Predicting dry weight in patients with ascites and liver cirrhosis using computed tomography imaging

Background/Aims: In cirrhotic patients, ascites may increase weight and adversely impact liver transplant candidacy. Methodology: In this study we used linear and volume measurements from abdominal CT imaging to estimate dry weight of transplant candidates using multivariable linear regressions. We reviewed 200 scans. For males there were 81, 26, and 41 scans with no/small, moderate, and large ascites, respectively, and 41, 6, and 5 scans of females with no/small/moderate, and large ascites respectively. Results: In males without ascites, subxiphoid subcutaneous fat volume had the strongest correlation with weight (r=0.826); the best prediction utilized four variables including height, subcutaneous subxiphoid fat volume, and intra-abdominal and subcutaneous umbilicus fat volumes (r=0.923, r²=0.852, SEE=15.15, p<0.001). In females, subcutaneous fat volume above the umbilicus had the best correlation (r=0.815); incorporating height and anterior subxiphoid fat thickness increased predictive accuracy (r=0.892, r²=0.796, SEE=15.37, p<0.001). These regressions consistently under-predicted scale weight in patients with moderate and large ascites (5.92±25.50 pounds and 11.21±19.34 pounds in males, and 2.29±23.76 and 8.37±11.44 in females). Conclusions: Equations to estimate patient weight regardless of ascites may offer a more accurate representation of size than scale weight in transplant candidates with ascites.