Effect of Perioperative Delta Sodium on Outcomes in Liver Transplant Recipients
Conditions: Liver Transplant; Complications, Perioperative/Postoperative Complications, Electrolyte Disturbance
Sponsor: Institute of Liver and Biliary Sciences, India

Cover Page 
 
Title: Effect of Perioperative Delta Sodium on Outcomes in Liver 
Transplant Recipients 
 
NCT: number awaited 
 
Date of document: 01/01/2018 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Study protocol 
 
All the patients who received a liver transplantation during the study period were 
identified and medical records were retrieved from the physical database at the medical 
records department. 
Data collected included the following: Patient’s age, gender, MELD score, body mass 
index, type of Liver Transplant (living donor or deceased donor recipients), underlying 
liver disease, history of hepatic encephalopathy (HE), and treatment with diuretics 
before surgery. 
Laboratory data recorded included serum sodium levels: preoperative, postoperative, 
peak, and trough (Na pre, Na post, Na max, and Na nadir),. Delta sodium (ΔNa) is 
defined as Na post – Na pre, and maximum delta sodium (ΔNa-max) as Na max – Na 
nadir. 
Intra-operative administration data of sodium bicarbonate, crystalloids and colloid 
volume, type, units of fresh frozen plasma (FFP) and packed red blood cells (PRBC), 
Vasopressin, Noradrenaline and diuretics was collected. 
Outcome variables assessed were the number of ICU days, number of ventilator days 
both NIV and invasive, day of extubation, any postoperative neurological 
complications,re-intubation if any and cause thereof were noted. 
Statistical Analysis 
 
Data were expressed as mean ± SD or median (interquartile range). Categorical 
Variables were compared with Pearson Chi-Square test, and continuous variables were 
compared with Student t test.  Non-normal continuous variables were compared using 

the Mann-Whitney U test (unpaired data). Analysis of variance (ANOVA) or Kruskal – 
Wallis ANOVA for repeated measurements was used for statistical analysis. Correlation 
were performed to measure the relationship between variables. Logistic Regression 
was used to evaluate the association between risk factors with an event. A p-value of 
<0.05 was considered statistically significant for all comparisons.