u0026ndash;2412.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDaga LKD, \u003cem\u003eJamias JD(2025).\u003c/em\u003e Association of ALBI Grade, APRI Score, and ALBI-APRI Score with Postoperative Outcomes among Patients with Liver Cirrhosis after Non-hepatic Surgery. \u003cem\u003eActa Medica Philippina\u003c/em\u003e. 59(10):74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalah EM, Marwan IK, Badawy MT, \u003cem\u003eEl Disoki AI, Sallam AN(2025).\u003c/em\u003e The Ability of the Albumin-Bilirubin Grade to Predict the Short-Term Outcomes \u0026amp; Complications Following Hepatic Resection. \u003cem\u003eThe Egyptian Journal of Surgery\u003c/em\u003e. 44(1):91\u0026ndash;97.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNewman KL, Johnson KM, Cornia PB, Wu P, Itani K, \u003cem\u003eIoannou GN(2020).\u003c/em\u003e Perioperative Evaluation and Management of Patients With Cirrhosis: Risk Assessment, Surgical Outcomes, and Future Directions. \u003cem\u003eClinical Gastroenterology and Hepatology\u003c/em\u003e. 18(11):2398\u0026ndash;2414.e2393.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZaharia R, Morarasu S, Ivanov AA, Dimofte GM, Lunca S(2025). Predicting Outcomes in Hepatocellular Carcinoma Surgery: ALBI is the Better Tool. An Observational Cohort Study. \u003cem\u003eChirurgia (Bucharest, Romania: 1990)\u003c/em\u003e. 120(5):555\u0026ndash;565.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWong WG, Perez Holguin RA, Tarren AY, Shen C, Vining C, Peng JS, \u003cem\u003eet al (2022).\u003c/em\u003e Albumin-bilirubin score is superior to platelet‐albumin‐bilirubin score and model for end‐state liver disease sodium for predicting posthepatectomy liver failure. \u003cem\u003eJournal of surgical oncology\u003c/em\u003e. 126(4):667\u0026ndash;679.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFragaki M, Sifaki-Pistolla D, Orfanoudaki E, Kouroumalis E (2019). Comparative evaluation of ALBI, MELD, and Child-Pugh scores in prognosis of cirrhosis: is ALBI the new alternative? \u003cem\u003eAnnals of Gastroenterology\u003c/em\u003e. 32(6):626.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchlosser K, Kao A, Zhang Y, Prasad T, Kasten K, Davis B, \u003cem\u003eet al(\u003c/em\u003e2023). MELD-Na score associated with postoperative complications in hernia repair in non-cirrhotic patients. \u003cem\u003eHernia\u003c/em\u003e. 2019; 23(1):51\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNg ZQ, Tan P, Theophilus M. Colorectal surgery in patients with liver cirrhosis: a systematic review. \u003cem\u003eWorld Journal of Surgery\u003c/em\u003e. 47(10):2519\u0026ndash;2531.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWetterkamp M, van Beekum CJ, Willis MA, Glowka TR, Manekeller S, \u003cem\u003eFimmers R, et al(2020).\u003c/em\u003e Risk factors for postoperative morbidity and mortality after small bowel surgery in patients with cirrhotic liver disease\u0026mdash;A retrospective analysis of 76 cases in a tertiary center. \u003cem\u003eBiology.\u003c/em\u003e 9(11):349.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarasco G, Alemanni LV, Colecchia A, Festi D, Bazzoli F, Mazzella G, \u003cem\u003eet al(\u003c/em\u003e2021). Prognostic value of the albumin-bilirubin grade for the prediction of post-hepatectomy liver failure: a systematic review and meta-analysis. \u003cem\u003eJournal of clinical medicine\u003c/em\u003e. 10(9):2011.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRuzzenente A, \u003cem\u003eDe\u003c/em\u003e Angelis M, Conci S, Campagnaro T, Isa G, Bagante F, \u003cem\u003eet al(\u003c/em\u003e2019). The albumin-bilirubin score stratifies the outcomes of Child-Pugh class A patients after resection of hepatocellular carcinoma. \u003cem\u003eTranslational Cancer Research\u003c/em\u003e. 8(Suppl 3):S233.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYasri S, \u003cem\u003eWiwanitkit V(2019).\u003c/em\u003e MELD-Na score and postoperative complications in hernia repair. \u003cem\u003eHernia\u003c/em\u003e. 23(4):823\u0026ndash;823.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndraus W, Pinheiro RS, Lai Q, Haddad LB, Nacif LS, D\u0026rsquo;Albuquerque LAC, \u003cem\u003eet al(\u003c/em\u003e2017). Abdominal wall hernia in cirrhotic patients: emergency surgery results in higher morbidity and mortality. \u003cem\u003eBMC surgery\u003c/em\u003e. 15(1):65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbbas N, Fallowfield J, Patch D, Stanley AJ, Mookerjee R, Tsochatzis E, \u003cem\u003eet al(\u003c/em\u003e2023). Guidance document: risk assessment of patients with cirrhosis prior to elective non-hepatic surgery. \u003cem\u003eFrontline Gastroenterology\u003c/em\u003e. 14(5):359\u0026ndash;370.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMansour D, Masson S, Hammond J, Leithead JA, Johnson J, Rahim MN, \u003cem\u003eet al(\u003c/em\u003e2023). British Society of Gastroenterology Best Practice Guidance: outpatient management of cirrhosis\u0026ndash;part 3: special circumstances. \u003cem\u003eFrontline Gastroenterology\u003c/em\u003e. 14(6):474\u0026ndash;482.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsai T-J, Syu K-J, Huang X-Y, Liu YS, Chen C-W, \u003cem\u003eChang Y-Y, et al(2026).\u003c/em\u003e Postoperative Survival Analysis of Elective Colorectal Cancer Surgery with Liver Cirrhosis: A Propensity-Matched Study. \u003cem\u003eCurrent Oncology\u003c/em\u003e. 33(1):29.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhu Q, Chen D, Lou Y, Xie X, Wu Y, Wang Z, \u003cem\u003eet al(\u003c/em\u003e2023). Baseline ALBI grade predicts benefits after splenectomy for cirrhotic patients with hypersplenism. \u003cem\u003eJournal of Gastrointestinal Surgery\u003c/em\u003e. 27(6):1130\u0026ndash;1140.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Risk stratification, cirrhotic, elective abdominal surgery, ALBI, MELD Na","lastPublishedDoi":"10.21203/rs.3.rs-9457480/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9457480/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Perioperative risk stratification in cirrhotic patients remains a significant clinical challenge. While the Albumin–Bilirubin (ALBI) and MELD-Na scores have emerged as objective alternatives to traditional systems, their comparative performance in elective surgery is not fully established. We aimed to compare the predictive accuracy of ALBI and MELD-Na for postoperative morbidity in cirrhotic patients undergoing elective major abdominal surgery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This prospective observational cohort study enrolled 57 cirrhotic patients undergoing elective major abdominal interventions between January 2024 and August 2025. Preoperative ALBI and MELD-Na scores were calculated. The primary endpoint was 30-day overall morbidity (surgical complications or hepatic decompensation, graded by the Clavien-Dindo classification. Predictive performance was evaluated using AUROC analysis, DeLong tests, multivariate logistic regression, and Kaplan-Meier survival analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The cohort was predominantly Child-Pugh A (89.5%) with a median age of 61.0 years. Postoperative morbidity occurred in 31.6% of patients; complications were primarily hepatic/medical (83.3%) and minor (Clavien-Dindo I–II, 72.2%). The ALBI score demonstrated significantly higher predictive accuracy for morbidity compared to MELD-Na (AUC: 0.835 vs. 0.683; \u003cem\u003eP=\u003c/em\u003e0.001). This superiority persisted in a subgroup analysis excluding patients with obstructive jaundice (\u003cem\u003eP=\u003c/em\u003e 0.001). An ALBI cut-off ≥2.42 yielded a sensitivity of 88.9% and a negative predictive value of 93.5%. In multivariate analysis, ALBI was the sole independent predictor of complications (OR: 24.0; 95% CI: 1.8–322.1; \u003cem\u003eP=\u003c/em\u003e0.016). Kaplan-Meier analysis confirmed significantly shorter complication-free survival in the high-risk ALBI group (Log-rank \u003cem\u003eP=\u003c/em\u003e 0.005), whereas MELD-Na failed to stratify risk effectively (Log-rank \u003cem\u003eP=\u003c/em\u003e 0.168).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: The ALBI score is a more robust and reliable tool than MELD-Na for preoperative risk stratification in cirrhotic patients. Its high negative predictive value and objective nature make it superior for identifying patients at risk of postoperative morbidity following major elective abdominal surgery.\u003c/p\u003e","manuscriptTitle":"Comparative Performance of ALBI score versus MELD-Na Score in Predicting Postoperative Outcomes Following Elective Major Abdominal Surgery in Cirrhotic Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-04 05:48:34","doi":"10.21203/rs.3.rs-9457480/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3d1c5834-fcb9-43b8-b555-02a70351a6a0","owner":[],"postedDate":"May 4th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"281425849439813723032001282040042422858","date":"2026-05-15T11:45:50+00:00","index":60,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-04T12:48:54+00:00","index":43,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T05:48:34+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-04 05:48:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9457480","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9457480","identity":"rs-9457480","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}