Comparative Survival Analysis of Urea Kinetic Based Indices

Hemodialysis Modality, Percentage of Body Fat, and Patient Survival

Background

A number of studies have reported lower mortality of overweight hemodialysis patients. This post hoc analysis of an observational prospective single-center study was aimed at elucidating whether both being overweight and surviving longer could result from changes in the hemodialysis modality.

Methods

The study included a cohort of 242 patients who were gradually switched from cuprophane membrane and acetate dialysis to polysulfone (including high-flux) membranes and bicarbonate dialysis. The analysis involved 12 months of baseline data obtained during the first calendar year after the patients entered the study (1994–2001) and repeated measurements for up to 132 months of follow-up (until 2004). Anthropometric measurements were made during the winter season and the percentage of body fat (%fat) was calculated from triceps, biceps, subscapular, and suprailiac skinfolds (K/DOQI guidelines). Kt/V, normalized protein catabolic rate, and cardiovascular comorbidity were also determined and laboratory analyses undertaken.

Results

Significant correlations were found between %fat and bicarbonate dialysate as well as polysulfone membrane and high-flux membrane. The linear mixed model showed dependence of %fat on polysulfone and high-flux membrane (p<0.01) Multivariate Cox regression (time-dependent covariates) found %fat to be an independent factor for longer survival, in addition to polysulfone and high-flux membranes.

Conclusion

Changes in hemodialysis modality were followed by both higher body fat percentage and patient survival. The reverse epidemiology of overweight patients might be at least partially the result of the influence of nonnutritional factors, such as a change in hemodialysis modality (introducing biocompatible high-flux and low-flux membranes and bicarbonate dialysis).

Predictive value of echocardiography and its relation to Kt/V and anthropometric parameters in hemodialysis patients

BACKGROUND

In order to evaluate the predictive value of echocardiograph parameters for mortality of hemodialysis patients and their relation to Kt/V and anthropometry, a prospective, single center study was analyzed post-hoc.

METHODS

This analysis encompassed 106 patients on maintenance hemodialysis monitored for 108 months from 1996 to 2004. spKt/V was calculated using the Daugirdas formula. Anthropometric measurements included mid-arm muscle measurements (MAMC) and percentage of body fat (%fat). Echocardiography included the estimations of left ventricular wall thickness, dimensions and volumes (EDV, ESV), systolic LV function (ejection fraction - EFLV, fractional shortening - VCF, stroke volume - SV) and diastolic LV function (E/A, VTI-A wave of transmitral flow velocity), left atrial diameter, as well as assessment of clinical and biochemical parameters. The Cox proportional hazard model was used to estimate predictive values of echocardiograph parameters.

RESULTS

Kt/V correlated significantly with left ventricular systolic and diastolic volumes and function, septal and posterior wall thickness and left atrium dimension. MAMC and %fat also correlated with many echocardiograph parameters. Multivariate Cox regression selected age [HR 1.07; CI (1.03-1.12); p < 0.01], albumin [HR 0.88; CI (0.79-0.97); p < 0.05] and left atrium dimension - binary [values > 4 cm were marked as "1" and others "0" - HR 3.76; CI (1.56-9.03); p < 0.01] as independent predictors of death.

CONCLUSION

Left atrium dimension was the most important predictor of mortality among the echocardiograph parameters. Many of these parameters were related to Kt/V and anthropometric measurements and could be the combined consequence of hypervolemia and hypertension.

Comparison of two diverse measurement methods by graphical agreement

Biological processes are complex, and several methods are often used to measure them. However, different methods could determine diverse parts of a single biological process. To date, there are no widely accepted and convenient methods for comparison between the results, so we consider graphical analysis with the ability to demonstrate the pattern of distribution of findings from one method across another. It appears that a two-series area plot is the most appropriate. After using normal values and a coding reference and examining the variables, unnecessary information is diminished and the graphics become more obvious. Three possibilities may be found: agreement or disagreement between variables or disagreement from normal values. Therefore, the graph may also be used to determine the corresponding normal values between variables. The association between variables may be tested using kappa coefficients, although graphical analysis remains more informative. Therefore, graphical analysis could compare two completely different variables that measure the same biological process or determine the range of normal values.

Could the level of serum albumin be a method for assessing malnutrition in hemodialysis patients?

BACKGROUND

Traditionally, serum albumin concentration has been used for assessing the nutrition status of hemodialysis patients despite evidence that the level is also affected by inflammation and many other underlying disorders frequently present in these individuals. The authors evaluated albumin as a nutrition parameter, comparing it with more specific anthropometric parameters.

METHODS

The study included a cohort of 271 patients. The analysis involved data obtained after patients entered the study (1994-2004). Anthropometric measurements included skinfolds, mid-arm circumference, mid-arm muscle circumference, percentage of body fat, body mass index, body height, and dry weight. Kt/V and normalized protein catabolic rate were also determined and laboratory analyses undertaken.

RESULTS

Serum albumin was only weakly correlated with mid-arm circumference (r = 0.12), mid-arm muscle circumference (r = 0.15), and fat-free mass (r = 0.12). Common factor analysis of nutrition parameters uncovered latent variables, but serum albumin was not associated strongly with them. The sensitivity of albumin in detecting malnutrition was 24%, with a specificity of 88% and a predictive value of 74%. Graphic analysis showed disagreement in albumin levels with percentage of body fat and mid-arm muscle circumference.

CONCLUSION

Serum albumin determination was shown to be a test with low sensitivity and specificity for evaluating malnutrition in hemodialysis patients. The values correlated weakly and showed graphic disagreement with anthropometric parameters. Therefore, methods that measure percentage of body fat and muscle mass should be used together or instead of serum albumin level for assessing the nutrition status of hemodialysis patients.

The predictive value of anthropometric parameters on mortality in haemodialysis patients

BACKGROUND

Since protein-calorie malnutrition is a common factor influencing morbidity and mortality of haemodialysis patients, assessing their nutritional status is important. The aim of this study was to investigate the predictive value of anthropometric parameters on mortality and their interrelationship.

METHODS

The study included a cohort of 242 patients. The analysis involved baseline data obtained during the first calendar year after the patients entered the study (1994-2001) and repeated measurements for up to 132 months of follow-up (until 2004). Anthropometric measurements were made during the winter season and included skinfolds, mid-arm circumference (MAC), body height and weight. The percentage of body fat (%fat) was calculated from triceps (TSF), biceps, subscapular and suprailiac skinfolds (Disease Outcomes Quality Initiative (DOQI) guidelines) and mid-arm muscle circumference (MAMC) from MAC and TSF. Body mass index (BMI), Kt/V, normalized protein catabolic rate (NPCR) and cardiovascular co-morbidity were also determined and laboratory analyses undertaken.

RESULTS

Strong correlations were found among the anthropometric parameters. Extended Cox regression analysis selected %fat, MAC, MAMC and TSF in addition to age, ischaemic heart disease, congestive heart failure, Kt/V, haemoglobin, creatinine, albumin and NPCR as potential predictors of mortality. The same anthropometric parameters were found to be independent mortality predictors in corresponding models. The most predictive anthropometric factor was MAC. BMI was not a risk factor.

CONCLUSION

Percentage of body fat, MAC, MAMC and TSF were independent predictors of mortality of haemodialysis patients, and MAC was the most predictive one.