Preoperative infection within a month is associated with inferior post-transplant outcomes in adult living donor liver transplants
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Abstract Background: Preoperative infection is a major determinant of outcome following liver transplant. The current study aims to assess the impact of the interval between preoperative infection and transplantation on post-operative outcomes following adult living donor liver transplantation (LDLT). Methods : Consecutive LDLT recipients (n=578), were divided into Group 1 (infection within 15 days), Group 2 (15 to 30 days), Group 3 (30 to 90 days), Group 4 (> 90 days), and Group 5 (without documented infection). The impact of timelines of pre-transplant infections on post-transplant outcomes were analyzed. Results: The group-1, 2, 3, 4 and 5 comprised 104(18%), 35(6%), 44(8%), 222(38%), and 173(30%) recipients respectively (n=578). Post-transplant sepsis and septic shock were seen in 278(48%) and 133(23%) patients respectively. Three-month mortality was 12.1% (70/578); 55.7% (39/70) of them had mortality attributed to sepsis. Patients with pre-LDLT infection within 30 days experienced higher three-month overall and sepsis-related mortality [25.17% vs 8%; OR:3.87(2.31-6.47); p=0.04] and [80% vs 31.42%; 8.73(2.92-26.04); p=<0.001] respectively, compared to recipients with infection beyond 30 days or no infection. With an upper limit of three-month mortality kept at 10%, ROC curve showed minimum pre-transplant ‘Infection-free interval’ of 27days (AUC=0.780). Multivariate analysis revealed pre-LDLT infection within 27 days [OR: 3.61(2.83-4.44)], pre-LDLT infection with MDR/XDR organisms [4.8 (1.6-14.9)], MELD >25 [2.51(1.09-5.79)], and biliary/vascular complications [1.82(1.10-2.74)] predicted three-month mortality. Conclusion: Infection within one month before LDLT is associated with high overall and sepsis-related three-month mortality. Preoperative infection within 27 days and MDR/XDR infections, MELD Na >25, and post-LDLT biliary/vascular complications predicted mortality.
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Preoperative infection within a month is associated with inferior post-transplant outcomes in adult living donor liver transplants | 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 Preoperative infection within a month is associated with inferior post-transplant outcomes in adult living donor liver transplants Bharat Nair, Nihar Mohapatra, Nilesh Sadashiv Patil, G Harsha Vardhan Reddy, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7280166/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: Preoperative infection is a major determinant of outcome following liver transplant. The current study aims to assess the impact of the interval between preoperative infection and transplantation on post-operative outcomes following adult living donor liver transplantation (LDLT). Methods : Consecutive LDLT recipients (n=578), were divided into Group 1 (infection within 15 days), Group 2 (15 to 30 days), Group 3 (30 to 90 days), Group 4 (> 90 days), and Group 5 (without documented infection). The impact of timelines of pre-transplant infections on post-transplant outcomes were analyzed. Results: The group-1, 2, 3, 4 and 5 comprised 104(18%), 35(6%), 44(8%), 222(38%), and 173(30%) recipients respectively (n=578). Post-transplant sepsis and septic shock were seen in 278(48%) and 133(23%) patients respectively. Three-month mortality was 12.1% (70/578); 55.7% (39/70) of them had mortality attributed to sepsis. Patients with pre-LDLT infection within 30 days experienced higher three-month overall and sepsis-related mortality [25.17% vs 8%; OR:3.87(2.31-6.47); p=0.04] and [80% vs 31.42%; 8.73(2.92-26.04); p=<0.001] respectively, compared to recipients with infection beyond 30 days or no infection. With an upper limit of three-month mortality kept at 10%, ROC curve showed minimum pre-transplant ‘Infection-free interval’ of 27days (AUC=0.780). Multivariate analysis revealed pre-LDLT infection within 27 days [OR: 3.61(2.83-4.44)], pre-LDLT infection with MDR/XDR organisms [4.8 (1.6-14.9)], MELD >25 [2.51(1.09-5.79)], and biliary/vascular complications [1.82(1.10-2.74)] predicted three-month mortality. Conclusion: Infection within one month before LDLT is associated with high overall and sepsis-related three-month mortality. Preoperative infection within 27 days and MDR/XDR infections, MELD Na >25, and post-LDLT biliary/vascular complications predicted mortality. Cirrhosis Liver transplantation Living donor Infection Sepsis Infection-free period Multidrug resistance Extensive drug resistance Three-month mortality Model for End Stage Liver Disease Sodium Figures Figure 1 Figure 2 INTRODUCTION The incidence perioperative sepsis in liver transplant (LT) recipients varies between 20 to 80 %. 1 A retrospective analysis has revealed that the incidence of sepsis after LT could be as high as 50%–80%, and sepsis-related deaths account for 50–90% of all post-LT mortality. 2 In the current era, LT is being offered to sicker patients. Living donor liver transplantation (LDLT) is generally performed as an elective or semi-emergency surgery in patients with chronic liver disease (CLD). LDLT gives an opportunity to time the operation depending on the recipient’s clinical condition. 3 The decision to expedite or delay LT in candidates with a recent infection is challenging and needs to be evidence-based. The aim of the current study is to assess the impact of the onset of infection (both bacterial and fungal) in the pre-LDLT period on the recipient’s post-LDLT outcomes and to ascertain an optimal pre-LDLT ‘Infection-free interval’ for better patient selection, risk stratification and timing of LDLT. METHODS Study design & patient selection: This is an analysis of prospectively collected data of consecutive adult patients who underwent LDLT at the Institute of Liver and Biliary Sciences, New Delhi, over a ten-year period from January, 2012 till January, 2022. For homogeneity, the LDLT for acute liver failure, deceased donor liver transplant (DDLT), simultaneous liver and kidney transplant, and pediatric LT were excluded from this study. The study was approved by the institutional ethics committee (IEC/2020/80/MA11) and registered under clinical trials.gov (NCT05109156). The informed consent was obtained for the prospective cohort (January, 2020 onwards), and was waived off for the retrospective cohort. Data was extracted from existing prospective databases using a predefined, standardized case-record form. Patients were divided into 5 groups based on the timing of pretransplant infection (last day of active infection -clinically or till last body fluid culture positive for either bacteria or fungus). Group 1 (infection within 15 days pre-LT), group 2 (infection between 16 to 30 days pre-LT), group 3 (infection between 31 days to 90 days pre-LT), group 4 (infection more than 90days pre-LT), group 5 (no preoperative infection). The pre-transplant assessment and peri operative care were as per standard protocol published previously. 4 Definitions The definition of sepsis used in our study was based on CDC criteria according to sepsis 3 guidelines. 5 Spontaneous bacterial peritonitis (SBP) was defined as a polymorphonucleated cell count of 250 cells/mm 3 or more in ascites, regardless of bacterial growth from culture, with or without the presence of peritoneal signs. 6 Bloodstream infections were classified as primary when the infection source from another site was unidentified and categorized as secondary in the presence of a determined infection source. Catheter-related infection was ascertained when the criteria of the Infectious Diseases Society of America guidelines were fulfilled . 7 Chest infection/pneumonia was defined as sputum/endotracheal secretion/ bronchoalveolar cultures positive or progressive opacity on chest X-ray with fever, leukocytosis, purulent sputum, newly developed or worsening cough, tachypnea, tachycardia, crepitations detected at auscultation, and/or derangement in arterial oxygen desaturation. Urinary tract infection (UTI) was defined as a urine culture positive with the presence of dysuria, frequency and/or urgency, and pyuria. Skin and soft-tissue infections , including cellulitis and necrotizing fasciitis, were defined as erythema or pus collection in the affected skin. Nasal infection was defined as a positive swab culture, including fungal and bacterial infections. Multi-drug resistant (MDR) bacteria were defined as resistance to at least one antibiotic in three or more antimicrobial categories and extensively drug resistant (XDR) in case of resistance to at least one antibiotic in all but two or fewer antimicrobial categories. 8 MDR fungus was defined as resistance to at least one antifungal agent in each category. The Clavien-Dindo classification of surgical complications (Grades I-V) was used for objective classification of post-transplant morbidity and mortality. 9 All vascular (hepatic artery, portal vein, or hepatic vein related) and biliary complications were clubbed together as biliary/vascular complications. ‘ Three-month mortality’ was defined as mortality occurring within 90 days after the LDLT. Immunosuppression and follow-up : Our post-transplant immunosuppression protocol has been previously published. 10 Statistical Analysis: Categorical variables were presented in number and percentage, and continuous variables were presented as mean ± SD or median, as suitable. Normality of data was tested by the Kolmogorov-Smirnov test. If the normality was rejected, then a non-parametric test was used. Quantitative variables were compared using an Independent t-test/Mann-Whitney test (when the data sets were not normally distributed) between the two groups. Qualitative variables were correlated using the Chi-Square test/Fisher’s exact test. Intergroup survival analysis using Kaplan-Meier analysis. A p-value of ≤0.05 was considered statistically significant. The data was entered in an MS EXCEL spreadsheet, and analysis was done using Statistical Package for Social Sciences (SPSS) version 23.0 (Armonk IBM). RESULTS During the study period, 816 liver transplants were performed at our institute. After excluding 112 pediatric liver transplants, 69 deceased donor liver transplants, and 57 adult transplants for acute liver failure, 578 adult LDLT recipients were enrolled for the study. The mean age, gender distribution, and body mass index (BMI) were comparable between the groups. ( Table 1 ) Median Model for End Stage Liver Disease Sodium (MELD Na) score was 25 (IQ range 23–27). The median MELD Na score was highest in patients in groups 1 and 2 (26 and 27, respectively). Nearly 90% of the patients (n = 519) were transplanted for CLD, while in approximately 10% (n = 59), the presentation was of acute-on-chronic liver failure (ACLF). The most common etiology for cirrhosis was alcoholic liver disease (ALD), 41.86% (n = 242), followed by cryptogenic, 15.57%(n = 90). The right lobe was more frequent type of graft used than the left lobe: 80% (n = 462) vs 20% (n = 116). The number of pre-transplant hospitalizations (1.84 ± 1.1, p value = 0.00), number of hospitalizations with infections (1.02 ± 0.36, p value = 0.04), and the duration of pre-transplant hospitalizations in days (10.69 ± 8.3, p value 90 days post-LT). (Table 1 ). Seventy percent (n = 408) of all patients experienced at least one episode of pre-LDLT infection. ( Table 1 ) Table 1 Pre-operative characteristics of the groups. Parameter Cohort (n = 578) Group1 n = 104(18%) (Infection within 15d) Group2 n = 35(6%) (Infection 16-30d) Group3 N = 44(8%) (Infection 31-90d) Group 4 n = 222(38%) (Infection > 90d) Group5 N = 173(30%) (No sepsis) P Value Age (Mean ± SD) 46.69 ± 9.93 46.07 ± 10.7 43.11 ± 8.07 44 ± 11.29 47.80 ± 9.52 47.04 ± 9.62 0.28 Male (n) (%) 504(87.1%) 93 (89.4%) 34(97.1%) 41(93.1%) 184(82.4%) 152(87.8%) 0.068 Female%(N) 274(10.3%) 11(10.6%) 1(2.9%) 3(6.9%) 38(17.6%) 221(12.2%) BMI 25.27 24.44 26.5 26.3 25.11 25.46 0.10 Comorbidity%(N) 146(25.3%) 46(44.23%) 14(40%) 19(43.18%) 91(40.99%) 73(42.19%) 0.14 Median MELD Na (Range) 25 (9–40) 26(12–40) 27(9–37) 25(13–38) 23(10–39) 24(9–40) 0.1 ALD 242(41.86%) 42(40.38%) 15(42.85%) 27(61.36%) 85(38.28%) 71(41.04%) 0.089 Cryptogenic CLD (n) 90(15.57%) 17(16.34%) 4(11.42%) 3(6.81%) 42(18.91%) 24)13.87%) NASH CLD (n) 79(13.66%) 15(14.42%) 5(14.28%) 8(18.18%) 32(14.41%) 19(10.98%) HBV CLD (n) 57(9.86%) 11(10.57%) 2(5.71%) 1(2.27%) 17(7.65%) 26(14.45%) HCV CLD (n) 42(7.26%) 5(4.8%) 1(2.85%) 2(4.54%) 23(10.36%) 11(5.78%) Others(n) 68(11.76%) 14(12.5%) 8(22.85%) 2(4.54%) 22(9.9%) 22(12.71%) CLD (%) 519(89.7%) 93(89.4%) 32(91.4%) 42(95.45%) 200(90.09%) 148(85.54%) 0.42 ACLF (%) 59(10.3%) 11(10.6%) 3(8.6%) 2(4.55%) 22(9.91%) 23(14.46%) Number of pre-LT hospitalizations 2.5 ± 1.4 2.94 ± 1.96 2.66 ± 1.00 1.84 ± 1.1 2.53 ± 1.58 < 0.001 Number of pre-LT hospitalizations with infections 1.2 ± 0.4 1.25 ± 0.44 1.13 ± 0.50 1.02 ± 0.36 0 - Duration of pre-LT hospitalizations (Days) 15.8 ± 10.06 20.17 ± 16.0 15.22 ± 7.12 10.69 ± 8.3 15.74 ± 12.2 < 0.001 Donor age (yrs) (Mean ± SD) 32.2 ± 7.2 34 ± 9.14 29.09 ± 6.95 34.02 ± 6.12 31.91 ± 6.63 30.72 ± 6.57 0.64 Donor (Male) 232(40.1%) 42(40.4%) 16(45.7%) 17(38.6%) 89(40.1%) 68(39.3%) 0.88 Donor (Female) 346(59.9%) 62(59.6%) 19(54.3%) 27(61.4%) 133(59.8%) 105(60.7%) 0.82 Donor LAI (Mean ± SD) 10.12 ± 2.83 10.60 ± 2.81 9.62 ± 2.75 11.07 ± 2.94 9.99 ± 2.85 9.85 ± 2.75 0.92 GRWR(Mean ± SD) 0.89 ± 0.20 0.78 ± 0.20 0.87 ± 0.21 0.91 ± 0.21 0.85 ± 0.20 0.92 ± 0.19 0.76 Blood loss (ml) (Mean ± SD) 2484 ± 584 2782 ± 620 2520 ± 564 2456 ± 555 2148 ± 542 2348 ± 564 0.82 Right lobe%(n) 462(80%) 88(84.61%) 32(91.42%) 39(86.66%) 168(75.76%) 135(78.03%) 0.068 Left lobe%(n) 116(20%) 16(15.38%) 3(8.58%) 6(13.63%) 54(24.32%) 37(21.38%) 0.102 Abbreviations; ACLF: Acute on chronic liver failure; ALD: Alcoholic liver disease; BMI: Body mass index; CLD: Chronic liver disease; GRWR: Graft to Recipient Weight Ratio; HBV: Hepatitis -B virus; HCV: Hepatitis C virus; LT: Liver transplantation; LAI: Liver attenuation index; MELD Na: Model for end-stage liver disease -Sodium. Group-wise incidence of various sources of infection is provided in Table S1 . The common organisms responsible for sepsis during the preoperative period and postoperative period as well were Klebsiella followed by E. Coli. (Table S2 ) MDR and XDR organisms accounted for nearly 50% of all the infections in the pre-LT period and the rest were sensitive organisms. On the other hand, close to 58% of infections in the post-LT period were attributed to MDR and XDR organisms (Table S 3 and S 4). During the pre-LT period, 61 (17.42%) patients had either proven or clinically suspected fungal infection. Similarly, 42 (13.81%) of the patients experienced fungal infection in the post-transplant period. (Table S 3 and S 4) Among all the post-LDLT outcomes ( Table 2 ) , need of withdrawal of immunosuppression therapy (P = 0.001), duration of mechanical ventilation (P < 0.001), three- month mortality (P < 0.001), and three-month mortality related to sepsis (p = 0.034) showed significantly different trends among the groups. Table 2 Post-operative outcomes of the groups. Parameter Total(n = 578) Group1 n = 104 ( Infection 90d) Group5 N = 173 (No sepsis) P value Sepsis 278(48.1% ) 49(47.1%) 24(68.6%) 22(50.0%) 107(48.2%) 76(43.9%) 0.126 Septic shock 133(23.1%) 30(28.8%) 11(32.4%) 11(25.0%) 45(20.3%) 36(21.1%) 0.28 Antimicrobial treatment escalation 269(47.1%) 54(51.5%) 25(68.6%) 19(44.2%) 102(46.2%) 72(42.0%) 0.55 Withdrawal of Immunosuppression therapy 241(42.1% ) 51(49.5%) 25(71.4%) 21(48.8%) 75(33.9%) 70(40.6%) 0.001 Duration of withdrawal of immunosuppression(days) 13.40 14.28 15.28 13.87 10.56 13.05 0.51 Mean duration of mechanical ventilation (hours) 43.44 ± 21.12 31.464 91.896 40.752 28.80 54.744 < 0.001 Mean duration for tapering off inotropes (Days) 2.04 ± 2.95 1.889 2.929 2.619 1.836 2.102 0.18 Mean Hospital stay (Days) 29.66 ± 21.4 30.240 30.343 31.159 28.266 30.593 0.81 Mean ICU stay (Days) 12.85 ± 11.4 12.894 13.943 14.636 12.194 12.977 0.7 Reintubation rate 63(10.9%) 15(14.4%) 3(8.6%) 6(14.0%) 20(9.0%) 19(11.0%) 0.61 Return to ICU 67(11.6%) 14(13.5%) 4(11.4%) 5(11.4%) 24(10.9%) 20(11.6%) 0.97 Re-laparotomy 51(8.8%) 13(12.5%) 6(17.1%) 5(11.4%) 17(7.7%) 10(5.8%) 0.116 Postoperative hemodialysis 27(4.7%) 9(8.7%) 2(5.7%) 1(2.3%) 9(4.1%) 6(3.5%) 0.28 Rejection requiring steroid pulse 32(5.5%) 6(5.8%) 1(3.9%) 3(6.5%) 15(6.7%) 8(4.6%) 0.10 Clavien-Dindo (> Grade3) complications 206(35.6%) 40(38.5%) 15(42.9%) 13(29.5%) 88(39.6%) 50(28.9%) 0.14 HAT%(n) 23(4%) 5(4.8%) 2(5.7%) 2(4.5%) 8(3.6%) 6(3.5%) 0.95 PVT%(n) 4(0.7%) 1(1%) 1(2.9%) 1(2.3%) 1(0.5%) 0(0%) 0.24 Biliary complications%(n) 30(5.2%) 6(5.8%) 2(5.7%) 3(6.8%) 12(5.4%) 7(4.0%) 0.93 Three months-mortality 70(12.1%) 30(28.8%) 5(14.2%) 5(11.3%) 16(7.2%) 14(8.0%) < 0.001 Three months mortality related to sepsis 39(55.7%) 24(82%) 4(80%) 2(40%) 5(31.2%) 4(28.5%) 0.034 Abbreviations : HAT: Hepatic artery thrombosis; ICU: Intensive Care Unit; LT: Liver Transplant; PVT: Portal Vein Thrombosis. Hepatic artery thrombosis (HAT) was detected in 23 patients (4%), portal vein thrombosis (PVT) was seen in 4 (0.7%), whereas biliary complications (both bile leak and biliary stricture) were noticed in 30 (5.2%) patients. There were no differences in the occurrence of biliary and vascular complications between the groups. There were no significant differences between the groups in terms of the occurrence of post-LDLT sepsis (p = 0.126). Although group 1 and 2 had more frequent septic shock compared to group 3, group 4, and 5 (p = 0.04; Table 3 ), the differences across the groups were not statistically significant (p = 0.28; Table 2 ). The three-month mortality for the whole cohort was 12.15% (n = 70). This was highest for group 1, followed by groups 2 & 3, and lowest for groups 4 & 5 (P < 0.001). The proportion of deaths related to only sepsis was significantly higher in group 1 (82%) and group 2 (80%), compared to group 3 (40%), group 4 (31.2%), and lowest for group 5 (28.5%) (p = 0.034). On comparing the outcome related to sepsis in less than 30 days versus sepsis beyond 30 days and the without-sepsis group, there was a significant difference in the incidence of septic shock, three-month mortality, and three-month mortality specifically related to sepsis between groups 1 and 2 combined (sepsis within 30 days before transplantation) versus other three groups clubbed together (P value 0.04, < 0.001, and < 0.001, respectively). ( Table 3 ) Table 3 Outcome related to infection in less than 30 days vs infection beyond 30 days and without sepsis. Parameter Total(n = 578) Infection 30 days and no infection (n = 439) Odds Ratio (95% CI) P Value Sepsis 278 (48.1%) 73(52.51%) 205(46.91%) 1.25(0.85–1.83) 0.12 Septic shock 133(23.1%) 41 (29.45%) 92(21.05%) 1.57(1.02–2.41) 0.04 Three months-mortality 70(12.1%) 35(25.17%) 35 (8%) 3.87(2.31–6.47) < 0.001 Three months-mortality related to sepsis 39(55.7%) 28 (80%) 11(31.42%) 8.73(2.92–26.04) < 0.001 In order to identify the pre-transplant ‘infection-free interval’ as a predictor of post-transplant three-month mortality, an ROC curve analysis was performed ( Fig. 1 ). ‘Infection-free interval’ implies the number of days between resolution of the last episode of infection till the day of transplant. The ROC curve revealed an AUC of 0.780. With an acceptable upper limit of three-month mortality kept at 10%, and the survival cut-off analysis showed the cut-off for minimum pre-transplant “infection-free interval” required was 27 days. Univariate analysis of the factors influencing the post-LDLT three-month mortality is showed in Table 4 . On multivariate analysis, pre-LT infection within 27 days, pre-LDLT infection with MDR/XDR organisms, high MELD Na ≥ 25, and post-LDLT biliary/vascular complications significantly predicted post-LDLT three-month mortality. ( Table 4 ) The Kaplan-Meier curve for three-month post-transplant survival is shown in Fig. 2 . Table 4 Univariable and Multivariable analysis of factors predicting post-transplant three-month mortality. Variables Univariate Analysis Multivariate analysis Odds Ratio (95% CI) p value Odds Ratio (95% Cl) p value Recipient age > 60 vs < 60 2.2(0.92–5.25) 0.067 Recipient Male Sex 0.67(0.30–1.50) 0.332 Recipient BMI 1.039(0.974–1.108) 0.247 Recipient DM 0.580(0.20–1.66) 0.306 ACLF vs CLD 2.61(1.26–5.44) 0.008 MELD Na ≥ 25 3.23(1.72–6.09) 0.00 2.51(1.09–5.79) 0.030 Donor Age 0.958(0.91-1.00) 0.057 Donor LAI 0.98(0.885–1.095) 0.773 Pre-LT hospitalization within 3 months 1.01(0.55–1.86) 0.96 Pre- LDLT infection within 27 days 4.8(2.22–10.61) < 0.001 3.61(2.83–4.44) 0.001 Graft Type (Left vs Right) 0.98(0.55–1.89) 0.10 GRWR 1.14(0.6—2.12) 0.66 Intra-operative Blood Loss (ml) 1.12(1.00-1.38) 0.709 Post-operative Biliary and vascular complications 2.4(1.8–3.2) 0.03 1.82(1.10–2.74) 0.05 Post-operative septic shock 1.88(0.99–3.57) 0.050 Rejection 0.56(0.17–1.88) 0.35 Pre-LDLT infection with MDR/XDR organisms 7.2 (3.4–15.2) 0.001 4.8 (1.6–14.9) 0.007 Abbreviations; BMI: Body Mass Index; DM: Diabetes Mellitus; GRWR: Graft to recipient weight ratio; LAI: Liver attenuation index; LDLT: Live Donor Liver Transplant; MDR: Multi drug resistant; MELD Na: Model for end-stage liver disease -Sodium; XDR: Extensively drug resistant. > DISCUSSION The present study is a first-of-its-kind endeavour in a large cohort of adult LDLT recipients being assessed for the impact of different timelines of pre-LDLT infections on post-LDLT sepsis and other outcomes. The study was specifically designed to assess the optimal pre-LDLT ‘infection-free interval’ required to minimize the post-LDLT infection, mortality, and morbidity. The study results revealed the incidence of septic shock, three-month mortality, and sepsis-related mortality were higher for recipients experiencing infection within a month prior to LDLT. ( Table 3 ) Multivariate analysis also showed pre-LDLT infection within 27 days, infection with MDR/XDR organisms, MELD Na score > 25 and post-LDLT biliary/vascular complications were the significant factors predicting three-month mortality with the first two factors revealing higher risk. Another novel finding on ROC curve analysis for an estimated post-transplant mortality of less than 10% at three months was a waiting period “cut off” of 27 days before LDLT following resolution of an episode of infection. It is a universally acknowledged fact that cirrhosis patients awaiting LT are at increased risk of infections and their sequalae. 1112 Factors contributing to this increased risk are immune dysfunction, alcohol abuse, malnutrition, genetic polymorphism, increased requirement of invasive procedures, high MELD score, and multiple hospitalizations. 3 Overall, the incidence of pre-transplant sepsis in the current study was 70%, which was higher than reported in the literature. 6 , 13 – 15 In addition, over half of these patients experienced MDR/XDR infections. (Table S3) This may be explained by a sicker patient cohort with a high median MELD Na of 25, multiple hospital admissions with sepsis and decompensations before LT, poor general condition with sarcopenia, and an overall delayed-decision making to LT because of the logistics of LDLT, making them more susceptible to infections. Average duration of pretransplant hospitalization of more than two weeks for optimization is also an additional surrogate marker of these high-acuity recipients. In an analysis of pre- and post-transplant sepsis profiles, Jalan et al. 11 reported SBP and UTI followed by bacteremia and pneumonia to be the most frequent sources of sepsis in cirrhosis patients awaiting LT, while in the study by Saleh et al. 13 , pneumonia (40%) followed by nasal colonization (30%) and UTI (20%) were the most frequent sources of sepsis. In the current study, the common sources of infection overall in the pre-transplant period were respiratory and urinary tract, followed by SBP. Liver transplant in a candidate with active sepsis can be deleterious for the recipient and has been associated with high incidences of graft loss and mortality. 16 Since LDLT for CLD is usually an elective procedure, a waiting period for ebbing of sepsis and related complications is justified. To achieve a clinical equipoise and optimal patient outcome, a period of infection-free period would be desirable. Previously published studies have shown that although pre-LT infections were associated with high post LT morbidity and hospital stay, but there was no difference in post-LT mortality. 6 , 14 , 17 , 18 A recent study by Simone Incicco et al. from Italy also found that, even though patients with pre-LT infection within three months experienced a higher incidence of post-LT infections and septic shock, the time from resolution of infection to LT did not affect the incidence of post-LT complication or one- and 5-year patient survival rates. 19 However, these studies did not look at the impact of the different timelines of infection in the pre-LT period on post-transplant outcome and, specifically, did not evaluate the desired infection-free interval before proceeding for LT. The current study specifically addresses these issues. Although the incidence of sepsis was not significantly different across the five categories of pre-LDLT infection, the incidence of septic shock was different between groups 1 & 2 versus the rest of the cohort. The post-LT three-month mortality was also significantly higher in groups 1 and 2 recipients in comparison to the rest of the groups (25% vs. 8%). ( Table 3 ) More than half of the mortality for the whole cohort was attributed to sepsis (both bacterial and fungal), and the proportion of three-month mortality related to sepsis was significantly higher in groups 1 and 2 compared to other groups (80% vs. 31%). ( Tables 2 and 3 ) This indicates the patients having pre-LDLT infection within one month, though not an independent predictor of post-LDLT sepsis; when sepsis occurred in these subsets of recipients, it progressed to septic shock more often and contributed to early post-LT mortality due to sepsis. These results compared to previous studies give us a new perspective regarding the timeline of pre-LT sepsis and its impact on sepsis-related early post-LT mortality and provide with crucial decision-making with regard to the timing of LDLT in the presence of infection within one month prior to LDLT. Hence, risk stratification of pre-LDLT infection as per the shorter timelines better predicts post-LDLT outcome. The ROC curve analysis revealed the optimal infection-free period required to predict better post-LT mortality is approximately four weeks with a good AUC (0.780). Multivariate analysis also showed pre-LT sepsis within 27 days predicts post-LDLT three-month mortality. This window period can help to plan LT, particularly in the context of LDLT for CLD patients, as the timing of transplant can be scheduled beforehand. The mandatory ‘Infection-free interval’ however, may not be applicable in sicker recipients such as ACLF and alcoholic hepatitis, as organ dysfunction and systemic inflammatory response playing a major role in addition to sepsis and high mortality without liver transplant. Nearly half of the recipients experienced post-LT sepsis as defined by sepsis 2 and 3 criteria. 5 This incidence is comparatively higher than the contemporary literature 20 and could be due to a sicker cohort of patients with a high incidence of pre-transplant infections and a high proportion of MDR/XDR infections (51%) compared to the reported literature. In our study, bacteremia was the most common source of sepsis across all groups during the post-LDLT period, while in the study by Hara and colleagues, 18 pneumonia followed by bacteremia were the most common sources of post-LT sepsis. On the other hand, intrabdominal sepsis was the most common source of post-LT sepsis, according to the study by Simone Incicco et al’. 19 These differences, akin to pre-LT infections, could be attributable to the pattern of hospital-acquired infection, antibiotic usage, patients’ etiological profile, and surgical reconstructions such as biliary anastomosis. In addition, the majority of the organisms responsible for post-LT sepsis in our study had MDR (44.73%) or XDR (13.15%) infections. (Table S4) In recently reported literature, the incidence of infection by MDR organisms varies from 20–68% following DDLT. 19 , 20 The data on the incidence of MDR infection in LDLT recipients has not been reported in the literature, and to our knowledge, the current study is the first to reports post-LDLT sepsis with a very high incidence of MDR infections. With more than two weeks of average in-hospital stay, and almost over half of the recipients harboring MDR infections prior to LDLT, higher incidence of post-LDLT sepsis with MDR infections suggest hospital-acquired infections by these organisms. In addition, approximately 14 % of the paients had fungal sepsis, and 35 % of them bing multidrug resistant. (Table S4) In contrast to the previous study, 19 our study result shows preoperative infection with MDR or XDR organisms is a strong determinant of poor outcome and predicts three-month mortality. In view of the ever-increasing incidence of infections by MDR organisms in cirrhotic patients, 21 this study finding carries considerable significance and hence could guide the timing of liver transplants in elective LDLT. LDLT recipients are at increased risk of biliary/vascular complications because the operation being technically more complicated. 22 23 Biliary/vascular complications are known to increase the risk of septic complications. In the current cohort, the overall biliary-vascular complications were about 9%, which compares favourably with the published literature. 24 Overall biliary complications of 5% and vascular complications of 4% at three months could be attributed to the refinement in technique described previously. 25 , 26 This is the largest study analyzing the impact of pre-LDLT infection on post-LDLT outcomes, with high median MELD Na scores and high incidence of pre- and post-LDLT infections. This is also a first endeavour to stratify outcomes based on the pre-LDLT timeline of infection and to ascertain an ideal cutoff of pre-transplant ‘infection-free period’ in the LDLT cohort. The main limitations are that, as the study outcomes were analyzed over a long period and there have been changes in patient management strategies and protocols, including selection, medical management, critical care, and surgical technique, this could have influenced outcomes. CONCLUSION Sepsis within one month before LDLT is associated with higher overall and sepsis-related three-month mortality. Pre-LDLT infection within a month and infection by MDR or XDR organisms, MELD Na > 25, and post-LT biliary/vascular complications significantly impact post-LT mortality. Pretransplant ‘infection-free interval’ is a good predictor for post-LT mortality, with four weeks as ideal cutoff before LT to reduce early post-LT sepsis-related mortality. Abbreviations LT Liver transplant LDLT Living donor liver transplantation CLD Chronic liver disease DDLT Deceased donor liver transplant SBP Spontaneous bacterial peritonitis UTI Urinary Tract Infection MDR Multidrug resistance XDR Extensively drug resistant ROC Receiver Operating Characteristic SPSS Statistical Package for Social Sciences MELD Na Model for End Stage Liver Disease Sodium ACLF Acute on chronic liver failure ALD Alcoholic Liver Disease HAT Hepatic artery thrombosis PVT Portal Vein Thrombosis BMI Body mass index GRWR Graft to Recipient Weight Ratio HBV Hepatitis -B virus HCV Hepatitis C virus LAI Liver attenuation index ICU Intensive Care Unit DM Diabetes Mellitus BAL Bronchoalveolar lavage SBE Spontaneous bacterial effusion ET Endotracheal tube Declarations Author’s contribution: Study concept/Design: VP. Data collection: BN, NM, GHR, NSP, GS, VK. Analysis and interpretation of data: BN, NM, GHR, VP. Manuscript drafting: BN, NM, VP. Critical revision of the manuscript for important intellectual content: VP, NM, SKS. Conflict of Interest : The authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript. Funding : The authors received no financial support to produce this manuscript. Patient Consent: Consent was obtained from the prospective arm and was waived off for the retrospective arm. Ethics approval: The study was approved by institutional scientific review board and ethics committee (IEC/2020/80/MA11) Trial registration: Present RCT was registered at ClinicalTrials.gov (NCT05109156) Acknowledgement: The authors wish to thank Dr. Guresh Kumar and Dr Ankit Bharadwaj for their contribution in the statistical analysis of the study References Fagiuoli S, Colli A, Bruno R et al. Management of infections pre- and post-liver transplantation: Report of an AISF consensus conference. J Hepatol . 2014;60(5):1075–1089. 10.1016/J.JHEP.2013.12.021/ASSET/9DE1917F-5F02-4E48-8445-665C345C5858/MAIN.ASSETS/FX8.JPG Donnelly JP, Locke JE, MacLennan PA, et al. Inpatient Mortality Among Solid Organ Transplant Recipients Hospitalized for Sepsis and Severe Sepsis. Clin Infect Dis. 2016;63(2):186–94. 10.1093/CID/CIW295 . Saab S, Wang V, Ibrahim AB, et al. MELD score predicts 1-year patient survival post-orthotopic liver transplantation. Liver Transpl. 2003;9(5):473–6. 10.1053/JLTS.2003.50090 . Pamecha V, Tharun G, Patil NS, et al. Graft Inflow Modulation by Splenic Artery Ligation for Portal Hyperperfusion Does Not Decrease Rates of Early Allograft Dysfunction in Adult Live Donor Liver Transplantation A Randomized Control Trial. Ann Surg. 2025;281(4):561–72. 10.1097/SLA.0000000000006369 . Singer M, Deutschman CS, Seymour C, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801–10. 10.1001/JAMA.2016.0287 . HY S, TV C. N S. Impact of pretransplant infections on clinical outcomes of liver transplant recipients. Liver Transpl. 16:222–8. Mermel LA, Allon M, Bouza E, et al. Clinical practice guidelines for the diagnosis and management of intravascular catheter-related infection: 2009 Update by the Infectious Diseases Society of America. Clin Infect Dis. 2009;49(1):1–45. 10.1086/599376 . Magiorakos AP, Srinivasan A, Carey RB, et al. Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance. Clin Microbiol Infect. 2012;18(3):268–81. 10.1111/J.1469-0691.2011.03570.X . Dindo D, Demartines N, Clavien PA. Classification of Surgical Complications: A New Proposal With Evaluation in a Cohort of 6336 Patients and Results of a Survey. Ann Surg. 2004;240(2):205. 10.1097/01.SLA.0000133083.54934.AE . Pamecha V, Mahansaria SS, Kumar S, et al. Association of thrombocytopenia with outcome following adult living donor liver transplantation. Transpl Int. 2016;29(10):1126–35. 10.1111/TRI.12819 . R J, J F, R W, B S, R M, P A. Bacterial infections in cirrhosis: a position statement based on the EASL Special Conference 2013. J Hepatol . 60:1310 – 1224. Chen W, Wu S, Gong L, et al. Exploring the risk factors of early sepsis after liver transplantation: development of a novel predictive model. Front Med (Lausanne). 2023;10. 10.3389/FMED.2023.1274961 . Saleh AM, Hassan EA, Gomaa AA, et al. Impact of pre-transplant infection management on the outcome of living-donor liver transplantation in Egypt. Infect Drug Resist. 2019;12:2277. 10.2147/IDR.S208954 . Bertuzzo VR, Giannella M, Cucchetti A, et al. Impact of preoperative infection on outcome after liver transplantation. Br J Surg. 2017;104(2):e172–81. 10.1002/BJS.10449 . Ferrarese A, Senzolo M, Sasset L, Bassi D, Cillo U, Burra P. Multidrug-resistant bacterial infections in the liver transplant setting. Updates Surg. 2024;76(7):2521–9. 10.1007/S13304-024-01903-6/METRICS . Petrowsky H, Rana A, Kaldas FM, et al. Liver transplantation in highest acuity recipients: Identifying factors to avoid futility. Ann Surg. 2014;259(6):1186–94. 10.1097/SLA.0000000000000265 . Heldman MR, Ngo S, Dorschner PB, Helfrich M, Ison MG. Pre- and post-transplant bacterial infections in liver transplant recipients. Transpl Infect Dis. 2019;21(5). 10.1111/TID.13152 . Hara T, Soyama A, Takatsuki M, et al. The impact of treated bacterial infections within one month before living donor liver transplantation in adults. Ann Transpl. 2014;19(1):674–9. 10.12659/AOT.892095 . Incicco S, Tonon M, Zeni N, et al. Impact of bacterial infections prior to liver transplantation on post-transplant outcomes in patients with cirrhosis. JHEP Rep. 2023;5(9):100808. 10.1016/J.JHEPR.2023.100808 . Martin-Mateos R, Martínez-Arenas L, Carvalho-Gomes Á, et al. Multidrug-resistant bacterial infections after liver transplantation: Prevalence, impact, and risk factors. J Hepatol. 2024;80(6):904–12. 10.1016/j.jhep.2024.02.023 . Fernández J, Prado V, Trebicka J, et al. Multidrug-resistant bacterial infections in patients with decompensated cirrhosis and with acute-on-chronic liver failure in Europe. J Hepatol. 2019;70(3):398–411. 10.1016/J.JHEP.2018.10.027 . Barbetta A, Aljehani M, Kim M, et al. Meta-analysis and meta-regression of outcomes for adult living donor liver transplantation versus deceased donor liver transplantation. Am J Transplant. 2021;21(7):2399–412. 10.1111/AJT.16440 . Reichman TW, Katchman H, Tanaka T, et al. Living donor versus deceased donor liver transplantation: A surgeon-matched comparison of recipient morbidity and outcomes. Transpl Int. 2013;26(8):780–7. 10. 1111/TRI.12127;PAGEGROUP:STRING:PUBLICATION. Humar A, Ganesh S, Jorgensen D, et al. Adult Living Donor Versus Deceased Donor Liver Transplant (LDLT Versus DDLT) at a Single Center: Time to Change Our Paradigm for Liver Transplant. Ann Surg. 2019;270(3):444–51. 10.1097/SLA.0000000000003463 . Pamecha V, Sasturkar SV, Sinha PK, Mohapatra N, Patil N. Biliary Reconstruction in Adult Living Donor Liver Transplantation: The All-Knots-Outside Technique. Liver Transpl. 2021;27(4):525–35. 10.1002/LT.25862 . Pamecha V, Sinha PK, Mukund A, et al. Hepatic artery–related complications after live donor liver transplantation. Langenbecks Arch Surg. 2024;408(1). 10.1007/S00423-023-02759-X . Supplementary Files SupplementaryMaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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19:54:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7280166/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7280166/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89838662,"identity":"cbb54fc6-bce9-4377-a887-564a124162b4","added_by":"auto","created_at":"2025-08-25 15:05:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":16091,"visible":true,"origin":"","legend":"\u003cp\u003eROC-Curve-pre transplant “infection-free period” (in days) as a predictor of post-transplant mortality.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7280166/v1/6e490a0ef47cb100aed1d0fe.png"},{"id":89838666,"identity":"91904bdc-d060-4664-9ab5-a2b7ded9f61a","added_by":"auto","created_at":"2025-08-25 15:05:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":155627,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan Meier Curve for three-month survival.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7280166/v1/dacd49d1f6a73da4c9a8ba6d.png"},{"id":96362953,"identity":"e4ccaadd-51b8-49cc-a110-759780b06590","added_by":"auto","created_at":"2025-11-20 10:03:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1514877,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7280166/v1/6e8c731c-477b-483b-b20b-4d89f2807a7a.pdf"},{"id":89840177,"identity":"490c3053-5348-4b22-a95f-838dc5f88022","added_by":"auto","created_at":"2025-08-25 15:13:38","extension":"docx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":27734,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-7280166/v1/b21cb126381343c5ae354189.docx"}],"financialInterests":"","formattedTitle":"Preoperative infection within a month is associated with inferior post-transplant outcomes in adult living donor liver transplants","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe incidence perioperative sepsis in liver transplant (LT) recipients varies between 20 to 80 %. \u003csup\u003e1\u003c/sup\u003e A retrospective analysis has revealed that the incidence of sepsis after LT could be as high as 50%\u0026ndash;80%, and sepsis-related deaths account for 50\u0026ndash;90% of all post-LT mortality.\u003csup\u003e2\u003c/sup\u003e In the current era, LT is being offered to sicker patients. Living donor liver transplantation (LDLT) is generally performed as an elective or semi-emergency surgery in patients with chronic liver disease (CLD). LDLT gives an opportunity to time the operation depending on the recipient\u0026rsquo;s clinical condition.\u003csup\u003e3\u003c/sup\u003e The decision to expedite or delay LT in candidates with a recent infection is challenging and needs to be evidence-based. The aim of the current study is to assess the impact of the onset of infection (both bacterial and fungal) in the pre-LDLT period on the recipient\u0026rsquo;s post-LDLT outcomes and to ascertain an optimal pre-LDLT \u0026lsquo;Infection-free interval\u0026rsquo; for better patient selection, risk stratification and timing of LDLT.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eStudy design \u0026amp; patient selection:\u003c/em\u003e\u003c/strong\u003eThis is an analysis of prospectively collected data of consecutive adult patients who underwent LDLT at the Institute of Liver and Biliary Sciences, New Delhi, over a ten-year period from January, 2012 till January, 2022. For homogeneity, the LDLT for acute liver failure, deceased donor liver transplant (DDLT), simultaneous liver and kidney transplant, and pediatric LT were excluded from this study. The study was approved by the institutional ethics committee (IEC/2020/80/MA11) and registered under clinical trials.gov (NCT05109156). The informed consent was obtained for the prospective cohort (January, 2020 onwards), and was waived off for the retrospective cohort. Data was extracted from existing prospective databases using a predefined, standardized case-record form. Patients were divided into 5 groups based on the timing of pretransplant infection (last day of active infection -clinically or till last body fluid culture positive for either bacteria or fungus). \u0026nbsp;Group 1 (infection within 15 days pre-LT), group 2 (infection between 16 to 30 days pre-LT), group 3 (infection between 31 days to 90 days pre-LT), group 4 (infection more than 90days pre-LT), group 5 (no preoperative infection). The pre-transplant assessment and peri operative care were as per standard protocol published previously. \u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eDefinitions\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe definition of sepsis used in our study was based on CDC criteria according to sepsis 3 guidelines. \u003csup\u003e5\u003c/sup\u003e \u003cstrong\u003eSpontaneous bacterial peritonitis (SBP)\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;was\u0026nbsp;\u003c/strong\u003edefined as a polymorphonucleated cell count of 250 cells/mm\u003csup\u003e3\u003c/sup\u003e or more in ascites, regardless of bacterial growth from culture, with or without the presence of peritoneal signs. \u003csup\u003e6\u003c/sup\u003e \u003cstrong\u003eBloodstream infections were\u0026nbsp;\u003c/strong\u003eclassified as \u003cstrong\u003eprimary\u0026nbsp;\u003c/strong\u003ewhen the infection source from another site was unidentified and categorized as \u003cstrong\u003esecondary\u003c/strong\u003e in the presence of a determined infection source. \u003cstrong\u003eCatheter-related infection\u003c/strong\u003e was ascertained when the criteria of the Infectious Diseases Society of America guidelines were fulfilled\u003csup\u003e. 7\u003c/sup\u003e \u003cstrong\u003eChest infection/pneumonia was defined as\u0026nbsp;\u003c/strong\u003esputum/endotracheal secretion/ bronchoalveolar cultures positive or progressive opacity on chest X-ray with fever, leukocytosis, purulent sputum, newly developed or worsening cough, tachypnea, tachycardia, crepitations detected at auscultation, and/or derangement in arterial oxygen desaturation. \u003cstrong\u003eUrinary tract infection (UTI) was\u0026nbsp;\u003c/strong\u003edefined as a urine culture positive with the presence of dysuria, frequency and/or urgency, and pyuria. \u003cstrong\u003eSkin and soft-tissue infections\u003c/strong\u003e, including cellulitis and necrotizing fasciitis, were defined as erythema or pus collection in the affected skin. \u003cstrong\u003eNasal infection\u0026nbsp;\u003c/strong\u003ewas defined as a positive swab culture, including fungal and bacterial infections.\u003cstrong\u003eMulti-drug resistant (MDR)\u003c/strong\u003e bacteria were defined as resistance to at least one antibiotic in three or more antimicrobial categories and \u003cstrong\u003eextensively drug resistant (XDR)\u003c/strong\u003e in case of resistance to at least one antibiotic in all but two or fewer antimicrobial categories. \u003csup\u003e8\u003c/sup\u003e MDR fungus was defined as resistance to at least one antifungal agent in each category.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Clavien-Dindo classification of surgical complications (Grades I-V) was used for objective classification of post-transplant morbidity and mortality. \u003csup\u003e9\u003c/sup\u003e All vascular (hepatic artery, portal vein, or hepatic vein related) and biliary complications were clubbed together as biliary/vascular complications. ‘\u003cstrong\u003eThree-month mortality’\u003c/strong\u003e was defined as mortality occurring within 90 days after the LDLT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eImmunosuppression and follow-up\u003c/em\u003e\u003c/strong\u003e: Our post-transplant immunosuppression protocol has been previously published. \u003csup\u003e10\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis:\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCategorical variables were presented in number and percentage, and continuous variables were presented as mean ± SD or median, as suitable. Normality of data was tested by the Kolmogorov-Smirnov test. If the normality was rejected, then a non-parametric test was used. Quantitative variables were compared using an Independent t-test/Mann-Whitney test (when the data sets were not normally distributed) between the two groups. Qualitative variables were correlated using the Chi-Square test/Fisher’s exact test. Intergroup survival analysis using Kaplan-Meier analysis. A p-value of ≤0.05 was considered statistically significant. The data was entered in an MS EXCEL spreadsheet, and analysis was done using Statistical Package for Social Sciences (SPSS) version 23.0 (Armonk IBM).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eDuring the study period, 816 liver transplants were performed at our institute. After excluding 112 pediatric liver transplants, 69 deceased donor liver transplants, and 57 adult transplants for acute liver failure, 578 adult LDLT recipients were enrolled for the study. The mean age, gender distribution, and body mass index (BMI) were comparable between the groups. \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e Median Model for End Stage Liver Disease Sodium (MELD Na) score was 25 (IQ range 23\u0026ndash;27). The median MELD Na score was highest in patients in groups 1 and 2 (26 and 27, respectively). Nearly 90% of the patients (n\u0026thinsp;=\u0026thinsp;519) were transplanted for CLD, while in approximately 10% (n\u0026thinsp;=\u0026thinsp;59), the presentation was of acute-on-chronic liver failure (ACLF). The most common etiology for cirrhosis was alcoholic liver disease (ALD), 41.86% (n\u0026thinsp;=\u0026thinsp;242), followed by cryptogenic, 15.57%(n\u0026thinsp;=\u0026thinsp;90). The right lobe was more frequent type of graft used than the left lobe: 80% (n\u0026thinsp;=\u0026thinsp;462) vs 20% (n\u0026thinsp;=\u0026thinsp;116). The number of pre-transplant hospitalizations (1.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1, p value\u0026thinsp;=\u0026thinsp;0.00), number of hospitalizations with infections (1.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36, p value\u0026thinsp;=\u0026thinsp;0.04), and the duration of pre-transplant hospitalizations in days (10.69\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3, p value\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly less for patients in group 4. It was observed that the no sepsis group (group 5) had a higher number of admissions than group 4 (sepsis\u0026thinsp;\u0026gt;\u0026thinsp;90 days post-LT). (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Seventy percent (n\u0026thinsp;=\u0026thinsp;408) of all patients experienced at least one episode of pre-LDLT infection. \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePre-operative characteristics of the groups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCohort\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;578)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup1\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;104(18%)\u003c/p\u003e\u003cp\u003e(Infection within 15d)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup2\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;35(6%)\u003c/p\u003e\u003cp\u003e(Infection 16-30d)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGroup3\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;44(8%)\u003c/p\u003e\u003cp\u003e(Infection 31-90d)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGroup 4\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;222(38%)\u003c/p\u003e\u003cp\u003e(Infection\u0026thinsp;\u0026gt;\u0026thinsp;90d)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eGroup5\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;173(30%)\u003c/p\u003e\u003cp\u003e(No sepsis)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eP Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46.69\u0026thinsp;\u0026plusmn;\u0026thinsp;9.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46.07\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43.11\u0026thinsp;\u0026plusmn;\u0026thinsp;8.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;11.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e47.80\u0026thinsp;\u0026plusmn;\u0026thinsp;9.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e47.04\u0026thinsp;\u0026plusmn;\u0026thinsp;9.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.28\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale (n) (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e504(87.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93 (89.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34(97.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e41(93.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e184(82.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e152(87.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0.068\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale%(N)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e274(10.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11(10.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1(2.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3(6.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e38(17.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e221(12.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e25.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.10\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComorbidity%(N)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e146(25.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46(44.23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14(40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19(43.18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e91(40.99%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e73(42.19%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.14\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedian MELD Na (Range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (9\u0026ndash;40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26(12\u0026ndash;40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27(9\u0026ndash;37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e25(13\u0026ndash;38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23(10\u0026ndash;39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24(9\u0026ndash;40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.1\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e242(41.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42(40.38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15(42.85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27(61.36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e85(38.28%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e71(41.04%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003e0.089\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCryptogenic CLD (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90(15.57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17(16.34%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4(11.42%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3(6.81%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e42(18.91%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e24)13.87%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNASH CLD (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e79(13.66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15(14.42%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5(14.28%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8(18.18%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32(14.41%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e19(10.98%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHBV CLD (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57(9.86%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11(10.57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2(5.71%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1(2.27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17(7.65%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26(14.45%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHCV CLD (n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42(7.26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(4.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1(2.85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(4.54%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23(10.36%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e11(5.78%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers(n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68(11.76%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14(12.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8(22.85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(4.54%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22(9.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e22(12.71%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCLD (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e519(89.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93(89.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32(91.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e42(95.45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e200(90.09%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e148(85.54%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003e0.42\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACLF (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e59(10.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11(10.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3(8.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(4.55%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e22(9.91%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e23(14.46%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber of pre-LT hospitalizations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.94\u0026thinsp;\u0026plusmn;\u0026thinsp;1.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\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\u003eNumber of pre-LT hospitalizations with infections\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.02\u0026thinsp;\u0026plusmn;\u0026thinsp;0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration of pre-LT hospitalizations (Days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.17\u0026thinsp;\u0026plusmn;\u0026thinsp;16.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15.22\u0026thinsp;\u0026plusmn;\u0026thinsp;7.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.69\u0026thinsp;\u0026plusmn;\u0026thinsp;8.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e15.74\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\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\u003eDonor age (yrs) (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34\u0026thinsp;\u0026plusmn;\u0026thinsp;9.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29.09\u0026thinsp;\u0026plusmn;\u0026thinsp;6.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34.02\u0026thinsp;\u0026plusmn;\u0026thinsp;6.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e31.91\u0026thinsp;\u0026plusmn;\u0026thinsp;6.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e30.72\u0026thinsp;\u0026plusmn;\u0026thinsp;6.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDonor (Male)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e232(40.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42(40.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16(45.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17(38.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e89(40.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e68(39.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDonor (Female)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e346(59.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62(59.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19(54.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e27(61.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e133(59.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e105(60.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDonor LAI\u003c/p\u003e\u003cp\u003e(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.12\u0026thinsp;\u0026plusmn;\u0026thinsp;2.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.60\u0026thinsp;\u0026plusmn;\u0026thinsp;2.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.62\u0026thinsp;\u0026plusmn;\u0026thinsp;2.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11.07\u0026thinsp;\u0026plusmn;\u0026thinsp;2.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.99\u0026thinsp;\u0026plusmn;\u0026thinsp;2.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGRWR(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.89\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.78\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.87\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBlood loss (ml)\u003c/p\u003e\u003cp\u003e(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2484\u0026thinsp;\u0026plusmn;\u0026thinsp;584\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2782\u0026thinsp;\u0026plusmn;\u0026thinsp;620\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2520\u0026thinsp;\u0026plusmn;\u0026thinsp;564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2456\u0026thinsp;\u0026plusmn;\u0026thinsp;555\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2148\u0026thinsp;\u0026plusmn;\u0026thinsp;542\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2348\u0026thinsp;\u0026plusmn;\u0026thinsp;564\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRight lobe%(n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e462(80%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88(84.61%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32(91.42%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39(86.66%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e168(75.76%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e135(78.03%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLeft lobe%(n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e116(20%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16(15.38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3(8.58%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6(13.63%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e54(24.32%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e37(21.38%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.102\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003eAbbreviations; ACLF: Acute on chronic liver failure; ALD: Alcoholic liver disease; BMI: Body mass index; CLD: Chronic liver disease; GRWR: Graft to Recipient Weight Ratio; HBV: Hepatitis -B virus; HCV: Hepatitis C virus; LT: Liver transplantation; LAI: Liver attenuation index; MELD Na: Model for end-stage liver disease -Sodium.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eGroup-wise incidence of various sources of infection is provided in \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e. The common organisms responsible for sepsis during the preoperative period and postoperative period as well were Klebsiella followed by E. Coli. \u003cb\u003e(Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e)\u003c/b\u003e MDR and XDR organisms accounted for nearly 50% of all the infections in the pre-LT period and the rest were sensitive organisms. On the other hand, close to 58% of infections in the post-LT period were attributed to MDR and XDR organisms \u003cb\u003e(Table S 3 and S 4).\u003c/b\u003e During the pre-LT period, 61 (17.42%) patients had either proven or clinically suspected fungal infection. Similarly, 42 (13.81%) of the patients experienced fungal infection in the post-transplant period. \u003cb\u003e(Table S 3 and S 4)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmong all the post-LDLT outcomes \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e, need of withdrawal of immunosuppression therapy (P\u0026thinsp;=\u0026thinsp;0.001), duration of mechanical ventilation (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), three- month mortality (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and three-month mortality related to sepsis (p\u0026thinsp;=\u0026thinsp;0.034) showed significantly different trends among the groups.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePost-operative outcomes of the groups.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal(n\u0026thinsp;=\u0026thinsp;578)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup1\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;104\u003c/p\u003e\u003cp\u003e( Infection\u0026thinsp;\u0026lt;\u0026thinsp;15d)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup2\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;35\u003c/p\u003e\u003cp\u003e( Infection 16-30d)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGroup3\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;44\u003c/p\u003e\u003cp\u003e( Infection 31-90d)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGroup 4\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;222\u003c/p\u003e\u003cp\u003e( Infection \u0026gt;90d)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eGroup5\u003c/p\u003e\u003cp\u003eN\u0026thinsp;=\u0026thinsp;173\u003c/p\u003e\u003cp\u003e(No sepsis)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eP value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSepsis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e278(48.1% )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49(47.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e24(68.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22(50.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e107(48.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e76(43.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.126\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeptic shock\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e133(23.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30(28.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11(32.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11(25.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e45(20.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e36(21.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.28\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAntimicrobial treatment escalation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e269(47.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54(51.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25(68.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19(44.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e102(46.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e72(42.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.55\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWithdrawal of Immunosuppression therapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e241(42.1% )\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51(49.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25(71.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21(48.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e75(33.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e70(40.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\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\u003eDuration of withdrawal of immunosuppression(days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e10.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e13.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.51\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean duration of mechanical ventilation (hours)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43.44\u0026thinsp;\u0026plusmn;\u0026thinsp;21.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31.464\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e91.896\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e40.752\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e28.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e54.744\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\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\u003eMean duration for tapering off inotropes (Days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.04\u0026thinsp;\u0026plusmn;\u0026thinsp;2.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.929\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.619\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.836\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.18\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean Hospital stay (Days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e29.66\u0026thinsp;\u0026plusmn;\u0026thinsp;21.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30.240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.343\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31.159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e28.266\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e30.593\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.81\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean ICU stay (Days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.85\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12.894\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.943\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.636\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12.194\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e12.977\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.7\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReintubation rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63(10.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15(14.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3(8.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6(14.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e20(9.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e19(11.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.61\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReturn to ICU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67(11.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14(13.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4(11.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5(11.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24(10.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e20(11.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.97\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRe-laparotomy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51(8.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13(12.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6(17.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5(11.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e17(7.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e10(5.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.116\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePostoperative hemodialysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27(4.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9(8.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2(5.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1(2.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9(4.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6(3.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.28\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRejection requiring steroid pulse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32(5.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6(5.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1(3.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3(6.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e15(6.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8(4.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.10\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClavien-Dindo (\u0026gt;\u0026thinsp;Grade3) complications\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e206(35.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40(38.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15(42.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13(29.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e88(39.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e50(28.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.14\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHAT%(n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23(4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5(4.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2(5.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8(3.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e6(3.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.95\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePVT%(n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4(0.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1(1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1(2.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1(2.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1(0.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0(0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.24\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBiliary complications%(n)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30(5.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6(5.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2(5.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3(6.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12(5.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7(4.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.93\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThree months-mortality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70(12.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30(28.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5(14.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5(11.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16(7.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e14(8.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\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\u003eThree months mortality related to sepsis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39(55.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24(82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4(80%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2(40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5(31.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4(28.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e\u003cb\u003e0.034\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAbbreviations\u003c/b\u003e: HAT: Hepatic artery thrombosis; ICU: Intensive Care Unit; LT: Liver Transplant; PVT: Portal Vein Thrombosis.\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\u003eHepatic artery thrombosis (HAT) was detected in 23 patients (4%), portal vein thrombosis (PVT) was seen in 4 (0.7%), whereas biliary complications (both bile leak and biliary stricture) were noticed in 30 (5.2%) patients. There were no differences in the occurrence of biliary and vascular complications between the groups. There were no significant differences between the groups in terms of the occurrence of post-LDLT sepsis (p\u0026thinsp;=\u0026thinsp;0.126). Although group 1 and 2 had more frequent septic shock compared to group 3, group 4, and 5 (p\u0026thinsp;=\u0026thinsp;0.04; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), the differences across the groups were not statistically significant (p\u0026thinsp;=\u0026thinsp;0.28; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The three-month mortality for the whole cohort was 12.15% (n\u0026thinsp;=\u0026thinsp;70). This was highest for group 1, followed by groups 2 \u0026amp; 3, and lowest for groups 4 \u0026amp; 5 (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The proportion of deaths related to only sepsis was significantly higher in group 1 (82%) and group 2 (80%), compared to group 3 (40%), group 4 (31.2%), and lowest for group 5 (28.5%) (p\u0026thinsp;=\u0026thinsp;0.034). On comparing the outcome related to sepsis in less than 30 days versus sepsis beyond 30 days and the without-sepsis group, there was a significant difference in the incidence of septic shock, three-month mortality, and three-month mortality specifically related to sepsis between groups 1 and 2 combined (sepsis within 30 days before transplantation) versus other three groups clubbed together (P value 0.04, \u0026lt;\u0026thinsp;0.001, and \u0026lt;\u0026thinsp;0.001, respectively). \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOutcome related to infection in less than 30 days vs infection beyond 30 days and without sepsis.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal(n\u0026thinsp;=\u0026thinsp;578)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInfection\u0026thinsp;\u0026lt;\u0026thinsp;30 days (n\u0026thinsp;=\u0026thinsp;139)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInfection\u0026thinsp;\u0026gt;\u0026thinsp;30 days and no infection (n\u0026thinsp;=\u0026thinsp;439)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSepsis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e278 (48.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73(52.51%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e205(46.91%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.25(0.85\u0026ndash;1.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSeptic shock\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e133(23.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41 (29.45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e92(21.05%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.57(1.02\u0026ndash;2.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThree months-mortality\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e70(12.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35(25.17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35 (8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.87(2.31\u0026ndash;6.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThree months-mortality related to sepsis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39(55.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (80%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11(31.42%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8.73(2.92\u0026ndash;26.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\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\u003eIn order to identify the pre-transplant \u0026lsquo;infection-free interval\u0026rsquo; as a predictor of post-transplant three-month mortality, an ROC curve analysis was performed \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e \u0026lsquo;Infection-free interval\u0026rsquo; implies the number of days between resolution of the last episode of infection till the day of transplant. The ROC curve revealed an AUC of 0.780. With an acceptable upper limit of three-month mortality kept at 10%, and the survival cut-off analysis showed the cut-off for minimum pre-transplant \u0026ldquo;infection-free interval\u0026rdquo; required was 27 days.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eUnivariate analysis of the factors influencing the post-LDLT three-month mortality is showed in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. On multivariate analysis, pre-LT infection within 27 days, pre-LDLT infection with MDR/XDR organisms, high MELD Na\u0026thinsp;\u0026ge;\u0026thinsp;25, and post-LDLT biliary/vascular complications significantly predicted post-LDLT three-month mortality. \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e The Kaplan-Meier curve for three-month post-transplant survival is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnivariable and Multivariable analysis of factors predicting post-transplant three-month mortality.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eUnivariate Analysis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eMultivariate analysis\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOdds Ratio (95% Cl)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRecipient age\u0026thinsp;\u0026gt;\u0026thinsp;60 vs\u0026thinsp;\u0026lt;\u0026thinsp;60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.2(0.92\u0026ndash;5.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.067\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRecipient Male Sex\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.67(0.30\u0026ndash;1.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.332\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRecipient BMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.039(0.974\u0026ndash;1.108)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.247\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRecipient DM\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.580(0.20\u0026ndash;1.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.306\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eACLF vs CLD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.61(1.26\u0026ndash;5.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMELD Na\u0026thinsp;\u0026ge;\u0026thinsp;25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.23(1.72\u0026ndash;6.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.51(1.09\u0026ndash;5.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.030\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDonor Age\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.958(0.91-1.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDonor LAI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.98(0.885\u0026ndash;1.095)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.773\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-LT hospitalization within 3 months\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.01(0.55\u0026ndash;1.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre- LDLT infection within 27 days\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.8(2.22\u0026ndash;10.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.61(2.83\u0026ndash;4.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGraft Type (Left vs Right)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.98(0.55\u0026ndash;1.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGRWR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.14(0.6\u0026mdash;2.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntra-operative Blood Loss (ml)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.12(1.00-1.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.709\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-operative Biliary and vascular complications\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.4(1.8\u0026ndash;3.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.82(1.10\u0026ndash;2.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-operative septic shock\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.88(0.99\u0026ndash;3.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRejection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.56(0.17\u0026ndash;1.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-LDLT infection with MDR/XDR organisms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.2 (3.4\u0026ndash;15.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.8 (1.6\u0026ndash;14.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eAbbreviations; BMI: Body Mass Index; DM: Diabetes Mellitus; GRWR: Graft to recipient weight ratio; LAI: Liver attenuation index; LDLT: Live Donor Liver Transplant; MDR: Multi drug resistant; MELD Na: Model for end-stage liver disease -Sodium; XDR: Extensively drug resistant.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe present study is a first-of-its-kind endeavour in a large cohort of adult LDLT recipients being assessed for the impact of different timelines of pre-LDLT infections on post-LDLT sepsis and other outcomes. The study was specifically designed to assess the optimal pre-LDLT \u0026lsquo;infection-free interval\u0026rsquo; required to minimize the post-LDLT infection, mortality, and morbidity. The study results revealed the incidence of septic shock, three-month mortality, and sepsis-related mortality were higher for recipients experiencing infection within a month prior to LDLT. \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e Multivariate analysis also showed pre-LDLT infection within 27 days, infection with MDR/XDR organisms, MELD Na score\u0026thinsp;\u0026gt;\u0026thinsp;25 and post-LDLT biliary/vascular complications were the significant factors predicting three-month mortality with the first two factors revealing higher risk. Another novel finding on ROC curve analysis for an estimated post-transplant mortality of less than 10% at three months was a waiting period \u0026ldquo;cut off\u0026rdquo; of 27 days before LDLT following resolution of an episode of infection.\u003c/p\u003e\u003cp\u003eIt is a universally acknowledged fact that cirrhosis patients awaiting LT are at increased risk of infections and their sequalae. \u003csup\u003e1112\u003c/sup\u003e Factors contributing to this increased risk are immune dysfunction, alcohol abuse, malnutrition, genetic polymorphism, increased requirement of invasive procedures, high MELD score, and multiple hospitalizations. \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Overall, the incidence of pre-transplant sepsis in the current study was 70%, which was higher than reported in the literature. \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e In addition, over half of these patients experienced MDR/XDR infections. \u003cb\u003e(Table S3)\u003c/b\u003e This may be explained by a sicker patient cohort with a high median MELD Na of 25, multiple hospital admissions with sepsis and decompensations before LT, poor general condition with sarcopenia, and an overall delayed-decision making to LT because of the logistics of LDLT, making them more susceptible to infections. Average duration of pretransplant hospitalization of more than two weeks for optimization is also an additional surrogate marker of these high-acuity recipients. In an analysis of pre- and post-transplant sepsis profiles, Jalan et al. \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e reported SBP and UTI followed by bacteremia and pneumonia to be the most frequent sources of sepsis in cirrhosis patients awaiting LT, while in the study by Saleh et al. \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, pneumonia (40%) followed by nasal colonization (30%) and UTI (20%) were the most frequent sources of sepsis. In the current study, the common sources of infection overall in the pre-transplant period were respiratory and urinary tract, followed by SBP.\u003c/p\u003e\u003cp\u003eLiver transplant in a candidate with active sepsis can be deleterious for the recipient and has been associated with high incidences of graft loss and mortality.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Since LDLT for CLD is usually an elective procedure, a waiting period for ebbing of sepsis and related complications is justified. To achieve a clinical equipoise and optimal patient outcome, a period of infection-free period would be desirable. Previously published studies have shown that although pre-LT infections were associated with high post LT morbidity and hospital stay, but there was no difference in post-LT mortality.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e A recent study by Simone Incicco et al. from Italy also found that, even though patients with pre-LT infection within three months experienced a higher incidence of post-LT infections and septic shock, the time from resolution of infection to LT did not affect the incidence of post-LT complication or one- and 5-year patient survival rates.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e However, these studies did not look at the impact of the different timelines of infection in the pre-LT period on post-transplant outcome and, specifically, did not evaluate the desired infection-free interval before proceeding for LT. The current study specifically addresses these issues. Although the incidence of sepsis was not significantly different across the five categories of pre-LDLT infection, the incidence of septic shock was different between groups 1 \u0026amp; 2 versus the rest of the cohort. The post-LT three-month mortality was also significantly higher in groups 1 and 2 recipients in comparison to the rest of the groups (25% vs. 8%). \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e More than half of the mortality for the whole cohort was attributed to sepsis (both bacterial and fungal), and the proportion of three-month mortality related to sepsis was significantly higher in groups 1 and 2 compared to other groups (80% vs. 31%). \u003cb\u003e(\u003c/b\u003eTables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e This indicates the patients having pre-LDLT infection within one month, though not an independent predictor of post-LDLT sepsis; when sepsis occurred in these subsets of recipients, it progressed to septic shock more often and contributed to early post-LT mortality due to sepsis. These results compared to previous studies give us a new perspective regarding the timeline of pre-LT sepsis and its impact on sepsis-related early post-LT mortality and provide with crucial decision-making with regard to the timing of LDLT in the presence of infection within one month prior to LDLT. Hence, risk stratification of pre-LDLT infection as per the shorter timelines better predicts post-LDLT outcome. The ROC curve analysis revealed the optimal infection-free period required to predict better post-LT mortality is approximately four weeks with a good AUC (0.780). Multivariate analysis also showed pre-LT sepsis within 27 days predicts post-LDLT three-month mortality. This window period can help to plan LT, particularly in the context of LDLT for CLD patients, as the timing of transplant can be scheduled beforehand. The mandatory \u0026lsquo;Infection-free interval\u0026rsquo; however, may not be applicable in sicker recipients such as ACLF and alcoholic hepatitis, as organ dysfunction and systemic inflammatory response playing a major role in addition to sepsis and high mortality without liver transplant.\u003c/p\u003e\u003cp\u003eNearly half of the recipients experienced post-LT sepsis as defined by sepsis 2 and 3 criteria.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e This incidence is comparatively higher than the contemporary literature\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e and could be due to a sicker cohort of patients with a high incidence of pre-transplant infections and a high proportion of MDR/XDR infections (51%) compared to the reported literature. In our study, bacteremia was the most common source of sepsis across all groups during the post-LDLT period, while in the study by Hara and colleagues,\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e pneumonia followed by bacteremia were the most common sources of post-LT sepsis. On the other hand, intrabdominal sepsis was the most common source of post-LT sepsis, according to the study by Simone Incicco et al\u0026rsquo;.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e These differences, akin to pre-LT infections, could be attributable to the pattern of hospital-acquired infection, antibiotic usage, patients\u0026rsquo; etiological profile, and surgical reconstructions such as biliary anastomosis. In addition, the majority of the organisms responsible for post-LT sepsis in our study had MDR (44.73%) or XDR (13.15%) infections. \u003cb\u003e(Table S4)\u003c/b\u003e In recently reported literature, the incidence of infection by MDR organisms varies from 20\u0026ndash;68% following DDLT.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e The data on the incidence of MDR infection in LDLT recipients has not been reported in the literature, and to our knowledge, the current study is the first to reports post-LDLT sepsis with a very high incidence of MDR infections. With more than two weeks of average in-hospital stay, and almost over half of the recipients harboring MDR infections prior to LDLT, higher incidence of post-LDLT sepsis with MDR infections suggest hospital-acquired infections by these organisms. In addition, approximately 14 % of the paients had fungal sepsis, and 35 % of them bing multidrug resistant. \u003cb\u003e(Table S4)\u003c/b\u003e In contrast to the previous study,\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e our study result shows preoperative infection with MDR or XDR organisms is a strong determinant of poor outcome and predicts three-month mortality. In view of the ever-increasing incidence of infections by MDR organisms in cirrhotic patients,\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e this study finding carries considerable significance and hence could guide the timing of liver transplants in elective LDLT.\u003c/p\u003e\u003cp\u003eLDLT recipients are at increased risk of biliary/vascular complications because the operation being technically more complicated. \u003csup\u003e22 23\u003c/sup\u003e Biliary/vascular complications are known to increase the risk of septic complications. In the current cohort, the overall biliary-vascular complications were about 9%, which compares favourably with the published literature. \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Overall biliary complications of 5% and vascular complications of 4% at three months could be attributed to the refinement in technique described previously. \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThis is the largest study analyzing the impact of pre-LDLT infection on post-LDLT outcomes, with high median MELD Na scores and high incidence of pre- and post-LDLT infections. This is also a first endeavour to stratify outcomes based on the pre-LDLT timeline of infection and to ascertain an ideal cutoff of pre-transplant \u0026lsquo;infection-free period\u0026rsquo; in the LDLT cohort. The main limitations are that, as the study outcomes were analyzed over a long period and there have been changes in patient management strategies and protocols, including selection, medical management, critical care, and surgical technique, this could have influenced outcomes.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eSepsis within one month before LDLT is associated with higher overall and sepsis-related three-month mortality. Pre-LDLT infection within a month and infection by MDR or XDR organisms, MELD Na\u0026thinsp;\u0026gt;\u0026thinsp;25, and post-LT biliary/vascular complications significantly impact post-LT mortality. Pretransplant \u0026lsquo;infection-free interval\u0026rsquo; is a good predictor for post-LT mortality, with four weeks as ideal cutoff before LT to reduce early post-LT sepsis-related mortality.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLiver transplant\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLDLT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLiving donor liver transplantation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCLD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eChronic liver disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDDLT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDeceased donor liver transplant\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSBP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSpontaneous bacterial peritonitis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eUTI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eUrinary Tract Infection\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMDR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMultidrug resistance\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eXDR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eExtensively drug resistant\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eReceiver Operating Characteristic\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSPSS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStatistical Package for Social Sciences\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMELD Na\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eModel for End Stage Liver Disease Sodium\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eACLF\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAcute on chronic liver failure\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eALD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAlcoholic Liver Disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHAT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHepatic artery thrombosis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePVT\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePortal Vein Thrombosis\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody mass index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGRWR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGraft to Recipient Weight Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHBV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHepatitis -B virus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHCV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHepatitis C virus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLAI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLiver attenuation index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eICU\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eIntensive Care Unit\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDiabetes Mellitus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBAL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBronchoalveolar lavage\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSBE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSpontaneous bacterial effusion\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eET\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEndotracheal tube\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor’s contribution:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy concept/Design: VP.\u003c/p\u003e\n\u003cp\u003eData collection: BN, NM, GHR, NSP, GS, VK.\u003c/p\u003e\n\u003cp\u003eAnalysis and interpretation of data: BN, NM, GHR, VP.\u003c/p\u003e\n\u003cp\u003eManuscript drafting: BN, NM, VP.\u003c/p\u003e\n\u003cp\u003eCritical revision of the manuscript for important intellectual content: VP, NM, SKS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e: The authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: The authors received no financial support to produce this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePatient Consent:\u003c/strong\u003e Consent was obtained from the prospective arm and was waived off for the retrospective arm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval:\u0026nbsp;\u003c/strong\u003eThe study was approved by institutional scientific review board and ethics committee (IEC/2020/80/MA11)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration:\u0026nbsp;\u003c/strong\u003ePresent RCT was registered at ClinicalTrials.gov (NCT05109156)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement:\u003c/strong\u003e The authors wish to thank Dr. Guresh Kumar and Dr Ankit Bharadwaj for their contribution in the statistical analysis of the study\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFagiuoli S, Colli A, Bruno R et al. 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Langenbecks Arch Surg. 2024;408(1). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/S00423-023-02759-X\u003c/span\u003e\u003cspan address=\"10.1007/S00423-023-02759-X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\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":true,"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":"Cirrhosis, Liver transplantation, Living donor, Infection, Sepsis, Infection-free period, Multidrug resistance, Extensive drug resistance, Three-month mortality, Model for End Stage Liver Disease Sodium","lastPublishedDoi":"10.21203/rs.3.rs-7280166/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7280166/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003ePreoperative infection is a major determinant of outcome following liver transplant. The current study aims to assess the impact of the interval between preoperative infection and transplantation on post-operative outcomes following adult living donor liver transplantation (LDLT).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: Consecutive LDLT recipients (n=578), were divided into Group 1 (infection within 15 days), Group 2 (15 to 30 days), Group 3 (30 to 90 days), Group 4 (\u0026gt; 90 days), and Group 5 (without documented infection). The impact of timelines of pre-transplant infections on post-transplant outcomes were analyzed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe group-1, 2, 3, 4 and 5 comprised 104(18%), 35(6%), 44(8%), 222(38%), and 173(30%) recipients respectively (n=578). Post-transplant sepsis and septic shock were seen in 278(48%) and 133(23%) patients respectively. Three-month mortality was 12.1% (70/578); 55.7% (39/70) of them had mortality attributed to sepsis. Patients with pre-LDLT infection within 30 days experienced higher three-month overall and sepsis-related mortality [25.17% vs 8%; OR:3.87(2.31-6.47); p=0.04] and [80% vs 31.42%; 8.73(2.92-26.04); p=\u0026lt;0.001] respectively, compared to recipients with infection beyond 30 days or no infection. With an upper limit of three-month mortality kept at 10%, ROC curve showed minimum pre-transplant ‘Infection-free interval’ of 27days (AUC=0.780). Multivariate analysis revealed pre-LDLT infection within 27 days [OR: 3.61(2.83-4.44)], pre-LDLT infection with MDR/XDR organisms [4.8 (1.6-14.9)], MELD \u0026gt;25 [2.51(1.09-5.79)], and biliary/vascular complications [1.82(1.10-2.74)] predicted three-month mortality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eInfection within one month before LDLT is associated with high overall and sepsis-related three-month mortality. Preoperative infection within 27 days and MDR/XDR infections, MELD Na \u0026gt;25, and post-LDLT biliary/vascular complications predicted mortality.\u003c/p\u003e","manuscriptTitle":"Preoperative infection within a month is associated with inferior post-transplant outcomes in adult living donor liver transplants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-25 15:05:33","doi":"10.21203/rs.3.rs-7280166/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":"58f2f029-ff5f-48d6-9de8-155a739a1f8c","owner":[],"postedDate":"August 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-15T00:49:21+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-25 15:05:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7280166","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7280166","identity":"rs-7280166","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}
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