CKD: Measuring Body Composition (2009)

Citation:
 
Study Design:
Class:
- Click here for explanation of classification scheme.
Quality Rating:
Research Purpose:

To identify early abnormalities in body composition in chronic kidney disease (CKD) by means of bioelectrical impedance analysis (BIA) and assessment of main nutritional markers in pre-dialysis patients who were at various stages of CKD at the first referral to an outpatient nephrology clinic.

Inclusion Criteria:

CKD patients

  • Adult CKD patients referred to first time to the outpatient renal clinic
  • Creatinine clearance (CrCl) equal or greater than 60ml per minute per 1.73m2 measured twice, two weeks apart, and divided according to Kidney Disease Outcomes Quality Initiative (K/DOQI) criteria.

Control subjects

Healthy individuals who were matched for sex, age and body mass index (BMI).

Exclusion Criteria:

CKD patients

  • Dialysis treatment
  • Kidney transplant
  • Diagnosis or suspicion of reversible cause of renal failure
  • Clinical conditions that affect body composition, such as cancer, severe liver failure and alcoholism
  • Habitual use of drugs that influence body composition or renal function, such as immunosuppressive or anti-inflammatory drugs
  • Physical amputation
  • Severe obesity (BMI>35)
  • Clinically detectable edema
  • Catabolic conditions.

Control subjects

Heavy physical training; more than one hour of vigorous exercise per day.

Description of Study Protocol:

Recruitment

Patients with CKD were referred to the outpatient renal clinic. Control group subjects were recruited from a previous general population-based study.

Design

Case-control and cross-sectional (partial results) study.

Blinding used

Not described.

Intervention

Not applicable.

Statistical Analysis

  • One-way and two-way analysis of variance
  • Bonferroni post-test was used for pairwise comparison
  • Multiple regression analysis used to evaluate the relationships between BIA and other variables, considering age, weight and CrCl as continuous variables and sex, diabetes and diuretic treatment as categorical variables
  • Bivariate 95% confidence intervals for mean impedance vectors of various groups were calculated, considering the bivariate normal distribution of resistance indexed to height (R/H) and reactance indexed to height (Xc/H)
  • Hoteling's T2 test for unpaired data was used to identify significant differences between impedance vector
  • Two-tailed P<0.05 was considered statistically significant for all test analysis. Data were reported as mean±SD.
Data Collection Summary:

Timing of Measurements

Body composition, anthropometrics and biochemistry were measured one time. Control subjects' measurements were selected from a previous study.

Dependent Variables

  • Fat-free mass (FFM): derived variable from BIA and estimated using the equations proposed by Kotler et al. BIA variables measured were resistance (R), reactance (Xc) and phase angle (phA). R and Xc were considered as such or indexed to height (R/H and Xc/H) for bioelectrical impedance vector analysis. R index was calculated as height2/R (cm2/ohm).
  • Total body water (TBW): derived variable from BIA and estimated by equations
  • Fat mass (FM): estimated as the difference between body weight and FFM
  • Body cell mass (BCM): derived variable from BIA and estimated by equations
  • Albumin
  • Weight (kg)
  • BMI.

Independent Variables

  • CKD stages 3, 4 or 5 vs. control
  • Nutritional status 

Control Variables

  • Creatinine clearance
  • Proteinuria
  • Protein intake
  • Use of diuretics
  • Diabetes
  • Antihypertensive drugs
  • Matching factors: sex, age and BMI.
Description of Actual Data Sample:

Initial N: Patients with CKD=84 (49 male; 35 female); control subjects=604 (298 male; 306 female)

Attrition (final N): Patients with CKD=84 (49 male; 35 female); control subjects=604 (298 male; 306 female) 

Age: Mean age=64 years

Ethnicity: Not mentioned.

Other relevant demographics: Underlying renal diseases were glomerular disease (13%), interstitial nephritis (20%), polycystic kidney disease (7%), diabetes (28%), hypertension (20%), and other or unknown conditions (12%). Patients had mild to severe CKD: 32 in stage 3, 31 in stage 4 and 21 in stage 5. Ninety percent of the patients were taking angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers, alpha-blockers, beta-blockers, and other. Forty-six percent of the patients were receiving diuretic treatment. At the time of enrollment, none of the patients had been prescribed a protein-restricted diet. The CrCl of patient with CKD was 27.8±13.8ml per minute per 1.73m2 for male and 27.4±13.0ml per minute per 1.73m2 for women.

Anthropometrics: In both patients with CKD and control subjects, age, height and weight were slightly different between sexes, whereas the mean BMI was similar.

Location: Naples, Italy.

Summary of Results:

 BIA variables and derived estimates of body composition in patients with CKD and control subjects

Variables

 

Male

 

Female
Patients Controls Patients Controls
R (ohm) 465±81b,c 492±64b 550±80d 574±63
Xc (ohm) 39±9b,c 53±9b 43±11c 58±9
R index (cm2/ohm) 61.5±12.9b,c 57.5±9.2b 43.5±7.9e 41.4±6.3
TBW (L) 41.8±7.3b,d 40.1±5.1b 30.0±4.7e 29.0±3.4
PhA (degrees) 4.84±0.97b,c 6.22±0.93b 4.51±0.98d 5.78±0.8
FFM (kg) 57.3±9.2b,c 55.3±6.5b 41.9±6.9 40.8±4.3
BCM (kg) 26.0±4.3b,c 27.9±3.4b 15.3±2.5c 16.4±2.1
FM (%) 20.3±7.1b,c 23.2±5.1b 30.4±7.3 32.0±6.3

bP<0.05 versus female patients; cP<0.01 vs. controls; dP<0.05 vs. controls; eP=0.06 vs. controls

  • As compared to control subjects, patients with CKD showed overt abnormalities of measured BIA variables
  • Significantly shorter and down-sloping mean impedance vectors were observed in both male and female patients with CKD; P<0.01
  • R index (variable related directly to total body water) was significantly higher in patients with CKD than in control subjects; P<0.01. Twenty-seven percent of men and 20% of women were above the 90th percentile derived in control subjects for R index after adjustment for sex, age and weight.
  • The differences in TBW were similar to those observed for R index, with a higher mean value in patients with CKD than in control subjects; P<0.01. However, when BCM and FM were measured, patients with CKD showed a reduction in both (men -6.7% and women -7.7%; men -12.9% and women -5.0%, respectively); P<0.01.

 

Other Findings

Individual and biochemical characteristics of patients with various CKD stages  (Cross-sectional study results)

Variables CKD 3 CKD 4 CKD 5
BMI (kg) 26.6±4.4 26.1±4.2 25.5±5.3
Albumin (g/dL) 3.88±0.28 3.76±0.36 3.73±0.56
Transferrin (mg/dL) 239±41 238±52 213±53
CrCl (ml/min/1.73m2) 42.2±7.3 23.3±3.5 11.8±2.9 a,b
Protein intake (g/kg/day) 0.88±0.19 0.79±0.19 0.79±0.28

aP<0.05 vs. CKD 3; bP<0.05 vs. CKD 4

  • Only 16 CKD patients had serum albumin less than 3.5g per dL, but none of them had BMI less  than 20. None of the seven underweight patients showed hypoalbuminemia.
  • When patients were compared to the three different stages of CKD, sex, age, BMI and prevalence of diabetes were comparable, as well serum albumin; and did not show differences with other nutritional markers or daily protein
  • R, R index, and Xc were comparable among the three CKD stages. Conversely, compared with control subjects PhA was reduced (P<0.01) in each of the CKD stages.
  • Patients with CKD and diabetes had lower values of R (468±89 vs. 512±89 ohm), Xc (34.8±8.1 vs. 43.2±10.4 ohm), and PhA (4.28±0.81 vs. 4.87±1.00 degrees); P<0.01, than patients with CKD without diabetes
  • Predictors of R were age, weight, and diabetes when simultaneous effects of various variables on BIA were assessed. Predictors of PhA were also age (r=-0.48; P<0.001) and weight (r=0.20; P=0.028), but also included CrCl (r=0.29;P=0.008), diabetes (r=-0.22;P=0.012), and diuretic treatment (r=-0.20; P=0.024)
  • No association was found in the whole CKD group between measured or derived BIA variables and main nutritional parameters, such as serum albumin, transferrin, cholesterol, triglycerides, and protein intake.

 

Author Conclusion:

Despite the absence of overt malnutrition, patients with CKD exhibit altered BIA variables from the early phases of renal disease. These alterations are related to the renal dysfunction, are more marked in the presence of diabetes, and mainly indicate the presence of overhydration in the absence of edema. Therefore, BIA represents an attractive clinical tool to detect impairment of body composition from the early stages of CKD.

Funding Source:
Other: not mentioned
Reviewer Comments:

Some variables, such as age and weight, were different between males and females in both populations. Patients enrolled in the analysis was a subset of "health" CKD population, therefore, the outcomes might be only applicable for this specific set of subjects.

Control subjects and their measurements were selected from a previous study (non-concurrent controls).

Quality Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) N/A
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? Yes
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? Yes
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies) Yes
 
Validity Questions
1. Was the research question clearly stated? Yes
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? Yes
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated? Yes
  1.3. Were the target population and setting specified? Yes
2. Was the selection of study subjects/patients free from bias? Yes
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? Yes
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? Yes
  2.4. Were the subjects/patients a representative sample of the relevant population? No
3. Were study groups comparable? No
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) N/A
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? No
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) No
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? Yes
  3.5. If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) Yes
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? No
4. Was method of handling withdrawals described? N/A
  4.1. Were follow-up methods described and the same for all groups? N/A
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) N/A
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? N/A
  4.4. Were reasons for withdrawals similar across groups? N/A
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study? N/A
5. Was blinding used to prevent introduction of bias? No
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? N/A
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) No
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? ???
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status? ???
  5.5. In diagnostic study, were test results blinded to patient history and other test results? ???
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? N/A
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied? N/A
  6.2. In observational study, were interventions, study settings, and clinicians/provider described? N/A
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? N/A
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? N/A
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described? N/A
  6.6. Were extra or unplanned treatments described? N/A
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? N/A
  6.8. In diagnostic study, were details of test administration and replication sufficient? N/A
7. Were outcomes clearly defined and the measurements valid and reliable? Yes
  7.1. Were primary and secondary endpoints described and relevant to the question? Yes
  7.2. Were nutrition measures appropriate to question and outcomes of concern? Yes
  7.3. Was the period of follow-up long enough for important outcome(s) to occur? N/A
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? Yes
  7.5. Was the measurement of effect at an appropriate level of precision? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? ???
  7.7. Were the measurements conducted consistently across groups? Yes
8. Was the statistical analysis appropriate for the study design and type of outcome indicators? Yes
  8.1. Were statistical analyses adequately described and the results reported appropriately? Yes
  8.2. Were correct statistical tests used and assumptions of test not violated? Yes
  8.3. Were statistics reported with levels of significance and/or confidence intervals? Yes
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? No
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? Yes
  8.6. Was clinical significance as well as statistical significance reported? Yes
  8.7. If negative findings, was a power calculation reported to address type 2 error? N/A
9. Are conclusions supported by results with biases and limitations taken into consideration? ???
  9.1. Is there a discussion of findings? Yes
  9.2. Are biases and study limitations identified and discussed? No
10. Is bias due to study's funding or sponsorship unlikely? ???
  10.1. Were sources of funding and investigators' affiliations described? No
  10.2. Was the study free from apparent conflict of interest? ???