Background and Aim
Haemodialysis (HD) patients have a high mortality rate, mainly due to cardiovascular disease and malnutrition. The aim of this study was to evaluate the efficacy of the analysis of body composition by bioimpedance (BIA) to predict the mortality risk in haemodialysis patients.
Materials and Methods
Observational longitudinal study (six years) on 78 prevalent HD patients
Gender, (n male) |
52 (66,7%) |
Age, years |
65,2±13,7 |
Dialysis vintage, years |
6,8±7,1 |
Kt/v sp Daug. |
1,5±0,3 |
BMI, Kg/m² |
26,8±5,1 |
sCreatinine, mg/dl |
9,9±2,6 |
sAlbumin, g/dl |
4±0,3 |
CRP, mg/dl |
0,94±1,4 |
Every two years, we collected clinical, laboratory and BIA data, including BIVA analysis and hydration scale (FIGURA 1).
We compared the BIA data of patients dead during the study period (n = 45; 65%) with those of survivors (n = 24; 35%). The significance of the differences between the mean values of the two groups at the baseline was evaluated.
Results
Nine patients moved to another haemodialysis facility.
|
Alive |
Dead |
p |
Age, years |
61±+13,3 |
70,5±11,8 |
0,003 |
Dialysis vintage, years |
10,2±9,1 |
5,3±5,6 |
0,007 |
Body Weight, Kg |
69,4±11,8 |
79,5±18,1 |
0,02 |
BMI, kg/m² |
24,8±3,1 |
28±6 |
0,01 |
Kt/v spDaug. |
1,62±0,2 |
1,5±0,3 |
ns |
sAlbumin, g/dl |
4,1±0,2 |
4,1±3,6 |
ns |
Resistance, Ohm |
644,9±100,7 |
599,1±89,7 |
ns |
Reactance, Ohm |
67,3±13,7 |
53,5±11,7 |
0,000003 |
Phase Angle, Detgree |
5,9±0,8 |
5,1±0,9 |
0,0003 |
BCMI, Kg/m² |
7,91±1,8 |
7,1±1,7 |
ns |
FMI, Kg/m² |
8,4±2,8 |
11,2±4,1 |
0,004 |
ECW, % |
46,1±3,6 |
50,6±5,2 |
0,0003 |
Hydratation, % |
71,2±3,3 |
73,3±1,8 |
0,0006 |
The patients dead at different times during the six years had significantly higher values of BMI and fat mass index compared to the survivors, while there were no significant differences for body cell mass (BCM) index and serum albumin.
Furthermore, deceased patients had lower values of reactance, phase angle and the percentage of extracellular water was higher.
Finally the BIVA analysis confirmed that the hydration was significantly higher in the deceased.
In summary survivors had normal values of BMI and fat mass, a smaller reduction in BCM and less fluid overload than deceased patients.
Conclusion
The survival of HD patients is influenced by the nutritional status.
In particular, fluid overload and decrease in muscle mass play a decisive role on survival.
Low values of electrical resistance and of phase angle and high values of hydration predict mortality risk in HD patients.