Predictive and prognostic significance of the Age, blood tests and comorbidities (ABC) score, Cologne-watch (C-watch) score and Rockall score for risk of mortality following variceal bleeding among cirrhotic patients

Predictive and prognostic significance of the Age, blood tests and comorbidities (ABC) score, Cologne-watch (C-watch) score and Rockall score for risk of mortality following variceal bleeding among 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 Predictive and prognostic significance of the Age, blood tests and comorbidities (ABC) score, Cologne-watch (C-watch) score and Rockall score for risk of mortality following variceal bleeding among cirrhotic patients EL-Zahraa Meghezel, Asmaa Sayed, Reem Makbol This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9023233/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: Acute variceal bleeding is one of the most life-threatening complications of liver cirrhosis. The development of several risk assessment score systems has led to the prediction of outcomes like rebleeding and death. These systems include pre- and post-endoscopy evaluations. Objective: To predict outcome of variceal bleeding in cirrhotic patients and detect risk factor of mortality. Patient and Methods: One hundred cirrhotic patients were admitted to Sohag University Hospital, presenting with upper gastrointestinal variceal bleeding between March 2024 and March 2025. All participants will be subjected to: Complete history, clinical examination, laboratory investigation (Complete blood count, liver and renal function tests, C-reactive protein (CRP) and ascitic fluid study), abdominal ultrasound and upper endoscopy were done. Predicting outcomes and assessment risk of mortality by: ABC score, C-watch score and Rockall score. Results: Mortality occurred in 36% of cases, rebleeding in 8%, while 56% had a good prognosis. Child score C were statistically significant in predicting mortality (P value: 0.01). Diagnostic performance of the studied scores in prediction of mortality showed that ABC score had the highest statistically significant diagnostic ability in predicting mortality, with an AUC of 72.6%, 95% CI: 0.6: 0.8, P value: <0.001. The cutoff point was 9.5 carrying a sensitivity of 44.4% and a specificity of 93.7%. Conclusion: Mortality was best predicted by a combination of elevated ABC score, other laboratory finding as (increased INR, CRP and ascitic fluid infection), the presence of combined portal-vein dilatation with thrombosis, hepatic focal lesion, presence of ascites on ultrasound and Child-Pugh class C. Among the evaluated scoring systems, the ABC score showed the best predictive performance for mortality. Liver cirrhosis mortality rate and ABC score Figures Figure 1 Figure 2 Figure 3 Introduction Liver cirrhosis (LC) is the final stage attained by slow progression of different chronic liver illnesses following years or decades, and it is marked by diffuse hepatic fibrosis & normal liver structures being replaced by regenerative liver nodules [ 1 , 2 ]. Liver diseases caused by alcohol, hepatitis B (HBV) and hepatitis C viruses (HCV), and non-alcoholic fatty liver disease (NAFLD) are the primary causes of cirrhosis [ 3 ]. Portal hypertension (PH) and associated consequences, such as gastro-esophageal varices (GEVs), variceal hemorrhage (VH), ascites, hepatorenal syndrome, portosystemic encephalopathy, and spontaneous bacterial peritonitis, are most commonly caused by cirrhosis [ 4 ]. ]. PH is the major driver in the transition from the compensated to the ‘decompensated’ stage of cirrhosis, that identified by the presence of clinical complications [ 5 , 6 ]. The main complication of the diseases is the gastrointestinal bleeding from the rupture of esophago-gastric varices, which is the leading cause of death in cirrhotic individuals [ 7 , 8 ]. Acute variceal bleeding is one of the most life-threatening complications. In the first two years of follow-up, 22–61% of cirrhotic patients who get primary prophylaxis will have their first variceal bleeding [ 9 ]. The likelihood of rebleeding elevated for patients suffering from peptic ulcers and variceal hemorrhage. Rebleeding is also considered to be an important cause of increasing death, and it occurs in approximately 10–30% of cases [ 10 , 11 ]. A number of clinical scores can be employed to classify the risk of complications, rebleeding, the necessity of clinical intervention, and mortality [ 12 ]. The Glasgow-Blatchford score (GBS), the AIMS65 score (albumin 1.5 (I), disturbed mental state (M), systolic blood pressure 90 (S), and age > 65 years (65)), and the clinical Rockall score (CRS) are the most prominent utilized scoring systems [ 13 ]. The following scoring systems include post-endoscopic scoring tools (eg, Cedars Sinai, full Rockall score, as well as Progretto Nazionale Emorragia Digestiva) and pre-endoscopic scoring tools (eg, the pre-endoscopy Rockall, AIMS65, as well as GBS) [ 14 , 15 ]. Rockall score has been developed in 1996 to predict death and rebleeding, involving both the clinical Rockall score & the full Rockall score, the pre-endoscopic Rockall score is calculated using the parameters that are performed before an upper endoscopy is performed which include: Age, comorbid diseases, as well as shock. The post-endoscopic RS is based on the same parameters, as well as the data obtained during endoscopy, which include: The cause of bleeding, and evidence of bleeding as shown in ( Fig. 1 ) [ 16 , 17 ]. In cases of variceal and non-variceal bleeding, it is both effective and easy to calculate. It is only possible to calculate the RS if an endoscopy has been performed [ 18 ]. In 2020, Laursen et al. [ 15 ] released an updated pre-endoscopy risk score for upper and lower gastrointestinal bleeding, called the ABC score, which is based on many factors including age, blood tests, and comorbidities. In terms of mortality prediction, this score was more useful than AIMS65, the prior best score for this outcome [ 19 ]. This scoring system is based on three criteria: Age, blood test results, and comorbidity. Using a scale from 0 to 18, with the risk being categorized into low (3 points), moderate (4–7 points), or high (8 points) as shown in ( Fig. 2 ) [ 15 , 20 ]. The new Cologne WATCH (C-WATCH) score has been developed as a pre-endoscopic scoring system for acute variceal & non-variceal upper gastrointestinal bleeding (UGIB) and only incorporates laboratory values (C- reactive protein, white blood cell count, ALT, thrombocytes, creatinine, and hemoglobin). The minimum point value is 0 and the maximum point value is 8 as shown in (Fig. 3) [ 21 ]. The Baylor bleeding score (BBS), the T-score (TSC), and the Cedars-Sinai Medical Center Predictive Index (CSMCPI) were some of the other predictive measures [ 22 ]. Some Prognosis in variceal bleeding is related especially to the severity of liver failure which assessed using Child–Pugh–Turcotte or MELD scores; in the majority of studies on variceal bleeding, which focus on the significance of classical prognostic scores concluded that the value was inferior in variceal bleeding in comparison with non-variceal bleeding [ 23 ]. Patients and Methods A prospective cohort study was performed on 100 cirrhotic patients, presenting with upper gastrointestinal variceal bleeding, attended to Tropical Medicine and Gastroenterology Department of Sohag University Hospital. The study was conducted after being authorized by the Ethics Committee of the Sohag Faculty of Medicine. All patients signed an informed consent. IRB: Soh-Med-24-03-04MS. All patients were subjected to : Complete history taking. Clinical examination: Vital signs (pulse 60–100 beats per minute, blood pressure 120/80 mm/Hg to 90/60 mm/Hg and temperature 36.2°C-37.5°C) [ 24 , 25 ]. Complete general and local examination. Laboratory investigation: Complete blood count (Hemoglobin (Hb), white blood cells (WBC) and platelet). Liver function test as alanine transaminase (ALT), aspartate transaminase (AST), serum albumin, total bilirubin, Prothrombin time (PT), Prothrombin concentration (PC), International normalized ratio (INR) and child pugh score which is based on (Encephalopathy ascites, serum albumin, total bilirubin and INR), classified into child A (5:6), child B (7:9) and child C (10:15) [ 26 ]. Serum creatinine, urea and C-reactive protein (CRP). Ascitic fluid study for patients with ascites. Serology for hepatitis C virus (HCV) and hepatitis B virus (HBV). Predicting outcomes and assessment risk of mortality by ABC score, C-watch score and Rockall score. Radiological investigation - Abdominal ultrasound with comment on: Liver size (The average liver span in the midclavicular line for the overall collective was 15.0 ± 1.5 cm) [ 27 ], echopattern (homogenous or coarse), surface (smooth or irregular) and the presence or absence of focal lesions. Portal vein diameter (The normal portal vein diameter does not exceed 13mm) [ 28 ], patency and presence of collaterals. Spleen size (Average splenic length of 12 cm), echopattern and splenic vein diameter < 10 mm diameter [ 29 ]. Presence of ascites or not. Endoscopic with comment on: Esophageal varices: -Size: Mildly filled (F1), moderately filled (F2) or markedly filled (F3). - Color: Colored white (Cw) or colored blue (Cb). -Red color sign (RC): Positive or negative. Gastric varies: Extension or isolated. Stigmata of recent bleeding. We also comment on associated lesions with varices as (Mallory-Weiss tear, peptic ulcer, erosive disease, esophagitis and malignancy). Statistical analysis: Statistics for the Social Sciences (SPSS) version 26, which is also utilized to display the outcomes, was employed for data entry and analysis. Data that did not follow a normal distribution were summarized using (IQR) and median. For quantitative data that did follow a normal distribution, means ± standard deviations were utilized, whereas descriptive statistics were used for qualitative data. Using the Shapiro-Wilk test, we checked for a normal distribution of the data. Using a Chi-square test, Fisher's exact test , or Monte Carlo significant testing (in cases where 20% or more of the total predicted cell counts were less than 5), we were able to discover the link between result groups and qualitative data. Independent sample t tests or Mann-Whiteny U tests , depending on distributional assumptions, were used to identify associations between groups and quantitative data. Binary logistic regression analysis, both univariate and multivariate, was used to identify characteristics that predicted rebleeding and mortality. If the P value of the variables in the outcome groups' bivariate analysis was less than or equal to 0.25, they were included in the regression analysis. The variables from the univariate model were used in the multivariate analysis, which employed the backward elimination approach, and had a P value of less than 0.05 for removal and a P value of ≤ 0.25 for variables. Utilizing a receiver operating characteristics (ROC) curve, researchers assessed the sensitivity and specificity of the tested biomarkers in detecting rebleeding and mortality. The cutoff values were obtained using Youden's index. Significance was determined using a p-value that was less than 0.05. Results From March 2024 to March 2025, a total of 100 patients were included in the study. Outcome of the studied patients was variable between good prognosis in 56% of patients and poor prognosis that divided into mortality which occurred in 36% of the cases and rebleeding in 8% of the cases as shown in (Table 1). Regarding risk of mortality, the mean age of the studied patients was statistically significantly higher among mortality group compared to survivor group (P value: 0.03). In addition, percentage of diabetic patients was higher statistically significant in mortality group than survivor group (P value: 0.03) as shown in (Table 2). When we studied the risk of mortality as regard examination data of studied patients, we found that presence of pallor, jaundice and ascites were higher statistically significant in mortality group than survivor group (P values: 0.047, 0.046 respectively) as shown in (Table 2). As regard laboratory investigation, it was found that there was statistically significant association between mortality and decreased serum albumin, increased INR and child score C (P value: 0.001, 0.02 and 0.01 respectively). There was significant association between mortality and increased serum creatinine and CRP (P values: 0.03, 0.001 respectively). As regarding ascitic fluid study we detected that SBP was highly statistically significant in mortality group than survivor (P value: 0.002) as shown in (Table 3). Abdominal ultrasound finding showed a higher statistically significant association between risk of mortality and presence of HFL (P value: 0.001) as shown in (Table 4). When we studied the role of scoring system in predicting mortality, we found that ABC score was the only statistically significant score to predict mortality (P value: <0.001) with significant higher ABC score risk in mortality than survivor group (P value: 0.001) as shown in (Table 5). In the univariate and multivariate analysis, we found that increased age, DM, decreased serum albumin level, increased INR, Child score C, occurrence of SBP, increased CRP level, presence of dilated thrombosed portal vein, presence of HFL, ascites and increased ABC score were statistically significant predictors of mortality in the univariate analysis (P value: 0.048, 0.03, 0.002, 0.03, 0,01, 0,03, 0.005, 0.04, 0,002, 0.04, < 0.001 respectively). However, multivariate logistic regression results revealed that increase in INR, presence of dilated thrombosed portal vein and increase in ABC score were statistically significant predictors for mortality (P value: 0.04, 0.003, < 0.001 respectively) as shown in (Table 6). Diagnostic performance of the studied scores in prediction of mortality showed the studied three scores had no statistically significance diagnostic performance in prediction of mortality. Despite that, ABC score showed the highest AUC in predicting mortality of 72.6% with significant diagnostic ability in predict mortality as shown in (Table 7). Table (1): Outcome results of the studied patients Mortality : N (%) Summary statistics (n = 100) 36 (36) Rebleeding : N (%) 8 (8) Good prognosis : N (%) 56 (56) Table (2): Risk of mortality as regard baseline clinical and examination data of the studied patients Age: Mean ± SD Median (IQR) Mortality group (n = 36) Survivor group (n = 64) P value 64.3 ± 12.4 65 (58.5:70) 59 ± 12.4 62 (54.3:67) 0.03* † Gender: Female N (%) Male N (%) 8 (22.2) 28 (77.8) 26 (40.6) 38 (59.4) 0.06 § Diabetes : N (%) 20 (55.6) 21 (32.8) 0.03 * § Hypertension : N (%) 9 (25) 14 (21.9) 0.72 § Co-morbidities LC associated with heart disease : N (%) 3 (8.3) 4 (6.3) 0.7 ‡ LC associated with renal failure : N (%) 3 (8.3) 2 (3.1) 0.35 ‡ Head & Neck : Normal N (%) Pallor N (%) Jaundice N (%) Pallor & jaundice N (%) 5 (13.9) 18 (50) 4 (11.1) 9 (25) 16 (25) 36 (56.3) 8 (12.5) 4 (6.3) 0.047 * ‡ Upper limb : Normal N (%) Flapping tremors N (%) Palmar erythema N (%) Flapping tremors & Palmer erythema N (%) 9 (25) 12 (33.3) 9 (25) 6 (16.7) 26 (40.6) 23 (35.9) 8 (12.5) 7 (10.9) 0.23 § Lower limb : Normal N (%) Lower limb oedema N (%) 22 (61.1) 14 (38.9) 46 (71.9) 18 (28.1) 0.27 § Abdomen : Normal N (%) Ascites N (%) Splenomegaly N (%) Hepatomegaly N (%) Ascites & organomegaly N (%) 14 (38.8) 10 (27.8) 6 (16.7) 2 (5.6) 4 (11.1) 29 (45.3) 7 (10.9) 18 (28.1) 0 10 (15.6) 0.046 *‡ † Mann-Whiteny U test, § Chi squared test, † Fisher’s Exact test, ‡ Monte Carlo test, * Significant at level < 0.05. LC : Liver cirrhosis; SBP : Systolic blood pressure; DBP : Diastolic blood pressure. Table (3): Risk of mortality as regard laboratory investigations of the studied patients Mortality group (n = 36) Survivor group (n = 64) P value CBC Hb (mg/dl) : Mean ± SD Median (IQR) 8.2 ± 2.1 7.8 (6.8:9.7) 8.8 ± 2.4 8.9 (7.3:10.6) 0.2 † WBCs : Mean ± SD Median (IQR) 8 ± 5.9 7 (4:9.3) 8.3 ± 6.1 5.9 (4.1:12.3) 0.9 § Platelet : Mean ± SD Median (IQR) 141.4 ± 92.3 118 (72:194.8) 123 ± 78.1 95 (65.5:168.8) 0.35 § LFT ALT (IU/L): Mean ± SD Median (IQR) 68.5 ± 111 24.5 (15:60.8) 36.8 ± 39.5 24 (15:40) 0.43 § AST (IU/L): Mean ± SD Median (IQR) 103 ± 180 45 (23:96) 52.2 ± 60.7 35 (20.3:55.8) 0.09 § Alb (g/dl): Mean ± SD 2.6 ± 0.6 3 ± 0.5 0.001 * † T.Bil (mg/dl): Mean ± SD Median (IQR) 3 ± 5 1.4 (0.8:2.5) 1.8 ± 2.3 1.2 (0.8:1.6) 0.28 § PT : Mean ± SD Median (IQR) 16.5 ± 5.6 15.6 (13.2:17.2) 15.3 ± 5.4 14.8 (13.1:16.5) 0.14 § PC : Mean ± SD Median (IQR) 66 ± 20.3 63.1 (52.3:75.8) 68.4 ± 16.9 69.4 (59:79) 0.3 § INR : Mean ± SD Median (IQR) 1.4 ± 0.5 1.3 (1.2:1.5) 1.2 ± 0.2 1.2 (1.1:1.3) 0.02 * § Child score : A N (%) B N (%) C N (%) 4 (11.1) 17 (47.2) 15 (41.7) 16 (25) 38 (59.4) 10 (15.6) 0.01 * ‡ Serology : Negative N (%) HCV N (%) HBV N (%) Unknown N (%) 6 (16.7) 27 (75) 0 3 (8.3) 10 (15.6) 45 (70.3) 5 (7.8) 4 (6.3) 0.41 ǂ Others Creatinine (mg/dl): Mean ± SD Median (IQR) 1.3 ± 1 1 (0.7:1.6) 0.96 ± 0.7 0.8 (0.5:1.2) 0.03 * § Urea (mg/dl) : Mean ± SD Median (IQR) 58.7 ± 68.2 33 (17:72.5) 38.2 ± 36.2 27 (17:43) 0.43 § CRP (mg/l) : Mean ± SD Median (IQR) 52.1 ± 40.8 47.2 (21.5:69.3) 27.9 ± 33.8 13.6 (5:38) < 0.001 * § AFS (n = 26) (n = 31) SBP: N (%) 7 (26.9) 3 (9.7) 0.16 † TLC : Mean ± SD Median (IQR) 577.5 ± 1043.1 307.5 (97:586.3) 277 ± 253.4 200 (150:315) 0.54 § Polymorphs : Mean ± SD Median (IQR) 50.3 ± 30.2 45 (21.3:81.3) 23.9 ± 21.7 10 (5:40) 0.002 * § Protein : Mean ± SD Median (IQR) 1.5 ± 1.9 1 (0.7:1.7) 1.6 ± 3 0.9 (0.6:1.3) 0.66 § † Fisher’s Exact test, § Mann-Whiteny U test, * Significant at level < 0.05. CBC : Complete blood count; Hb : Haemoglobin; WBC : White blood cells; LFT : Liver function test; ALT : Alanine transaminase; AST : Aspartate transaminase; Alb : Albumin; T.Bil : Total bilirubin; PT : Prothrombin time; PC : Prothrombin concentration; INR : International normalized ratio; HCV : Hepatitis C virus; HBV : Hepatitis B virus; CRP : C-reactive protein; AFS : Ascitic fluid study; SBP : Spontaneous bacterial peritonitis; TLC : Total leucocytic count. Table (4): Risk of mortality as regard abdominal U/S of the studied patients Liver size: Average N (%) Enlarged N (%) Mortality group (n = 36) Survivor group (n = 64) P value 30 (83.3) 6 (16.7) 56 (87.5) 8 (12.5) 0.56 † Liver echo-pattern: Coarse N (%) Heterogeneous 33 (91.7) 3 (8.3) 58 (90.6) 6 (9.4) 1.0 § Portal vein : Normal N (%) Dilated N (%) Thrombosed N (%) Dilated & thrombosed N (%) 17 (47.2) 7 (19.4) 5 (13.9) 7 (19.4) 34 (53.1) 21 (32.8) 6 (9.4) 3 (4.7) 0.07 ‡ HFL : N (%) 12 (33.3) 5 (7.8) 0.001 * † Spleen size : Average N (%) Enlarged N (%) 10 (27.8) 26 (72.2) 14 (21.9) 50 (78.1) 0.51 † Dilated splenic vein : N (%) 5 (13.9) 10 (15.6) 0.82 † Ascites : No N (%) Mild N (%) Moderate N (%) Marked N (%) 10 (27.8) 10 (27.8) 9 (25) 7 (19.4) 33 (51.6) 10 (15.6) 12 (18.8) 9 (14.1) 0.13 † † Fisher’s Exact test, § Monte Carlo test. HFL : Hepatic focal lesion. Table (5): Risk of mortality as regard scoring system of the studied patients Rockall score : Mean ± SD Median Mortality group (n = 36) Survivor group (n = 64) P value 5.6 ± 1 5 (5:7) 5.3 ± 1.1 5 (5:6) 0.1 † Rockall score risk : Moderate N (%) High N (%) 19 (52.8) 17 (47.2) 42 (65.6) 22 (34.4) 0.21 § ABC score : Mean ± SD Median 8.6 ± 3 8 (6:11) 6.4 ± 2 6 (5:7) < 0.001 * † ABC score risk : Low N (%) Moderate N (%) High N (%) 0 15 (41.7) 21 (58.3) 1 (1.6) 49 (76.6) 14 (21.9) 0.001 * C-watch score : Mean ± SD Median 4.4 ± 1.1 5 (4:5) 3.97 ± 1.2 4 (3:5) 0.07 † C-watch score complication risk : 5% N (%) 10% N (%) 18% N (%) 30% N (%) 45% N (%) 62% N (%) 76% N (%) 0 1 (2.8) 7 (19.4) 9 (25) 15 (41.7) 2 (5.6) 2 (5.6) 2 (3.1) 4 (6.3) 17 (26.6) 20 (31.1) 13 (20.3) 8 (12.5) 0 0.08 ‡ C-watch score complication risk : ≥ 18% N (%) 18–45% N (%) >45% N (%) 8 (22.2) 24 (66.7) 4 (11.1) 23 (35.9) 33 (51.6) 8 (12.5) 0.31 § † Mann-Whiteny U test, § Fisher’s Exact test, ‡ Monte Carlo test. ABC : Age, blood tests and comorbidities; C-watch : Cologne watch. Table (6): Univariate and multivariate binary logistic regression of predictors of mortality Univariate Unadjusted OR (95% CI) P value Age : 1.04 (1:1.1) 0.048 * Male gender : 2.4 (0.9:6.1) 0.07 DM : 2.6 (1.1:5.9) 0.03 * Hb : 0.9 (0.7:1.1) 0.2 AST : 1.01 (0.99:1.01) 0.09 Albumin : 0.29 (0.1:0.6) 0.002 * PT : 1.04 (0.96:1.1) 0.33 INR : 6.9 (1.2:38.8) 0.03 * Child score : A a B C 1 1.8 (0.5:6.2) 6 (1.5:23.3) 0.36 0.01 * SBP occurrence : 4.9 (1.2:20.4) 0.03 * Creatinine : 1.7 (0.98:3.1) 0.06 CRP : 1.02 (1.01:1.03) 0.005 * Portal vein : Normal a Dilated Thrombosed Dilated & thrombosed 1 0.67 (0.2:1.9) 1.7 (0.4:6.3) 4.7 (1.1:20.3) 0.44 0.45 0.04 * HFL : 5.9 (1.9:18.6) 0.002 * Ascites : No Mild Moderate Marked 1 3.3 (1.1:10.2) 2.5 (0.8:7.6) 2.6 (0.8:8.7) 0.04 * 0.11 0.13 Rockall score : 1.4 (0.9:2.1) 0.09 ABC score : 1.4 (1.2:1.8) < 0.001 * C-watch score : 1.4 (0.98:2) 0.06 Multivariate ABC score : 1.6 (1.2:2) < 0.001 * Portal vein : Normal a Dilated Thrombosed Dilated & thrombosed 1 0.8 (0.2:2.6) 2.1 (0.4:10.8) 14.3 (2.5:80.8) 0.68 0.39 0.003 * INR : 6.6 (1.1:41.1) 0.04 * a reference group, * Significant at level < 0.05. DM : Diabetes Melius; Hb : Haemoglobin; AST : Aspartate transaminase; PT : Prothrombin time; INR : International normalized ratio; SBP : Spontaneous bacterial peritonitis; CRP : C- reactive protein; HFL : Hepatic focal lesion; ABC : Age, blood tests and comorbidities; C-watch : Cologne watch. Table (7): Diagnostic performance of the studied scores in prediction of mortality Rockall score : AUC 95% CI P value Cutoff point Sensitivity Specificity 59.5% 0.5:0.7 0.12 6.5 27.8% 85.9% ABC score : 72.6% 0.6:0.8 < 0.001 * 9.5 44.4% 93.7% C-watch score : 60.5% 0.5:0.7 0.08 4.5 52.8% 67.2% ABC : Age, blood tests and comorbidities; C- watch : Cologne watch. Discussion The current study included 100 patients with acute upper gastrointestinal variceal bleeding secondary to liver cirrhosis. Our study detected that mortality occurred in 36% of cases, rebleeding in 8%, while 56% had a good prognosis. This mortality rate is agreed with previous studies by Garcia-Tsao et al. [ 30 ], who have reported variable mortality rates in variceal bleeding, ranging from 15% to 40%, depending on liver function status and timing of intervention. Possible explanations for the high mortality rate in our study include advanced portal hypertension, severe underlying cirrhosis, delayed presentation, or insufficient healthcare resources. Otherwise, a prior study by Lo et al. [ 31 ] reported that the rate of early rebleeding following UGIB was between 9% and 19%, which is close to our result (8%). Regarding risk of mortality, the present study revealed that age was statistically significant higher in the mortality group compared to survivor which agreed with Reverter et al. [ 32 ], who demonstrated that older age was independently predicted mortality in patients with acute variceal bleeding. This finding suggests that advanced age is an important predictor of mortality in patients with variceal bleeding as older patients often present with multiple comorbidities, reduced physiological reserve, and impaired hepatic and renal function, all of which may contribute to poorer outcomes [ 33 ], emphasizing the need for close monitoring and aggressive management in elderly individuals. Diabetes mellitus also statistically significant increased mortality risk. This result agreed with Trombetta et al., and Yang et al. [ 34 , 35 ], who found that diabetes mellitus significantly correlated with gastroesophageal variceal bleeding and showed an increased risk of mortality. This result could be explained by the fact that hyperglycemia increases the risk of variceal hemorrhage and mortality by causing splanchnic hyperemia, increasing portal blood flow as a result of blood sugar fluctuations that raise portal pressure, and impacting tissue repair and wound healing [ 36 ]. Examination of our patients revealed that pallor had statistically significant association with increased morality which agreed with Raţiu et al. [ 37 ], who detected that pallor was indicator of severe anemia associated with increasing mortality in variceal bleeding. This can be explained by that anemia reflects significant blood loss, hemodynamic stress, and reduced oxygen-carrying capacity, all of which worsen prognosis [ 38 ]. Also, presence of jaundice also associated with increased mortality rate. Our finding was similar to Mohammad et al. [ 39 ], who detected that serum bilirubin > 3 mg/dl is a predictor of mortality in patient with variceal bleeding. The presence of ascites on clinical examination shows statistically significant association with increased mortality rate, and align with Nevens et al., and Hori et al. [ 40 , 41 ]. This is due to ascites marks a decompensated cirrhotic, reflecting advanced portal hypertension and hemodynamic dysregulation, as well as possible renal impairment, these factors act as independent drivers of poor outcomes following variceal bleeding [ 42 ]. Laboratory parameters of our patients revealed that decreased in serum albumin showed highly statistically significant association with increased mortality rate. Similar, Krige et al., and Min et al. [ 43 , 44 ] demonstrated that albumin, as a marker of hepatic synthetic function, is a critical prognostic factor in variceal bleeding and mortality. Our patients who had increased INR also showed statistically significant association with increased mortality, this agreed with Shingina et al. [ 45 ], who shown that coagulation markers, such as INR > 1.5, are significant independent predictors of mortality and should be used in early risk classification for cirrhotic patients with variceal haemorrhage. We also detected that Child-Pugh C had statistically significant increased risk of mortality. These findings aligned with García-Pagán et al. [ 46 ], who detect Child-Pugh score for a long time has been used to categorize patients at risk of mortality; patients in Child-Pugh class C have a very bad prognosis. Clinical research and clinical practice both continue to utilize the Child-Pugh score as the gold standard for assessing variceal bleeding which is detected by D'Amico et al. [ 5 ], who found that mortality was particularly high in Child class C patients who required longer hospital stays. Increased in serum creatinine also showed statistically significant association with increased risk of mortality, this agreed with Ismail et al., and Berzigotti, [ 47 , 48 ]. As the development of hepatorenal syndrome can worsen systemic perfusion and hepatic decompensation, thereby increasing the risk of death. Kim et al. [ 49 ] identified serum creatinine as an independent predictor of in-hospital mortality in acute variceal haemorrhage. We detected that CRP was highly statistically significantly elevated in the mortality group. This profound inflammatory state likely reflects systemic infection, tissue damage, or the inflammatory of advanced liver disease, this was in agreement with Ichikawa et al. [ 50 ], who discovered that increased C-reactive protein levels would have predicted 6-week mortality following oesophageal variceal haemorrhage, even in the absence of clinically apparent infection. Our result revealed that spontaneous bacterial peritonitis increased mortality rate, which is agreed with Lee et al. [ 51 ], who found that bacterial infections, particularly SBP, significantly raise the risk of mortality in cirrhotic patients with variceal bleeding. This result may be explained by that SBP exacerbates oesophageal variceal bleeding by increasing sinusoidal pressure, disrupting haemostasis, as well as endotoxemia, which are triggers for variceal bleeding in cirrhotic patients [ 52 ]. Presence of hepatic focal lesions is associated with an elevated and statistically significant risk of mortality that is in agreement with Chen et al. [ 53 ], who found that HCC patients with acute variceal bleeding had a worse prognosis. Also, Chung, [ 54 ] detected that HCC, commonly accompanied by acute variceal bleeding (AVB), is known as a poor prognostic factor in AVB patients. This can be explained by HCC linked to underlying cirrhosis and/or tumor invasion of the portal vein, which can result in thrombosis and portal hypertension-induced variceal bleeding [ 55 ]. Patients with severe HCC are at increased risk of variceal bleeding and death due to the decrease in serum levels of several blood clotting factors caused by the liver's decreased plasma protein production [ 56 ]. We detected that ABC score was highly statistically significant in predicting mortality, this was strongly supported by Jimenez-Rosales et al. [ 57 ], who demonstrated ABC score's superiority in predicting mortality in cirrhotic patients complicated by variceal haemorrhage (AUROC 0.804), and Laursen et al. [ 58 ], who validated ABC score as an accurate mortality predictor. Rockall score was not significant to predict mortality, this result agreed with Stanley et al. [ 19 ], who found Rockall score had limited utility for mortality prediction. Also, C-watch score is getting close to the performance but still not significant. This finding suggests that while the C-watch score was originally developed and validated for general upper gastrointestinal bleeding, its applicability may be limited in cases specifically related to portal hypertension and variceal haemorrhage. Similar findings were reported by Allo et al. [ 59 ], who noted that although the C-watch score showed good discriminative ability in non-variceal bleeding, its performance was less in patients with variceal bleeding. In multivariate analysis; ABC score, PVT and INR were predictor for mortality. This may be explained that portal vein thrombosis and dilation may indicate more advanced portal hypertension and impaired hepatic perfusion, both of which can worsen patient outcomes which contributes to increased variceal pressure and risk of rebleeding, which may further explain the observed rise in mortality [ 60 ] Diagnostic performance of the studied scores in prediction of mortality showed that, except for the ABC score, which had the most significant diagnostic capacity in predicting death with an AUC of 72.6%, none of the other three scores exhibited any meaningful diagnostic performance in mortality prediction. Our findings were agreed with Liu et al. [ 61 ], who found that, among all scores, the ABC score had the best AUROC value of 0.72 for predictive of 30-day mortality in UGIB patients. Conclusion Univariate logistic regression analysis showed that advanced age, presence of diabetes mellitus, hypoalbuminemia, prolonged INR, child score C, ascetic fluid infection, increased CRP, presence of combined dilated and thrombosed portal vein, HFL and ascites on ultrasound and ABC score are predictors, while multivariate showed that ABC score, dilated and thrombosed portal vein and prolonged INR are the only predictors of mortality. Conventional endoscopic stigmata and commonly used upper-GI bleeding scores showed limited value for predicting death. Among the evaluated scoring systems, the ABC score showed the best predictive performance for mortality. Abbreviations LC Liver cirrhosis, HBV hepatitis B virus, HCV hepatitis C virus, NAFLD non-alcoholic fatty liver disease, PH portal hypertension, GEVs gastro-esophageal varices, VH variceal hemorrhage, CRS clinical Rockall score, ABC Age, blood tests and comorbidities score, AIMS65 AIMS65 score, GBS Glasgow-Blatchford, C- WATCH Cologne watch, UGIB upper gastrointestinal bleeding, BBS Baylor bleeding score, CSMCPI Cedars–Sinai Medical Center Predictive Index, TSC T-score, Hb hemoglobin, WBC white blood cells, ALT alanine transaminase, AST aspartate transaminase, PT prothrombin time, PC prothrombin concentration, INR International normalized ratio, CRP C-reactive protein, F1 mildly filled, F2 moderately filled, F3 markedly filled, Cw colored white, Cb colored blue and RC red color sign. 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Alimentary pharmacology & therapeutics; 33(9): 1010–18. García-Pagán J C, Caca K, Bureau C, Laleman W, Appenrodt B, Luca A, & Bosch J (2010): Early use of TIPS in patients with cirrhosis and variceal bleeding. New England Journal of Medicine; 362(25): 2370–79. Ismail F W, Mumtaz K, Shah H A, Hamid S, Abbas Z, Abid S & Jafri W (2006): Factors predicting in-hospital mortality in patients with cirrhosis hospitalized with gastro-esophageal variceal hemorrhage. Indian Journal of Gastroenterology; 25(5): 240. Berzigotti A (2017): Advances and challenges in cirrhosis and portal hypertension. BMC medicine; 15(1): 200. Kim J H, Im C B, Lee S S, Jeon H, Choi J W, Kim H J & Lee O J (2021): Impact of acute kidney injury on mortality in patients with acute variceal bleeding. BMC gastroenterology; 21(1): 290. Ichikawa T, Machida N, Kaneko H, Oi I & Fujino M A (2019): C-reactive protein can predict patients with cirrhosis at a high risk of early mortality after acute esophageal variceal bleeding. Internal Medicine; 58(4): 487–95. Lee S W, Lee T Y & Chang C S (2009): Independent factors associated with recurrent bleeding in cirrhotic patients with esophageal variceal hemorrhage. Digestive diseases and sciences; 54(5): 1128–34. Gan Z H, Tsai C C, Tseng K C, Tsai C C, Hsieh Y H & Hung T H (2014): The effect of bacterial infections in cirrhotic patients with esophageal variceal bleeding. Annals of Hepatology; 13(3): 364–69. Chen C H, Sheu J C, Huang G T, Lee H S, Yang P M, Wong J M & Chen D S (1998): Characteristics of hepatocellular carcinoma presenting with variceal bleeding. Journal of gastroenterology and hepatology; 13(2): 170–74. Chung J W (2018): Role of endoscopic treatment or balloon-occluded retrograde transvenous obliteration in patients with Child-Pugh class C end-stage liver cirrhosis and esophageal/gastric varices. Clinical and Molecular Hepatology; 25(2): 181. 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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-9023233","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":619107524,"identity":"350cdae4-8fd1-46a0-ad57-2114b4179ef1","order_by":0,"name":"EL-Zahraa Meghezel","email":"","orcid":"","institution":"Sohag University","correspondingAuthor":false,"prefix":"","firstName":"EL-Zahraa","middleName":"","lastName":"Meghezel","suffix":""},{"id":619107527,"identity":"7c93d09f-f185-4d5d-b51f-852725eedccf","order_by":1,"name":"Asmaa Sayed","email":"data:image/png;base64,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","orcid":"","institution":"Sohag University","correspondingAuthor":true,"prefix":"","firstName":"Asmaa","middleName":"","lastName":"Sayed","suffix":""},{"id":619107528,"identity":"e5959e13-8f0f-49ee-b434-267aee300e74","order_by":2,"name":"Reem Makbol","email":"","orcid":"","institution":"Sohag University","correspondingAuthor":false,"prefix":"","firstName":"Reem","middleName":"","lastName":"Makbol","suffix":""}],"badges":[],"createdAt":"2026-03-03 19:10:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9023233/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9023233/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106728119,"identity":"73956302-ceb8-43aa-969b-208739343d1a","added_by":"auto","created_at":"2026-04-12 18:41:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":47787,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBP\u003c/strong\u003e: Blood pressure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRockall scores in patients with upper gastrointestinal bleeding [17]\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9023233/v1/31440e4c370a9f0ecc672480.jpg"},{"id":106728221,"identity":"d394eb80-cffe-4b2e-a65e-8fe44ce23150","added_by":"auto","created_at":"2026-04-12 18:42:11","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35273,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe ABC score for the prediction of 30-day mortality [20]\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9023233/v1/36f4844dad06868e07e36e52.jpg"},{"id":106702666,"identity":"4e7935ab-293b-439b-8f08-cdfe1f99f7f5","added_by":"auto","created_at":"2026-04-12 07:35:29","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":89974,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eALT:\u003c/strong\u003e Alanine transaminase.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eC-WATCH score scheme of the 7 steps for calculating the C-WATCH score [21]\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9023233/v1/1b3c1ba8bd08da59c90f2e55.jpg"},{"id":106960686,"identity":"3801fb24-870c-4c74-9e15-f818b9f9dd78","added_by":"auto","created_at":"2026-04-15 09:22:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2112055,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9023233/v1/f0bc27e0-c3b5-4341-973b-607126dca602.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Predictive and prognostic significance of the Age, blood tests and comorbidities (ABC) score, Cologne-watch (C-watch) score and Rockall score for risk of mortality following variceal bleeding among cirrhotic patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLiver cirrhosis (LC) is the final stage attained by slow progression of different chronic liver illnesses following years or decades, and it is marked by diffuse hepatic fibrosis \u0026amp; normal liver structures being replaced by regenerative liver nodules [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Liver diseases caused by alcohol, hepatitis B (HBV) and hepatitis C viruses (HCV), and non-alcoholic fatty liver disease (NAFLD) are the primary causes of cirrhosis [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Portal hypertension (PH) and associated consequences, such as gastro-esophageal varices (GEVs), variceal hemorrhage (VH), ascites, hepatorenal syndrome, portosystemic encephalopathy, and spontaneous bacterial peritonitis, are most commonly caused by cirrhosis [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. ]. PH is the major driver in the transition from the compensated to the \u0026lsquo;decompensated\u0026rsquo; stage of cirrhosis, that identified by the presence of clinical complications [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The main complication of the diseases is the gastrointestinal bleeding from the rupture of esophago-gastric varices, which is the leading cause of death in cirrhotic individuals [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAcute variceal bleeding is one of the most life-threatening complications. In the first two years of follow-up, 22\u0026ndash;61% of cirrhotic patients who get primary prophylaxis will have their first variceal bleeding [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The likelihood of rebleeding elevated for patients suffering from peptic ulcers and variceal hemorrhage. Rebleeding is also considered to be an important cause of increasing death, and it occurs in approximately 10\u0026ndash;30% of cases [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A number of clinical scores can be employed to classify the risk of complications, rebleeding, the necessity of clinical intervention, and mortality [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The Glasgow-Blatchford score (GBS), the AIMS65 score (albumin\u0026thinsp;\u0026lt;\u0026thinsp;30g/L (A), INR\u0026thinsp;\u0026gt;\u0026thinsp;1.5 (I), disturbed mental state (M), systolic blood pressure 90 (S), and age\u0026thinsp;\u0026gt;\u0026thinsp;65 years (65)), and the clinical Rockall score (CRS) are the most prominent utilized scoring systems [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The following scoring systems include post-endoscopic scoring tools (eg, Cedars Sinai, full Rockall score, as well as Progretto Nazionale Emorragia Digestiva) and pre-endoscopic scoring tools (eg, the pre-endoscopy Rockall, AIMS65, as well as GBS) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRockall score has been developed in 1996 to predict death and rebleeding, involving both the clinical Rockall score \u0026amp; the full Rockall score, the pre-endoscopic Rockall score is calculated using the parameters that are performed before an upper endoscopy is performed which include: Age, comorbid diseases, as well as shock. The post-endoscopic RS is based on the same parameters, as well as the data obtained during endoscopy, which include: The cause of bleeding, and evidence of bleeding as shown in \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In cases of variceal and non-variceal bleeding, it is both effective and easy to calculate. It is only possible to calculate the RS if an endoscopy has been performed [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn 2020, Laursen et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] released an updated pre-endoscopy risk score for upper and lower gastrointestinal bleeding, called the ABC score, which is based on many factors including age, blood tests, and comorbidities. In terms of mortality prediction, this score was more useful than AIMS65, the prior best score for this outcome [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This scoring system is based on three criteria: Age, blood test results, and comorbidity. Using a scale from 0 to 18, with the risk being categorized into low (3 points), moderate (4\u0026ndash;7 points), or high (8 points) as shown in \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe new Cologne WATCH (C-WATCH) score has been developed as a pre-endoscopic scoring system for acute variceal \u0026amp; non-variceal upper gastrointestinal bleeding (UGIB) and only incorporates laboratory values (C- reactive protein, white blood cell count, ALT, thrombocytes, creatinine, and hemoglobin). The minimum point value is 0 and the maximum point value is 8 as shown in \u003cb\u003e(Fig.\u0026nbsp;3)\u003c/b\u003e [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The Baylor bleeding score (BBS), the T-score (TSC), and the Cedars-Sinai Medical Center Predictive Index (CSMCPI) were some of the other predictive measures [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Some Prognosis in variceal bleeding is related especially to the severity of liver failure which assessed using Child\u0026ndash;Pugh\u0026ndash;Turcotte or MELD scores; in the majority of studies on variceal bleeding, which focus on the significance of classical prognostic scores concluded that the value was inferior in variceal bleeding in comparison with non-variceal bleeding [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e"},{"header":"Patients and Methods","content":"\u003cp\u003eA prospective cohort study was performed on 100 cirrhotic patients, presenting with upper gastrointestinal variceal bleeding, attended to Tropical Medicine and Gastroenterology Department of Sohag University Hospital. The study was conducted after being authorized by the Ethics Committee of the Sohag Faculty of Medicine. All patients signed an informed consent. IRB: Soh-Med-24-03-04MS.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAll patients were subjected to\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eComplete history taking.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eClinical examination:\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eVital signs (pulse 60\u0026ndash;100 beats per minute, blood pressure 120/80 mm/Hg to 90/60 mm/Hg and temperature 36.2\u0026deg;C-37.5\u0026deg;C) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eComplete general and local examination.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLaboratory investigation:\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eComplete blood count (Hemoglobin (Hb), white blood cells (WBC) and platelet).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eLiver function test as alanine transaminase (ALT), aspartate transaminase (AST), serum albumin, total bilirubin, Prothrombin time (PT), Prothrombin concentration (PC), International normalized ratio (INR) and child pugh score which is based on (Encephalopathy ascites, serum albumin, total bilirubin and INR), classified into child A (5:6), child B (7:9) and child C (10:15) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSerum creatinine, urea and C-reactive protein (CRP).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAscitic fluid study for patients with ascites.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSerology for hepatitis C virus (HCV) and hepatitis B virus (HBV).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePredicting outcomes and assessment risk of mortality by ABC score, C-watch score and Rockall score.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eRadiological investigation\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e-\u003c/b\u003eAbdominal ultrasound with comment on:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eLiver size (The average liver span in the midclavicular line for the overall collective was 15.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5 cm) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], echopattern (homogenous or coarse), surface (smooth or irregular) and the presence or absence of focal lesions.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePortal vein diameter (The normal portal vein diameter does not exceed 13mm) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], patency and presence of collaterals.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSpleen size (Average splenic length of 12 cm), echopattern and splenic vein diameter\u0026thinsp;\u0026lt;\u0026thinsp;10 mm diameter [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePresence of ascites or not.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEndoscopic with comment on:\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eEsophageal varices:\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e-Size: Mildly filled (F1), moderately filled (F2) or markedly filled (F3).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e- Color: Colored white (Cw) or colored blue (Cb).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e-Red color sign (RC): Positive or negative.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eGastric varies: Extension or isolated.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStigmata of recent bleeding.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWe also comment on associated lesions with varices as (Mallory-Weiss tear, peptic ulcer, erosive disease, esophagitis and malignancy).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eStatistics for the Social Sciences (SPSS) version 26, which is also utilized to display the outcomes, was employed for data entry and analysis. Data that did not follow a normal distribution were summarized using (IQR) and median. For quantitative data that did follow a normal distribution, means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations were utilized, whereas descriptive statistics were used for qualitative data. Using the Shapiro-Wilk test, we checked for a normal distribution of the data.\u003c/p\u003e \u003cp\u003eUsing a \u003cem\u003eChi-square test, Fisher's exact test\u003c/em\u003e, or \u003cem\u003eMonte Carlo significant testing\u003c/em\u003e (in cases where 20% or more of the total predicted cell counts were less than 5), we were able to discover the link between result groups and qualitative data. Independent sample \u003cem\u003et tests\u003c/em\u003e or \u003cem\u003eMann-Whiteny U tests\u003c/em\u003e, depending on distributional assumptions, were used to identify associations between groups and quantitative data.\u003c/p\u003e \u003cp\u003eBinary logistic regression analysis, both univariate and multivariate, was used to identify characteristics that predicted rebleeding and mortality. If the P value of the variables in the outcome groups' bivariate analysis was less than or equal to 0.25, they were included in the regression analysis. The variables from the univariate model were used in the multivariate analysis, which employed the backward elimination approach, and had a P value of less than 0.05 for removal and a P value of \u0026le;\u0026thinsp;0.25 for variables.\u003c/p\u003e \u003cp\u003eUtilizing a receiver operating characteristics (ROC) curve, researchers assessed the sensitivity and specificity of the tested biomarkers in detecting rebleeding and mortality. The cutoff values were obtained using Youden's index. Significance was determined using a p-value that was less than 0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eFrom March 2024 to March 2025, a total of 100 patients were included in the study. Outcome of the studied patients was variable between good prognosis in 56% of patients and poor prognosis that divided into mortality which occurred in 36% of the cases and rebleeding in 8% of the cases as shown in \u003cb\u003e(Table\u0026nbsp;1).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eRegarding risk of mortality, the mean age of the studied patients was statistically significantly higher among mortality group compared to survivor group (P value: 0.03). In addition, percentage of diabetic patients was higher statistically significant in mortality group than survivor group (P value: 0.03) as shown in \u003cb\u003e(Table\u0026nbsp;2).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWhen we studied the risk of mortality as regard examination data of studied patients, we found that presence of pallor, jaundice and ascites were higher statistically significant in mortality group than survivor group (P values: 0.047, 0.046 respectively) as shown in \u003cb\u003e(Table\u0026nbsp;2).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAs regard laboratory investigation, it was found that there was statistically significant association between mortality and decreased serum albumin, increased INR and child score C (P value: 0.001, 0.02 and 0.01 respectively). There was significant association between mortality and increased serum creatinine and CRP (P values: 0.03, 0.001 respectively). As regarding ascitic fluid study we detected that SBP was highly statistically significant in mortality group than survivor (P value: 0.002) as shown in \u003cb\u003e(Table\u0026nbsp;3).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAbdominal ultrasound finding showed a higher statistically significant association between risk of mortality and presence of HFL (P value: 0.001) as shown in \u003cb\u003e(Table\u0026nbsp;4).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWhen we studied the role of scoring system in predicting mortality, we found that ABC score was the only statistically significant score to predict mortality (P value: \u0026lt;0.001) with significant higher ABC score risk in mortality than survivor group (P value: 0.001) as shown in \u003cb\u003e(Table\u0026nbsp;5).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn the univariate and multivariate analysis, we found that increased age, DM, decreased serum albumin level, increased INR, Child score C, occurrence of SBP, increased CRP level, presence of dilated thrombosed portal vein, presence of HFL, ascites and increased ABC score were statistically significant predictors of mortality in the univariate analysis (P value: 0.048, 0.03, 0.002, 0.03, 0,01, 0,03, 0.005, 0.04, 0,002, 0.04, \u0026lt;\u0026thinsp;0.001 respectively). However, multivariate logistic regression results revealed that increase in INR, presence of dilated thrombosed portal vein and increase in ABC score were statistically significant predictors for mortality (P value: 0.04, 0.003, \u0026lt;\u0026thinsp;0.001 respectively) as shown in \u003cb\u003e(Table\u0026nbsp;6).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eDiagnostic performance of the studied scores in prediction of mortality showed the studied three scores had no statistically significance diagnostic performance in prediction of mortality. Despite that, ABC score showed the highest AUC in predicting mortality of 72.6% with significant diagnostic ability in predict mortality as shown in \u003cb\u003e(Table\u0026nbsp;7).\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;(1): Outcome results of the studied patients\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\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\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMortality\u003c/b\u003e: N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSummary statistics (n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (36)\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\u003eRebleeding\u003c/b\u003e: N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGood prognosis\u003c/b\u003e: N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (56)\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 \u003cb\u003eTable\u0026nbsp;(2): Risk of mortality as regard baseline clinical and examination data of the studied patients\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge:\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMortality group (n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivor group (n\u0026thinsp;=\u0026thinsp;64)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e \u003cp\u003e65 (58.5:70)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e \u003cp\u003e62 (54.3:67)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03*\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender:\u003c/p\u003e \u003cp\u003eFemale N (%)\u003c/p\u003e \u003cp\u003eMale N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (22.2)\u003c/p\u003e \u003cp\u003e28 (77.8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (40.6)\u003c/p\u003e \u003cp\u003e38 (59.4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003csup\u003e\u0026sect;\u003c/sup\u003e\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\u003eDiabetes\u003c/b\u003e: N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (55.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e*\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e: N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.72\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCo-morbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLC associated with\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eheart disease\u003c/b\u003e: N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLC associated with\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003erenal failure\u003c/b\u003e: N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHead \u0026amp; Neck\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eNormal N (%)\u003c/p\u003e \u003cp\u003ePallor N (%)\u003c/p\u003e \u003cp\u003eJaundice N (%)\u003c/p\u003e \u003cp\u003ePallor \u0026amp; jaundice N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (13.9)\u003c/p\u003e \u003cp\u003e18 (50)\u003c/p\u003e \u003cp\u003e4 (11.1)\u003c/p\u003e \u003cp\u003e9 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (25)\u003c/p\u003e \u003cp\u003e36 (56.3)\u003c/p\u003e \u003cp\u003e8 (12.5)\u003c/p\u003e \u003cp\u003e4 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.047\u003c/b\u003e*\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUpper limb\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eNormal N (%)\u003c/p\u003e \u003cp\u003eFlapping tremors N (%)\u003c/p\u003e \u003cp\u003ePalmar erythema N (%)\u003c/p\u003e \u003cp\u003eFlapping tremors \u0026amp;\u003c/p\u003e \u003cp\u003ePalmer erythema N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (25)\u003c/p\u003e \u003cp\u003e12 (33.3)\u003c/p\u003e \u003cp\u003e9 (25)\u003c/p\u003e \u003cp\u003e6 (16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (40.6)\u003c/p\u003e \u003cp\u003e23 (35.9)\u003c/p\u003e \u003cp\u003e8 (12.5)\u003c/p\u003e \u003cp\u003e7 (10.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.23\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLower limb\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eNormal N (%)\u003c/p\u003e \u003cp\u003eLower limb oedema N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (61.1)\u003c/p\u003e \u003cp\u003e14 (38.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (71.9)\u003c/p\u003e \u003cp\u003e18 (28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAbdomen\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eNormal N (%)\u003c/p\u003e \u003cp\u003eAscites N (%)\u003c/p\u003e \u003cp\u003eSplenomegaly N (%)\u003c/p\u003e \u003cp\u003eHepatomegaly N (%)\u003c/p\u003e \u003cp\u003eAscites \u0026amp; organomegaly N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (38.8)\u003c/p\u003e \u003cp\u003e10 (27.8)\u003c/p\u003e \u003cp\u003e6 (16.7)\u003c/p\u003e \u003cp\u003e2 (5.6)\u003c/p\u003e \u003cp\u003e4 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (45.3)\u003c/p\u003e \u003cp\u003e7 (10.9)\u003c/p\u003e \u003cp\u003e18 (28.1)\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e10 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.046\u003c/b\u003e\u003csup\u003e*\u0026Dagger;\u003c/sup\u003e\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 \u003csup\u003e\u0026dagger;\u003c/sup\u003e Mann-Whiteny U test, \u003csup\u003e\u0026sect;\u003c/sup\u003e Chi squared test, \u003csup\u003e\u0026dagger;\u003c/sup\u003e Fisher\u0026rsquo;s Exact test, \u003csup\u003e\u0026Dagger;\u003c/sup\u003e Monte Carlo test, * Significant at level\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLC\u003c/b\u003e: Liver cirrhosis; \u003cb\u003eSBP\u003c/b\u003e: Systolic blood pressure; \u003cb\u003eDBP\u003c/b\u003e: Diastolic blood pressure.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;(3): Risk of mortality as regard laboratory investigations of the studied patients\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabc\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMortality group (n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivor group (n\u0026thinsp;=\u0026thinsp;64)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eCBC\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\u003eHb (mg/dl)\u003c/b\u003e: Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003cp\u003e7.8 (6.8:9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4 8.9 (7.3:10.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWBCs\u003c/b\u003e: Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.9\u003c/p\u003e \u003cp\u003e7 (4:9.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.3\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1 5.9 (4.1:12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlatelet\u003c/b\u003e: Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141.4\u0026thinsp;\u0026plusmn;\u0026thinsp;92.3\u003c/p\u003e \u003cp\u003e118 (72:194.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123\u0026thinsp;\u0026plusmn;\u0026thinsp;78.1 95 (65.5:168.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLFT\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALT\u003c/b\u003e (IU/L): Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68.5\u0026thinsp;\u0026plusmn;\u0026thinsp;111\u003c/p\u003e \u003cp\u003e24.5 (15:60.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36.8\u0026thinsp;\u0026plusmn;\u0026thinsp;39.5 24 (15:40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAST\u003c/b\u003e (IU/L): Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103\u0026thinsp;\u0026plusmn;\u0026thinsp;180\u003c/p\u003e \u003cp\u003e45 (23:96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52.2\u0026thinsp;\u0026plusmn;\u0026thinsp;60.7 35 (20.3:55.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlb\u003c/b\u003e (g/dl): Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eT.Bil\u003c/b\u003e (mg/dl): Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003cp\u003e1.4 (0.8:2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 1.2 (0.8:1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePT\u003c/b\u003e: Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.6 15.6 (13.2:17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4 14.8 (13.1:16.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePC\u003c/b\u003e: Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66\u0026thinsp;\u0026plusmn;\u0026thinsp;20.3\u003c/p\u003e \u003cp\u003e63.1 (52.3:75.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.4\u0026thinsp;\u0026plusmn;\u0026thinsp;16.9 69.4 (59:79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eINR\u003c/b\u003e: Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003cp\u003e1.3 (1.2:1.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2 1.2 (1.1:1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e*\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild score\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eA N (%)\u003c/p\u003e \u003cp\u003eB N (%)\u003c/p\u003e \u003cp\u003eC N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (11.1)\u003c/p\u003e \u003cp\u003e17 (47.2)\u003c/p\u003e \u003cp\u003e15 (41.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (25) 38 (59.4) 10 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e*\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSerology\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eNegative N (%)\u003c/p\u003e \u003cp\u003eHCV N (%)\u003c/p\u003e \u003cp\u003eHBV N (%)\u003c/p\u003e \u003cp\u003eUnknown N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (16.7)\u003c/p\u003e \u003cp\u003e27 (75)\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e3 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (15.6) 45 (70.3) 5 (7.8) 4 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.41\u003csup\u003eǂ\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOthers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCreatinine\u003c/b\u003e (mg/dl): Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003cp\u003e1 (0.7:1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003cp\u003e0.8 (0.5:1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e*\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrea (mg/dl)\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.7\u0026thinsp;\u0026plusmn;\u0026thinsp;68.2\u003c/p\u003e \u003cp\u003e33 (17:72.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.2\u0026thinsp;\u0026plusmn;\u0026thinsp;36.2\u003c/p\u003e \u003cp\u003e27 (17:43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCRP (mg/l)\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.1\u0026thinsp;\u0026plusmn;\u0026thinsp;40.8\u003c/p\u003e \u003cp\u003e47.2 (21.5:69.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.9\u0026thinsp;\u0026plusmn;\u0026thinsp;33.8\u003c/p\u003e \u003cp\u003e13.6 (5:38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e*\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAFS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;26)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;31)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSBP: N (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (26.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTLC\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e577.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1043.1\u003c/p\u003e \u003cp\u003e307.5 (97:586.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e277\u0026thinsp;\u0026plusmn;\u0026thinsp;253.4\u003c/p\u003e \u003cp\u003e200 (150:315)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.54\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePolymorphs\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50.3\u0026thinsp;\u0026plusmn;\u0026thinsp;30.2\u003c/p\u003e \u003cp\u003e45 (21.3:81.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.9\u0026thinsp;\u0026plusmn;\u0026thinsp;21.7\u003c/p\u003e \u003cp\u003e10 (5:40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e*\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProtein\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.9\u003c/p\u003e \u003cp\u003e1 (0.7:1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003cp\u003e0.9 (0.6:1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003csup\u003e\u0026sect;\u003c/sup\u003e\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 \u003csup\u003e\u0026dagger;\u003c/sup\u003e Fisher\u0026rsquo;s Exact test, \u003csup\u003e\u0026sect;\u003c/sup\u003e Mann-Whiteny U test, * Significant at level\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCBC\u003c/b\u003e: Complete blood count; \u003cb\u003eHb\u003c/b\u003e: Haemoglobin; \u003cb\u003eWBC\u003c/b\u003e: White blood cells; \u003cb\u003eLFT\u003c/b\u003e: Liver function test; \u003cb\u003eALT\u003c/b\u003e: Alanine transaminase; \u003cb\u003eAST\u003c/b\u003e: Aspartate transaminase; \u003cb\u003eAlb\u003c/b\u003e: Albumin; \u003cb\u003eT.Bil\u003c/b\u003e: Total bilirubin; \u003cb\u003ePT\u003c/b\u003e: Prothrombin time; \u003cb\u003ePC\u003c/b\u003e: Prothrombin concentration; \u003cb\u003eINR\u003c/b\u003e: International normalized ratio; \u003cb\u003eHCV\u003c/b\u003e: Hepatitis C virus; \u003cb\u003eHBV\u003c/b\u003e: Hepatitis B virus; \u003cb\u003eCRP\u003c/b\u003e: C-reactive protein; \u003cb\u003eAFS\u003c/b\u003e: Ascitic fluid study; \u003cb\u003eSBP\u003c/b\u003e: Spontaneous bacterial peritonitis; \u003cb\u003eTLC\u003c/b\u003e: Total leucocytic count.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;(4): Risk of mortality as regard abdominal U/S of the studied patients\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabd\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLiver size:\u003c/p\u003e \u003cp\u003eAverage N (%)\u003c/p\u003e \u003cp\u003eEnlarged N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMortality group (n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivor group (n\u0026thinsp;=\u0026thinsp;64)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 (83.3)\u003c/p\u003e \u003cp\u003e6 (16.7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (87.5)\u003c/p\u003e \u003cp\u003e8 (12.5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver echo-pattern:\u003c/p\u003e \u003cp\u003eCoarse N (%)\u003c/p\u003e \u003cp\u003eHeterogeneous\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (91.7)\u003c/p\u003e \u003cp\u003e3 (8.3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58 (90.6)\u003c/p\u003e \u003cp\u003e6 (9.4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0\u003csup\u003e\u0026sect;\u003c/sup\u003e\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\u003ePortal vein\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eNormal N (%)\u003c/p\u003e \u003cp\u003eDilated N (%)\u003c/p\u003e \u003cp\u003eThrombosed N (%)\u003c/p\u003e \u003cp\u003eDilated \u0026amp; thrombosed N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (47.2)\u003c/p\u003e \u003cp\u003e7 (19.4)\u003c/p\u003e \u003cp\u003e5 (13.9)\u003c/p\u003e \u003cp\u003e7 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (53.1)\u003c/p\u003e \u003cp\u003e21 (32.8)\u003c/p\u003e \u003cp\u003e6 (9.4)\u003c/p\u003e \u003cp\u003e3 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHFL\u003c/b\u003e: N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5 (7.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e*\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSpleen size\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eAverage N (%)\u003c/p\u003e \u003cp\u003eEnlarged N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (27.8)\u003c/p\u003e \u003cp\u003e26 (72.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (21.9)\u003c/p\u003e \u003cp\u003e50 (78.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.51\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDilated splenic vein\u003c/b\u003e: N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10 (15.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAscites\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eNo N (%)\u003c/p\u003e \u003cp\u003eMild N (%)\u003c/p\u003e \u003cp\u003eModerate N (%)\u003c/p\u003e \u003cp\u003eMarked N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (27.8)\u003c/p\u003e \u003cp\u003e10 (27.8)\u003c/p\u003e \u003cp\u003e9 (25)\u003c/p\u003e \u003cp\u003e7 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (51.6)\u003c/p\u003e \u003cp\u003e10 (15.6)\u003c/p\u003e \u003cp\u003e12 (18.8)\u003c/p\u003e \u003cp\u003e9 (14.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003csup\u003e\u0026dagger;\u003c/sup\u003e\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 \u003csup\u003e\u0026dagger;\u003c/sup\u003e Fisher\u0026rsquo;s Exact test, \u003csup\u003e\u0026sect;\u003c/sup\u003e Monte Carlo test. \u003cb\u003eHFL\u003c/b\u003e: Hepatic focal lesion.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;(5): Risk of mortality as regard scoring system of the studied patients\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabe\" border=\"1\"\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eRockall score\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD Median\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMortality group (n\u0026thinsp;=\u0026thinsp;36)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSurvivor group (n\u0026thinsp;=\u0026thinsp;64)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.6\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u003c/p\u003e \u003cp\u003e5 (5:7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003cp\u003e5 (5:6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003csup\u003e\u0026dagger;\u003c/sup\u003e\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\u003eRockall score risk\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eModerate N (%)\u003c/p\u003e \u003cp\u003eHigh N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (52.8)\u003c/p\u003e \u003cp\u003e17 (47.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (65.6)\u003c/p\u003e \u003cp\u003e22 (34.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABC score\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003cp\u003e8 (6:11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003cp\u003e6 (5:7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;\u003cb\u003e0.001\u003c/b\u003e*\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABC score risk\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eLow N (%)\u003c/p\u003e \u003cp\u003eModerate N (%)\u003c/p\u003e \u003cp\u003eHigh N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e15 (41.7)\u003c/p\u003e \u003cp\u003e21 (58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.6)\u003c/p\u003e \u003cp\u003e49 (76.6)\u003c/p\u003e \u003cp\u003e14 (21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\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\u003e\u003cb\u003eC-watch score\u003c/b\u003e: Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD Median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003cp\u003e5 (4:5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.97\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2\u003c/p\u003e \u003cp\u003e4 (3:5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003csup\u003e\u0026dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC-watch score complication risk\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e5% N (%)\u003c/p\u003e \u003cp\u003e10% N (%)\u003c/p\u003e \u003cp\u003e18% N (%)\u003c/p\u003e \u003cp\u003e30% N (%)\u003c/p\u003e \u003cp\u003e45% N (%)\u003c/p\u003e \u003cp\u003e62% N (%)\u003c/p\u003e \u003cp\u003e76% N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003cp\u003e1 (2.8)\u003c/p\u003e \u003cp\u003e7 (19.4)\u003c/p\u003e \u003cp\u003e9 (25)\u003c/p\u003e \u003cp\u003e15 (41.7)\u003c/p\u003e \u003cp\u003e2 (5.6)\u003c/p\u003e \u003cp\u003e2 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (3.1)\u003c/p\u003e \u003cp\u003e4 (6.3)\u003c/p\u003e \u003cp\u003e17 (26.6)\u003c/p\u003e \u003cp\u003e20 (31.1)\u003c/p\u003e \u003cp\u003e13 (20.3)\u003c/p\u003e \u003cp\u003e8 (12.5)\u003c/p\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003csup\u003e\u0026Dagger;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC-watch score complication risk\u003c/b\u003e:\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;18% N (%)\u003c/p\u003e \u003cp\u003e18\u0026ndash;45% N (%)\u003c/p\u003e \u003cp\u003e\u0026gt;45% N (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (22.2)\u003c/p\u003e \u003cp\u003e24 (66.7)\u003c/p\u003e \u003cp\u003e4 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (35.9)\u003c/p\u003e \u003cp\u003e33 (51.6)\u003c/p\u003e \u003cp\u003e8 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003csup\u003e\u0026sect;\u003c/sup\u003e\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 \u003csup\u003e\u0026dagger;\u003c/sup\u003e Mann-Whiteny U test, \u003csup\u003e\u0026sect;\u003c/sup\u003e Fisher\u0026rsquo;s Exact test, \u003csup\u003e\u0026Dagger;\u003c/sup\u003e Monte Carlo test.\u003c/p\u003e \u003cp\u003e \u003cb\u003eABC\u003c/b\u003e: Age, blood tests and comorbidities; \u003cb\u003eC-watch\u003c/b\u003e: Cologne watch.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;(6): Univariate and multivariate binary logistic regression of predictors of mortality\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabf\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eUnivariate\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnadjusted OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.04 (1:1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.048\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale gender\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.4 (0.9:6.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDM\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.6 (1.1:5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHb\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.9 (0.7:1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAST\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.01 (0.99:1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlbumin\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.29 (0.1:0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePT\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.04 (0.96:1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eINR\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.9 (1.2:38.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChild score\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eA\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eB\u003c/p\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e1.8 (0.5:6.2)\u003c/p\u003e \u003cp\u003e6 (1.5:23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003cp\u003e\u003cb\u003e0.01\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSBP occurrence\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.9 (1.2:20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.03\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCreatinine\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.7 (0.98:3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCRP\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.02 (1.01:1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\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\u003e\u003cb\u003ePortal vein\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eNormal \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDilated\u003c/p\u003e \u003cp\u003eThrombosed\u003c/p\u003e \u003cp\u003eDilated \u0026amp; thrombosed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.67 (0.2:1.9)\u003c/p\u003e \u003cp\u003e1.7 (0.4:6.3)\u003c/p\u003e \u003cp\u003e4.7 (1.1:20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003cp\u003e0.45\u003c/p\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHFL\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5.9 (1.9:18.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAscites\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003eMild\u003c/p\u003e \u003cp\u003eModerate\u003c/p\u003e \u003cp\u003eMarked\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e3.3 (1.1:10.2)\u003c/p\u003e \u003cp\u003e2.5 (0.8:7.6)\u003c/p\u003e \u003cp\u003e2.6 (0.8:8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e*\u003c/p\u003e \u003cp\u003e0.11\u003c/p\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRockall score\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.4 (0.9:2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABC score\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.4 (1.2:1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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\u003e\u003cb\u003eC-watch score\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.4 (0.98:2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eMultivariate\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eABC score\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.6 (1.2:2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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\u003e\u003cb\u003ePortal vein\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eNormal \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDilated\u003c/p\u003e \u003cp\u003eThrombosed\u003c/p\u003e \u003cp\u003eDilated \u0026amp; thrombosed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003e0.8 (0.2:2.6)\u003c/p\u003e \u003cp\u003e2.1 (0.4:10.8)\u003c/p\u003e \u003cp\u003e14.3 (2.5:80.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003cp\u003e0.39\u003c/p\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eINR\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.6 (1.1:41.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.04\u003c/b\u003e*\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 \u003csup\u003ea\u003c/sup\u003e reference group, * Significant at level\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDM\u003c/b\u003e: Diabetes Melius; \u003cb\u003eHb\u003c/b\u003e: Haemoglobin; \u003cb\u003eAST\u003c/b\u003e: Aspartate transaminase; \u003cb\u003ePT\u003c/b\u003e: Prothrombin time; \u003cb\u003eINR\u003c/b\u003e: International normalized ratio; \u003cb\u003eSBP\u003c/b\u003e: Spontaneous bacterial peritonitis; \u003cb\u003eCRP\u003c/b\u003e: C- reactive protein; \u003cb\u003eHFL\u003c/b\u003e: Hepatic focal lesion; \u003cb\u003eABC\u003c/b\u003e: Age, blood tests and comorbidities; \u003cb\u003eC-watch\u003c/b\u003e: Cologne watch.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;(7): Diagnostic performance of the studied scores in prediction of mortality\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabg\" border=\"1\"\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eRockall score\u003c/b\u003e:\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% 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\u003eCutoff point\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.5%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5:0.7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.8%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85.9%\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\u003eABC score\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6:0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e93.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eC-watch score\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5:0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e52.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e67.2%\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 \u003cb\u003eABC\u003c/b\u003e: Age, blood tests and comorbidities; \u003cb\u003eC- watch\u003c/b\u003e: Cologne watch.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe current study included 100 patients with acute upper gastrointestinal variceal bleeding secondary to liver cirrhosis. Our study detected that mortality occurred in 36% of cases, rebleeding in 8%, while 56% had a good prognosis. This mortality rate is agreed with previous studies by Garcia-Tsao et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], who have reported variable mortality rates in variceal bleeding, ranging from 15% to 40%, depending on liver function status and timing of intervention. Possible explanations for the high mortality rate in our study include advanced portal hypertension, severe underlying cirrhosis, delayed presentation, or insufficient healthcare resources. Otherwise, a prior study by Lo et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] reported that the rate of early rebleeding following UGIB was between 9% and 19%, which is close to our result (8%).\u003c/p\u003e \u003cp\u003eRegarding risk of mortality, the present study revealed that age was statistically significant higher in the mortality group compared to survivor which agreed with Reverter et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], who demonstrated that older age was independently predicted mortality in patients with acute variceal bleeding. This finding suggests that advanced age is an important predictor of mortality in patients with variceal bleeding as older patients often present with multiple comorbidities, reduced physiological reserve, and impaired hepatic and renal function, all of which may contribute to poorer outcomes [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], emphasizing the need for close monitoring and aggressive management in elderly individuals.\u003c/p\u003e \u003cp\u003eDiabetes mellitus also statistically significant increased mortality risk. This result agreed with Trombetta et al., and Yang et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], who found that diabetes mellitus significantly correlated with gastroesophageal variceal bleeding and showed an increased risk of mortality. This result could be explained by the fact that hyperglycemia increases the risk of variceal hemorrhage and mortality by causing splanchnic hyperemia, increasing portal blood flow as a result of blood sugar fluctuations that raise portal pressure, and impacting tissue repair and wound healing [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eExamination of our patients revealed that pallor had statistically significant association with increased morality which agreed with Raţiu et al. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], who detected that pallor was indicator of severe anemia associated with increasing mortality in variceal bleeding. This can be explained by that anemia reflects significant blood loss, hemodynamic stress, and reduced oxygen-carrying capacity, all of which worsen prognosis [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Also, presence of jaundice also associated with increased mortality rate. Our finding was similar to Mohammad et al. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], who detected that serum bilirubin\u0026thinsp;\u0026gt;\u0026thinsp;3 mg/dl is a predictor of mortality in patient with variceal bleeding.\u003c/p\u003e \u003cp\u003eThe presence of ascites on clinical examination shows statistically significant association with increased mortality rate, and align with Nevens et al., and Hori et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. This is due to ascites marks a decompensated cirrhotic, reflecting advanced portal hypertension and hemodynamic dysregulation, as well as possible renal impairment, these factors act as independent drivers of poor outcomes following variceal bleeding [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLaboratory parameters of our patients revealed that decreased in serum albumin showed highly statistically significant association with increased mortality rate. Similar, Krige et al., and Min et al. [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] demonstrated that albumin, as a marker of hepatic synthetic function, is a critical prognostic factor in variceal bleeding and mortality. Our patients who had increased INR also showed statistically significant association with increased mortality, this agreed with Shingina et al. [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], who shown that coagulation markers, such as INR\u0026thinsp;\u0026gt;\u0026thinsp;1.5, are significant independent predictors of mortality and should be used in early risk classification for cirrhotic patients with variceal haemorrhage.\u003c/p\u003e \u003cp\u003eWe also detected that Child-Pugh C had statistically significant increased risk of mortality. These findings aligned with Garc\u0026iacute;a-Pag\u0026aacute;n et al. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], who detect Child-Pugh score for a long time has been used to categorize patients at risk of mortality; patients in Child-Pugh class C have a very bad prognosis. Clinical research and clinical practice both continue to utilize the Child-Pugh score as the gold standard for assessing variceal bleeding which is detected by D'Amico et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], who found that mortality was particularly high in Child class C patients who required longer hospital stays.\u003c/p\u003e \u003cp\u003eIncreased in serum creatinine also showed statistically significant association with increased risk of mortality, this agreed with Ismail et al., and Berzigotti, [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. As the development of hepatorenal syndrome can worsen systemic perfusion and hepatic decompensation, thereby increasing the risk of death. Kim et al. [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] identified serum creatinine as an independent predictor of in-hospital mortality in acute variceal haemorrhage.\u003c/p\u003e \u003cp\u003eWe detected that CRP was highly statistically significantly elevated in the mortality group. This profound inflammatory state likely reflects systemic infection, tissue damage, or the inflammatory of advanced liver disease, this was in agreement with Ichikawa et al. [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e], who discovered that increased C-reactive protein levels would have predicted 6-week mortality following oesophageal variceal haemorrhage, even in the absence of clinically apparent infection.\u003c/p\u003e \u003cp\u003eOur result revealed that spontaneous bacterial peritonitis increased mortality rate, which is agreed with Lee et al. [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], who found that bacterial infections, particularly SBP, significantly raise the risk of mortality in cirrhotic patients with variceal bleeding. This result may be explained by that SBP exacerbates oesophageal variceal bleeding by increasing sinusoidal pressure, disrupting haemostasis, as well as endotoxemia, which are triggers for variceal bleeding in cirrhotic patients [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePresence of hepatic focal lesions is associated with an elevated and statistically significant risk of mortality that is in agreement with Chen et al. [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], who found that HCC patients with acute variceal bleeding had a worse prognosis. Also, Chung, [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] detected that HCC, commonly accompanied by acute variceal bleeding (AVB), is known as a poor prognostic factor in AVB patients. This can be explained by HCC linked to underlying cirrhosis and/or tumor invasion of the portal vein, which can result in thrombosis and portal hypertension-induced variceal bleeding [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Patients with severe HCC are at increased risk of variceal bleeding and death due to the decrease in serum levels of several blood clotting factors caused by the liver's decreased plasma protein production [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe detected that ABC score was highly statistically significant in predicting mortality, this was strongly supported by Jimenez-Rosales et al. [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], who demonstrated ABC score's superiority in predicting mortality in cirrhotic patients complicated by variceal haemorrhage (AUROC 0.804), and Laursen et al. [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], who validated ABC score as an accurate mortality predictor.\u003c/p\u003e \u003cp\u003eRockall score was not significant to predict mortality, this result agreed with Stanley et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], who found Rockall score had limited utility for mortality prediction.\u003c/p\u003e \u003cp\u003eAlso, C-watch score is getting close to the performance but still not significant. This finding suggests that while the C-watch score was originally developed and validated for general upper gastrointestinal bleeding, its applicability may be limited in cases specifically related to portal hypertension and variceal haemorrhage. Similar findings were reported by Allo et al. [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e], who noted that although the C-watch score showed good discriminative ability in non-variceal bleeding, its performance was less in patients with variceal bleeding.\u003c/p\u003e \u003cp\u003eIn multivariate analysis; ABC score, PVT and INR were predictor for mortality. This may be explained that portal vein thrombosis and dilation may indicate more advanced portal hypertension and impaired hepatic perfusion, both of which can worsen patient outcomes which contributes to increased variceal pressure and risk of rebleeding, which may further explain the observed rise in mortality [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eDiagnostic performance of the studied scores in prediction of mortality showed that, except for the ABC score, which had the most significant diagnostic capacity in predicting death with an AUC of 72.6%, none of the other three scores exhibited any meaningful diagnostic performance in mortality prediction. Our findings were agreed with Liu et al. [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], who found that, among all scores, the ABC score had the best AUROC value of 0.72 for predictive of 30-day mortality in UGIB patients.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eUnivariate logistic regression analysis showed that advanced age, presence of diabetes mellitus, hypoalbuminemia, prolonged INR, child score C, ascetic fluid infection, increased CRP, presence of combined dilated and thrombosed portal vein, HFL and ascites on ultrasound and ABC score are predictors, while multivariate showed that ABC score, dilated and thrombosed portal vein and prolonged INR are the only predictors of mortality.\u003c/p\u003e \u003cp\u003eConventional endoscopic stigmata and commonly used upper-GI bleeding scores showed limited value for predicting death. Among the evaluated scoring systems, the ABC score showed the best predictive performance for mortality.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eLC Liver cirrhosis, HBV hepatitis B virus, HCV hepatitis C virus, NAFLD non-alcoholic fatty liver disease, PH portal hypertension, GEVs gastro-esophageal varices, VH variceal hemorrhage, CRS clinical Rockall score, ABC Age, blood tests and comorbidities score, AIMS65 AIMS65 score, GBS Glasgow-Blatchford, C- WATCH Cologne watch, UGIB upper gastrointestinal bleeding, BBS Baylor bleeding score, CSMCPI Cedars\u0026ndash;Sinai Medical Center Predictive Index, TSC T-score, Hb hemoglobin, WBC white blood cells, ALT alanine transaminase, AST aspartate transaminase, PT prothrombin time, PC prothrombin concentration, INR International normalized ratio, CRP C-reactive protein, F1 mildly filled, F2 moderately filled, F3 markedly filled, Cw colored white, Cb colored blue and RC red color sign.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAsmaa sayed wrote the main manuscript text and collect patients data.Reem.M.Makbol revised the collected data and selected figures and tables.EL-Zahraa.M.Megheizel was the supervisor and detect the number of cases and main All reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eManns M P, Czaja A J, Gorham J D, Krawitt E L, Mieli-Vergani G, Vergani D \u0026amp; Vierling J M (2010): Diagnosis and management of autoimmune hepatitis. 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Digestive Diseases; 40(6): 826\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCostache R S, Dragomirică A S, Dumitraș E A, Mariana J, Căruntu A, Popescu A \u0026amp; Costache D O (2021): Portal vein thrombosis: A concise review. Experimental and Therapeutic Medicine; 22(1): 759.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu S, Zhang X, Walline J H, Yu X \u0026amp; Zhu H (2021): Comparing the performance of the ABC, AIMS65, GBS, and pRS scores in predicting 90-day mortality or rebleeding among emergency department patients with acute upper gastrointestinal bleeding: A prospective multicenter study. Journal of Translational Internal Medicine; 9(2): 114\u0026ndash;22.\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":"Liver cirrhosis, mortality rate and ABC score","lastPublishedDoi":"10.21203/rs.3.rs-9023233/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9023233/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eAcute variceal bleeding is one of the most life-threatening complications of liver cirrhosis. The development of several risk assessment score systems has led to the prediction of outcomes like rebleeding and death. These systems include pre- and post-endoscopy evaluations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eTo predict outcome of variceal bleeding in cirrhotic patients and detect risk factor of mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient and Methods: \u003c/strong\u003eOne hundred cirrhotic patients were admitted to Sohag University Hospital, presenting with upper gastrointestinal variceal bleeding between March 2024 and March 2025. All participants will be subjected to: Complete history, clinical examination, laboratory investigation (Complete blood count, liver and renal function tests, C-reactive protein (CRP) and ascitic fluid study), abdominal ultrasound and upper endoscopy were done. Predicting outcomes and assessment risk of mortality by: ABC score, C-watch score and Rockall score.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Mortality occurred in 36% of cases, rebleeding in 8%, while 56% had a good prognosis.\u003c/p\u003e\n\u003cp\u003eChild score C were statistically significant in predicting mortality (P value: 0.01). Diagnostic performance of the studied scores in prediction of mortality showed that ABC score had the highest statistically significant diagnostic ability in predicting mortality, with an AUC of 72.6%, 95% CI: 0.6: 0.8, P value: \u0026lt;0.001. The cutoff point was 9.5 carrying a sensitivity of 44.4% and a specificity of 93.7%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eMortality was best predicted by a combination of elevated ABC score, other laboratory finding as (increased INR, CRP and ascitic fluid infection), the presence of combined portal-vein dilatation with thrombosis, hepatic focal lesion, presence of ascites on ultrasound and Child-Pugh class C. Among the evaluated scoring systems, the ABC score showed the best predictive performance for mortality.\u003c/p\u003e","manuscriptTitle":"Predictive and prognostic significance of the Age, blood tests and comorbidities (ABC) score, Cologne-watch (C-watch) score and Rockall score for risk of mortality following variceal bleeding among cirrhotic patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-12 07:35:25","doi":"10.21203/rs.3.rs-9023233/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":"26948ae2-ea3d-4cae-9b60-e0977451a9c0","owner":[],"postedDate":"April 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-12T07:35:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-12 07:35:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9023233","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9023233","identity":"rs-9023233","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}