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From the Clinical Research Centers |
Neuroendocrine Unit (S.G., C.C., T.S., A.K.), Infectious Disease Unit (S.D., N.B.), and Radiology (D.R., M.T.) and Physical Therapy Departments (K.P., M.C.), Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114; and the Radiology Department, Boston Veterans Affairs Medical Center and Boston University School of Medicine (B.B.), Boston, Massachusetts 02130
Address all correspondence and requests for reprints to: Steven Grinspoon, M.D., Neuroendocrine Unit, Bulfinch 457B, Massachusetts General Hospital, Boston, Massachusetts 02114.
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Abstract |
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 Top Abstract IntroductionSubjects and MethodsResultsDiscussionReferences |
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Introduction |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Subjects and Methods |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Twenty-four HIV-positive subjects (aged 37 ± 1 yr) were recruited from the multidisciplinary HIV practice at the Massachusetts General Hospital and from advertisements in local newspapers, television, and radio stations from 1997–1998. Weight, testosterone levels, and medication history were determined at a screening assessment. All patients met the following inclusion criteria: 1) free testosterone level more than 42 pmol/L at screening [normal range, 42–112 pmol/L (12.0–35.0 pg/mL) for ages 18–49 yr], and 2) wasting [weight <90% of ideal body weight (IBW) or involuntary weight loss >10% of baseline weight (7)]. Inclusion was not limited based on CD4 count. Patients were excluded with significant diarrhea (>6 stools/day); hemoglobin below 5.0 mmol/L (8 g/dL); platelet count below 50,000 cells/mm3; creatinine more than 177 µmol/L (2 mg/dL); new opportunistic infection within 6 weeks of screening; prior usage of testosterone, anabolic steroids, GH, ketoconazole, or systemic steroid therapy within 3 months of screening; or history of prostate malignancy. None of the patients reported any prior use of GH or anabolic steroids. Three patients had previously received short term testosterone administration, with discontinuation 5, 9, and 24 months before study entry. In addition, patients receiving antiretroviral agents, including protease inhibitors, were required to have been on a stable regimen for at least 6 weeks before study entry. All subjects gave written consent as approved by the human studies committee of the Massachusetts General Hospital.
Protocol
Subjects returned within approximately 2 weeks of the screening visit for a 2-day baseline in-patient visit to the General Clinical Research Center at the Massachusetts General Hospital for hormonal, nutritional, immune function, and body composition analysis, including assessment by dual energy x-ray absorptiometry (DXA), 40K isotope analysis, and urinary creatinine excretion and determination of functional capacity and muscle strength. No subjects experienced the onset of a new opportunistic infection, other complication, or significant weight change between the screening and baseline visits.
Body composition analysis
Whole body and regional fat and lean body mass were assessed by DXA (Hologic-4500 densitometer, Hologic, Inc., Waltham, MA; precision error, 3% for fat and 1.5% for whole body lean mass) (8). Regions of interest, including arms, legs, and trunk, were standardized (QDR-4500 1995 Users Guide, Hologic, Inc.).
Total body potassium was assessed by 60-min counting of the 1.46 keV
-ray emission of endogenous 40K in a whole body counter
with two sodium iodide detectors, one each fixed above and below the
patient at the xiphoid (Canberra Nuclear, Meriden, CT; precision error,
<2.5% based on repeated calibration with a known potassium chloride
source). The total 40K count was corrected for the
simultaneous radon measurement based on regression equations developed
independently for the upper and lower sodium iodide detectors from 68
consecutive analyses performed over a 72-h period on a calibrated
standard. For the upper detector, the change in 40K
attributable to radon was: change in 40K counts =
(0.282 x Rn count at 1765 KeV) + 0.001 (r2 = 0.49;
P < 0.0001). For the lower detector, the change in
40K attributable to radon was: change in 40K
counts = (0.285 x Rn count at 1765 KeV) + 0.001
(r2 = 0.75; P < 0.0001). The
40K count at each detector for each scan was summed to
obtain the total 40K count. Total body potassium was
derived from a constant of 95 g potassium/13,800 counts potassium
determined in a calibrated phantom. Body cell mass was derived from
total body potassium based on the equation of Forbes et al.
of 68.1 meq K/kg lean body mass (9).
Twenty-four-hour excretion of urinary creatinine was determined while the subject was consuming a meat-free diet, multiplied by a constant of 18 kg muscle/g urinary creatinine and indexed for height to determine the percentage of predicted muscle mass (10, 11).
The cross-sectional area of the muscles of the arm and leg were
determined by computed tomography (CT) scan (General Electric RP High
Speed Helical CT Scanner, Milwaukee, WI; Fig. 1
). The midpoints of the left
humerus and femur were obtained from measurements from a scout image
obtained with the extremities in a standard position. The arm was held
in external rotation and supported at the elbow to avoid compression of
the soft tissues. The leg was scanned with the knee fully extended and
the foot perpendicular to the CT table. Single 10-mm thick axial images
(arm, 120 kVp, 200 mA, 2-s scan time; leg, 120 kVp, 170 mA, 2-s scan
time) were obtained. Using graphical analysis software provided by the
scanner manufacturer (General Electric Advantage Windows Workstation
version 2.0, General Electric Corp., Milwaukee, WI), contours
were traced manually around the extremity circumference and around the
anterior and posterior muscle groups. Cross-sectional area was recorded
for each compartment and summed for total cross-sectional muscle area.
All measurements were made in duplicate. The SE of the
measurement was calculated as the SD of the difference
between the first and second measurements for each patient, divided by
the mean measurement. The SE of the arm muscle area was
±3%, and that for the leg muscle was ±1%.
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Weight was determined after an overnight fast. The percent IBW was calculated based on standard height and weight tables (12). Subjects were instructed on the completion of a 4-day food record, which was analyzed for total calorie, fat, protein, and carbohydrate content (version 8A/2.6, Minnesota Nutrition Data Systems, Minneapolis, MN) by the Clinical Research Center dietitian. Subjects received an isocaloric, meat-free, protein-substituted diet 3 days before and during the in-patient assessment, during which creatinine excretion was determined. Calorie and protein intakes were monitored on a daily basis and modified to match those reported in the out-patient food records immediately before the visit.
Functional status and exercise functional testing
Overall functional status was determined by Karnofsky score (13). Exercise history was assessed by a standardized questionnaire adapted from that developed by Kohl et al. (14). Exercise functional status was determined by the Physical Therapy Department of the Massachusetts General Hospital using the 6-min walk test (distance walked in 6 min) as an index of overall functional and aerobic capacity (15). Upper and lower extremity muscle strengths were determined by the quantitative muscular function test (QMT). The testing procedure, a component of the Tufts quantitative neuromuscular examination, is highly precise for the determination of isometric strength (test-retest correlation, r = 0.96–0.98) and has been validated in normal control and disease subjects (16, 17). The peak isometric force of 1) shoulder flexion, 2) shoulder extension, 3) elbow flexion, 4) elbow extension, 5) knee flexion, and 6) knee extension was measured through an electronic strain gauge tensiometer on the best of two repetitions (17, 18). Positioning of the patient and limbs were standardized (18). The z-scores were determined for each category (MVCT Computer Analysis Software, Boston, MA) by subtracting an individual’s raw score from an established mean in healthy control male subjects and dividing by the SD of the control measurement (16). Upper and lower extremity mega z-scores were determined by averaging z-scores for shoulder flexion, shoulder extension, elbow flexion and elbow extension (upper extremity), and knee flexion and extension (lower extremity) (18).
Biochemical and immunological assays
Serum hematocrit was measured using published methods (19). Serum total and free testosterone were measured by RIA kit (Diagnostics Products Corp., Los Angeles, CA), with intraassay coefficients of variation of 5–12% for total testosterone and 3.2–4.3% for free testosterone. CD4 cell counts were measured by flow cytometry (Becton Dickinson Immunocytochemistry Systems, San Jose CA). Viral load was determined using the Amplicor HIV-1 Monitor Test (Roche Molecular Systems, Branchburg, NJ).
Statistical analysis
Body composition indexes, muscle size, muscle strength, and functional capacity were compared by univariate regression analysis using JMP for SAS (SAS Institute, Cary, NC). Forward selection stepwise regression analysis was performed for Karnofsky score and regional muscle strength, using P = 0.05 for entry into the model. Muscle mass, hemoglobin, CD4, viral load, body mass index (BMI), cross-sectional muscle area, exercise performance status, lean body mass, and body cell mass were tested as covariates for inclusion in the model for Karnofsky score, whereas muscle mass, lean body mass, body cell mass, muscle area, and weight were tested for inclusion in the model of regional muscle strength.
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Results |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Subjects were 37 ± 1 yr of age and weighed 95.5 ±
3.0% of IBW with a BMI of 21.9 ± 0.7 kg/m2 and an
average weight loss of 15 ± 1%. The subjects demonstrated 90%
of the expected muscle mass by the creatinine height index method. The
mean CD4 count was 354 ± 70 cells/mm3 and viral load
was 58,561 ± 32,205 copies among the subjects (Table 1). Sixty-two percent of the subjects
were receiving protease inhibitor therapy, with an average
duration of therapy of 8 ± 2 months.
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The total cross-sectional muscle areas of the lower and upper
extremities, biceps, and quadriceps are shown in Table 1
. Quadriceps
size was reduced in comparison with normative data previously published
in age-matched men (74.9 ± 15.9 vs. 95.1 ± 13.2
cm2, mean ± SD; P <
0.0001) (6).
Performance status
Overall performance status on the Karnofsky scale was highly
correlated with weight (r = 0.51; P = 0.018; by
BMI), lean body mass (r = 0.46; P = 0.036; by
DXA), and body cell mass (r = 0.47; P = 0.037; by
40K isotope analysis) and tended to correlate inversely
with viral load (r = -0.41; P = 0.073), but not
CD4 count (Table 2). In a stepwise
regression model, the cross-sectional muscle area of the upper
extremity (UE) was the best predictor of performance status
(P < 0.001), accounting for 52% of the variability in
the Karnofsky score. Weight, lean body mass, body cell mass, CD4, and
viral load were not independent predictors of Karnofsky score in the
model. Exercise history did not correlate with performance status, body
composition, or muscle strength. The final equation for the model is:
Karnofsky score = 80.0 + 0.43 x UE cross-sectional muscle
area (cm2) (r2 = 0.52).
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Biceps and quadriceps areas were highly correlated with and
predictive of strength on elbow and knee flexion, respectively, in
univariate and stepwise regression analyses. The univariate regression
equations relating muscle size and function are shown below: strength
of knee extension (Newtons) = 71.5 + 3.7 x quadriceps area
(cm2) (r2 = 0.49; P < 0.001)
(Fig. 1); and strength of elbow flexion (Newtons) = 67.7 + 7.6 x
biceps area (cm2) (r2 = 0.37; P
< 0.01).
Muscle strength of the lower extremity determined by composite score on
QMT testing (knee extension and flexion) was significantly correlated
with weight, lean body mass, body cell mass, and muscle area in a
univariate regression analysis (Table 2). In a stepwise regression
model, lower extremity (LE) cross-sectional muscle area was the best
predictive factor of lower body strength (r2 = 0.70;
P < 0.0001). Weight, lean body mass, and body cell
mass were not independent predictors of lower extremity muscle
strength. The final equation for the model is shown below: QMT
composite score (LE) = -3.6 + 0.02 x LE cross-sectional muscle
area (cm2) (r2 = 0.70).
Muscle strength of the upper extremity determined by composite score on
QMT testing (shoulder flexion, shoulder extension, elbow flexion, and
elbow extension) was correlated significantly with weight, lean body
mass, body cell mass, and muscle area in a univariate regression
analysis (Table 2). In a stepwise regression model, lean body mass
(LBM) determined by DXA was the best predictive factor of overall upper
body strength (r2 = 0.78; P < 0.0001). The
final equation for the model is shown below: QMT composite score (UE) =
-6.8 + 0.06 x LBM (kg) + 0.12 x BMI (kg/m2)
(r2 = 0.78).
Exercise functional capacity
Performance on the 6-min walk test was correlated significantly
with lower extremity muscle area, lean body mass, and body cell mass
(Table 2). In a stepwise regression model, lower extremity
cross-sectional muscle area was most predictive of performance on the
6-min walk test (r2 = 0.26; P = 0.030).
Weight, lean body mass, and body cell mass were not independent
predictors of performance on the 6-min walk test. The final equation
for the model is shown below: 6-min walk (feet) = 636 + 11.6 x LE
cross-sectional muscle area (cm2) (r2 =
0.26).
Comparison of body composition indexes by protease inhibitor status
No differences in weight, CD4, weight loss, or exercise history
were observed among patients receiving protease inhibitor therapy
compared to those not receiving this treatment. In contrast, viral load
was lower in patients receiving protease inhibitor therapy
(141,369 ± 78,381 vs. 7,603 ± 4,358 copies;
P = 0.04). A trend toward reduced regional fat in the
arm area in the protease inhibitor-treated vs. the
nontreated patients was demonstrated by DXA (P = 0.056;
Table 1). No other differences in whole or regional body composition
were seen.
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Discussion |
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TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
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Significant sarcopenia was demonstrated in the study subjects. Kotler et al. have previously demonstrated the significant and disproportionate loss of body cell mass among men with AWS (1, 2). The loss of body cell mass is a predictor of reduced survival (22) and has generally been assumed to be the causal factor of increased fatigue and decreased functional and performance status among such patients. In this study, subjects weighed 95% of IBW, but demonstrated only 90% of predicted muscle mass using the creatinine height index. In addition, comparison of cross-sectional quadriceps area with normative data from healthy age-matched men suggests a 20% reduction in regional muscle mass (5). Of importance, all of the patients in this study were eugonadal based on a normal screening free testosterone level, such that the changes in muscle mass could not be attributed to hypogonadism (23). Furthermore, muscle mass was significantly and comparably reduced among the subset of patients receiving protease inhibitor therapy.
We investigated the relationship between regional muscle mass and performance status, as assessed by Karnofsky score. The cross-sectional muscle area of the upper extremity was the best predictive factor of Karnofsky score in a stepwise regression analysis. In contrast, weight, body cell mass, and immune function were not independent predictors of functional status in the regression model. These data are the first to suggest that regional muscle mass may be an important factor in overall functional status in men with AIDS wasting. Although it is hypothesized that increased regional muscle mass may allow better performance of daily activities with less fatigue, the specific relationship between regional muscle mass and overall performance status is not known. Furthermore, the finding that upper extremity cross-sectional muscle area is the primary determinant of performance status may be unique to patients with AIDS wasting or may be related to the methods of muscle mass and functionality assessment in this study. Further studies investigating the effects of regional muscle mass on overall performance status are needed.
Regional muscle mass was also compared with muscle strength of individual muscle groups and overall composite scores of the upper and lower extremities. A significant relationship between regional muscle mass and strength was observed. For example, the cross-sectional muscle area of the lower extremity was the single best predictive factor for lower extremity muscle function testing and performance on the 6-min walk test. Total body lean body mass was the most predictive of overall upper extremity muscle function, a composite score of various muscle groups. Of note, a significant correlation between muscle area and strength has been established for healthy young and older patients and in disease states such as congestive heart failure (6, 24). The highly significant correlation (r = 0.7; P < 0.001) between quadriceps area and force of knee extension among subjects with AIDS wasting in this study is comparable to that seen in healthy men (6). These data demonstrate that a significant relationship between muscle size and function is observed in men with AIDS wasting as in other populations. The slope of the regression equation of quadriceps size and strength was 3.7 in our patients compared to 5.7 in a younger (28 vs. 37 yr) population of healthy patients reported by Maughan et al., potentially suggesting less strength per unit of existing muscle (6). However, a definitive comparison of the relationship between muscle size and function in age-matched HIV vs. healthy populations is not possible from our experimental paradigm, and further studies are needed to assess the relative strength of muscle in men with AIDS wasting.
Recent reports indicate increased fat mass among patients receiving protease inhibitors, the etiology of which is unclear (25, 26, 27). We compared indexes of body composition and regional fat mass between subjects receiving or not receiving protease inhibitors. Overall fat mass in the arms tended to be less in the protease inhibitor-treated patients compared to that in the nontreated patients, but patients receiving protease inhibitor therapy tended to have less, not more, fat at all sites. Similarly, no differences in regional lean mass by DXA were observed based on protease inhibitor status. The number of patients studied was not, however, sufficient to draw a definitive conclusion regarding the body composition effects of protease inhibitors in men with AIDS wasting. Furthermore, changes in body composition may be a late stage phenomenon among protease inhibitor-treated men with AIDS, and the average duration of protease inhibitor usage in this study may have been insufficient to produce changes in body composition. Finally, the effects of protease inhibitors on body composition may be different among men with AWS who have lost significant weight compared to those in HIV-positive subjects without an initial weight loss. Although our data suggest no significant changes in fat redistribution by protease status, prospective studies are needed to explore this issue.
The need to increase lean body mass is considered critical among men with AWS. Our data provide further evidence of generalized and regional sarcopenia in men with AWS, a large proportion of whom were receiving protease inhibitor therapy. Furthermore, these are the first data to demonstrate that regional muscle mass, as assessed by CT scanning of cross-sectional muscle area, is highly predictive of overall functional status, regional muscle strength, and exercise performance among men with AWS. In contrast, more global measures of overall muscle strength are best predicted by whole body lean body mass. Our data support a rationale for strategies that build regional, in addition to whole body, muscle mass in men with AWS. In this regard, exercise and strength-training programs may be valuable adjunctive strategies to increase functional status. Further research into the efficacy of combined anabolic strategies to build regional muscle mass and improve functional status in men and women with AWS is needed.
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Acknowledgments |
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Footnotes |
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Received August 14, 1998.
Revised September 21, 1998.
Accepted September 30, 1998.
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