[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-188402-en":3,"doc-seo-188402-105":30,"detail-sidebar-cat-1-en-105":89},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":11,"category_id":12,"category_name":13,"doc_title":14,"doc_description":15,"doc_content":16,"file_id":17,"file_url":18,"file_type":19,"file_size":20,"view_count":4,"is_deleted":4,"is_public":11,"is_downloadable":11,"audit_status":11,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":15,"update_tm":28,"read_time":29},188402,962084931830,"Jacob","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",1,17,"Forms","Patient Characteristics and AKI Risk Predictors in Liver Transplant Recipients","This study summarizes baseline characteristics of 134 liver transplant recipients and compares groups with acute kidney injury (AKI, n=64) versus non-AKI (n=70). It reports demographic distribution, transplant indication patterns (including viral liver disease and alcoholism), liver disease severity (Child-Pugh, MELD, MELD-Na), renal and coagulation markers, and perioperative variables such as ischemia times and surgery duration. Multivariable results identify viral liver disease (adjusted OR 2.9), warm ischemia time (OR 1.1), and serum lactate (OR 1.3) as independent predictors of AKI.","| Variable | 134 patients |\n| --- | --- |\n| Gender |  |\n| Female, n (%) | 67 (50%) |\n| Male, n (%) | 60 (50%) |\n| Age (years), median (IQ) | 56 (48-62) |\n| Transplant indication |  |\n| Viral liver disease, n (%) | 67 (50%) |\n| Alcoholism, n (%) | 80 (59%) |\n| Hepatic encephalopathy, n (%) | 62 (46%) |\n| Child-Pugh classification |  |\n| Class A or B, n (%) | 92 (69%) |\n| Class C, n (%) | 42 (31%) |\n| Hypertension, n (%) | 32 (24%) |\n| Diabetes, n (%) | 35 (26%) |\n| Heart disease, n (%) | 2 (1.5%) |\n| Glomerular filtration rate, |  |\n| median (IR) | 93 (65.2-115.2) |\n| MELD, median (IR) | 19 (15-23) |\n| Creatinine (preoperative, mg/dL), |  |\n| median (IR) | 0.9 (0.7-1.2) |\n| INR, median (IR) | 1.5 (1.2-1.7) |\n| Bilirubin, median (IR) | 2.8 (1.7-6.3) |\n| Sodium, median (IR) | 136 (132-139) |\n| MELD-Na, median (IR) | 22 (18-26) |\n\n\n| Variable | AKI (n = 64) | Non-AKI (n = 70) | P |\n| --- | --- | --- | --- |\n| Gender (female %) | 14 (21) | 26 (37) | 0.6 |\n| Hypertension (%) | 14 (21) | 18 (25) | 0.6* |\n| Diabetes (%) | 21 (32) | 14 (20) | 0.1* |\n| Heart Disease (%) | 1 (0.01) | 1 (0.01) | 0.1* |\n| Alcoholism (%) | 42 (66) | 38 (54) | 0.2* |\n| Encephalopathy (%) | 38 (59) | 24 (34) | 0.005* |\n| CHILD A or B (%) | 39 (60) | 53 (75) | 0.09* |\n| C | 25 (40) | 17 (25) |  |\n| Trans-operative Bleeding (%) | 33 (51) | 28 (40) | 0.2* |\n| Volume of Blood Products (%) | 39 (60) | 33 (47) | 0.1* |\n| Viral etiology for underlying end-stage liver disease (%) | 40 (62) | 27 (38) | 0.009* |\n| Age-median (IR) (years) | 55 (48.2-62.7) | 56.5 (47.7-62) | 0.2† |\n| Preoperative creatinine-median (IR) (mg/dL) | 0.9 (0.7-1.2) | 0.9 (0.6-1.2) | 0.5† |\n| INR-median | 1.5 (1.3-1.8) | 1.4 (1.1-1.6) | 0.06† |\n| Bilirubin-median (IR) (mg/L) | 3.7 (2-6.8) | 2.2 (1.4-5) | 0.07† |\n| Sodium-median(IR) (mmol/L) | 135 (131-138) | 138 (133-140) | 0.02† |\n| MELD-Na– median (IR) | 23 (18-28) | 22 (17-24) | 1† |\n| MELD-median (IR) | 20 (16.2-23.7) | 18 (14.7-22) | 0.1† |\n| GFR-pre-LT-mean (SD) (mL/min) | 94.5±45.2 | 87.7 ± 30 | 0.3‡ |\n| Cold ischemia time-mean (SD) (min) | 316.8±74 | 299 ± 61 | 0.1‡ |\n| Hot ischemia time-median (IR) (min) | 31 (28-35) | 30 (25-32.2) | 0.02† |\n| Surgery duration-mean (SD) (min) | 396±70 | 384 ± 94 | 0.4‡ |\n| Lactate-median (IR) (mmol/L) | 2.3 (1.7-3.3) | 1.9 (1.4-2.5) | 0.04† |\n\n\n| Predictor | Adjusted Odds | P | IC 95% |\n| --- | --- | --- | --- |\n| Viral liver disease | 2.9 | 0.01 | 1.2 - 7 |\n| Warm ischemia time | 1.1 | 0.02 | 1.01 - 1.20 |\n| Serum lactate | 1.3 | 0.03 | 1.02 - 1.89 |","cbCaifLxnEW6lOkI","https://ap.wps.com/l/cbCaifLxnEW6lOkI","pdf",179007,7,"English","en",105,"","[{\"question\":\"How does the document define and compare the AKI and non-AKI groups?\",\"answer\":\"It stratifies 134 patients into AKI (n=64) and non-AKI (n=70) groups and reports corresponding baseline and perioperative variables with P-values for group comparisons.\"},{\"question\":\"Which perioperative ischemia variable is associated with AKI risk in the predictor table?\",\"answer\":\"Warm ischemia time is an independent predictor of AKI, with an adjusted odds ratio of 1.1 (P=0.02), as reported in the final results section.\"},{\"question\":\"What independent predictors of AKI are identified in the adjusted analysis?\",\"answer\":\"The document lists viral liver disease (adjusted OR 2.9, P=0.01), warm ischemia time (adjusted OR 1.1, P=0.02), and serum lactate (adjusted OR 1.3, P=0.03) as independent predictors.\"}]","Patient Characteristics and AKI Risk Predictors in Liver Transplant Recipients | PDF",1788389177,3,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":14,"keywords":25,"description":15,"schema_data":34,"social_meta":84,"head_meta":86,"extra_data":88,"updated_unix":28},"patient-characteristics-and-aki-risk-predictors-in-liver-transplant-recipients",{"@graph":35,"@context":83},[36,52,66],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,49],{"item":40,"name":41,"@type":42,"position":11},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/template/","Template",2,{"item":48,"name":13,"@type":42,"position":29},"https://docshare.wps.com/template/forms/",{"item":50,"name":14,"@type":42,"position":51},"https://docshare.wps.com/template/patient-characteristics-and-aki-risk-predictors-in-liver-transplant-recipients/188402/",4,{"url":50,"name":14,"@type":53,"author":54,"headline":14,"publisher":56,"fileFormat":59,"inLanguage":23,"description":15,"dateModified":60,"datePublished":60,"encodingFormat":59,"isAccessibleForFree":61,"interactionStatistic":62},"DigitalDocument",{"name":9,"@type":55},"Person",{"url":40,"name":57,"@type":58},"DocShare","Organization","application/pdf","2026-09-02",true,{"@type":63,"interactionType":64,"userInteractionCount":4},"InteractionCounter",{"@type":65},"ViewAction",{"@type":67,"mainEntity":68},"FAQPage",[69,75,79],{"name":70,"@type":71,"acceptedAnswer":72},"How does the document define and compare the AKI and non-AKI groups?","Question",{"text":73,"@type":74},"It stratifies 134 patients into AKI (n=64) and non-AKI (n=70) groups and reports corresponding baseline and perioperative variables with P-values for group comparisons.","Answer",{"name":76,"@type":71,"acceptedAnswer":77},"Which perioperative ischemia variable is associated with AKI risk in the predictor table?",{"text":78,"@type":74},"Warm ischemia time is an independent predictor of AKI, with an adjusted odds ratio of 1.1 (P=0.02), as reported in the final results section.",{"name":80,"@type":71,"acceptedAnswer":81},"What independent predictors of AKI are identified in the adjusted analysis?",{"text":82,"@type":74},"The document lists viral liver disease (adjusted OR 2.9, P=0.01), warm ischemia time (adjusted OR 1.1, P=0.02), and serum lactate (adjusted OR 1.3, P=0.03) as independent predictors.","https://schema.org",{"og:url":50,"og:type":85,"og:title":14,"og:site_name":57,"og:description":15},"article",{"robots":87,"canonical":50},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":90},[91,96,101,106,111,116,119,124,129],{"id":92,"doc_module":11,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},11,"Presentations",90,"presentations",{"id":97,"doc_module":11,"doc_module_name":45,"category_name":98,"show_sort_weight":99,"slug":100},12,"Resumes",80,"resumes",{"id":102,"doc_module":11,"doc_module_name":45,"category_name":103,"show_sort_weight":104,"slug":105},14,"Invoices",70,"invoices",{"id":107,"doc_module":11,"doc_module_name":45,"category_name":108,"show_sort_weight":109,"slug":110},15,"Posters",60,"posters",{"id":112,"doc_module":11,"doc_module_name":45,"category_name":113,"show_sort_weight":114,"slug":115},16,"Social Media",50,"social-media",{"id":12,"doc_module":11,"doc_module_name":45,"category_name":13,"show_sort_weight":117,"slug":118},40,"forms",{"id":120,"doc_module":11,"doc_module_name":45,"category_name":121,"show_sort_weight":122,"slug":123},18,"Letters",30,"letters",{"id":125,"doc_module":11,"doc_module_name":45,"category_name":126,"show_sort_weight":127,"slug":128},21,"Paper Templates",5,"papers-templates",{"id":130,"doc_module":11,"doc_module_name":45,"category_name":131,"show_sort_weight":4,"slug":132},158,"General","general-158"]