Share this article on:

00002030-200511040-0000900002030_2005_19_1807_dube_antiretroviral_16article< 138_0_18_9 >AIDS© 2005 Lippincott Williams & Wilkins, Inc.Volume 19(16)4 November 2005p 1807–1818Glucose metabolism, lipid, and body fat changes in antiretroviral-naive subjects randomized to nelfinavir or efavirenz plus dual nucleosides[CLINICAL SCIENCE]Dubé, Michael Pa; Parker, Robert Ab; Tebas, Pablof; Grinspoon, Steven Kc; Zackin, Robert Ab,*; Robbins, Gregory Kd; Roubenoff, Ronenne; Shafer, Robert Wg; Wininger, David Ah; Meyer, William A IIIi; Snyder, Sally Wj; Mulligan, KathleenkFrom the aDivision of Infectious Diseases, Indiana University, Indianapolis, IndianabStatistical and Data Analysis Center, Harvard School of Public HealthcDivision of NutritiondDivision of Infectious Diseases, Harvard UniversityeFriedman School of Nutrition Science and Policy, Tufts University, Boston, MassachusettsfDivision of Infectious Diseases, University of Pennsylvania, Philadelphia, PennsylvaniagDivision of Infectious Diseases, Stanford University, Palo Alto, CaliforniahDivision of Infectious Diseases, Ohio State University, Columbus, OhioiQuest Diagnostics Incorporated, BaltimorejSocial & Scientific Systems Inc, Silver Spring, MarylandkDivision of Endocrinology, University of California at San Francisco, San Francisco, California, USA.* Deceased.Received 18 January, 2005Revised 20 March, 2005Accepted 5 April, 2005Correspondence to Dr M.P. Dubé, Wishard Memorial Hospital, 1001 W 10th St, Suite OPW-430, Indianapolis, IN 46202, USA. Email: mpdube@iupui.eduAbstractObjective: To determine if particular components of antiretroviral drug regimens are associated with greater insulin resistance, dyslipidemia, and peripheral lipoatrophy.Methods: Metabolic and body composition variables were measured prospectively over 64 weeks in 334 antiretroviral-naive, HIV-infected subjects who were randomized to receive nelfinavir, efavirenz, or both, combined with zidovudine/lamivudine or didanosine/stavudine in a factorial design, multicenter trial. Subjects assigned to efavirenz (n = 110) were compared with those assigned to nelfinavir (n = 99); subjects assigned to zidovudine/lamivudine (n = 154) were compared with those assigned to didanosine/stavudine (n = 180). A subset of 157 subjects had serial dual-energy X-ray absorptiometry (DEXA) scans.Results: Lipid measures increased in all groups. Greater increases in high density lipoprotein (HDL) cholesterol occurred with efavirenz than with nelfinavir. Greater increases in total cholesterol, non-HDL cholesterol and HDL cholesterol occurred with stavudine and didanosine than with zidovudine/lamivudine. There were no differences in insulin resistance in the comparisons. After initial increases in the first 16 weeks, median limb fat decreased. Greater changes in percentage changes in limb fat occurred with didanosine/stavudine (−16.8%) than with zidovudine/lamivudine (+4.0%; P < 0.001 for overall change from baseline) and with nelfinavir (−13.1%) compared with efavirenz (+1.8%; P = 0.003).Conclusions: Over 64 weeks, all regimens were associated with increases in lipids but insulin resistance did not differ between groups. Regimens containing didanosine/stavudine and regimens containing nelfinavir were associated with greater loss of limb fat.IntroductionTreatment of HIV infection with combination antiretroviral therapy is associated with disorders of glucose and lipid metabolism [1–10] and of body fat distribution [3,9,11–13]. The relative contribution of protease inhibitors, non-nucleoside reverse transcriptase inhibitors (NNRTI), and nucleoside reverse transcriptase inhibitors (NRTI) to the development of these abnormalities is not fully understood.The present study was a prospective analysis of subjects who were naive to antiretroviral drugs and was a substudy of a large randomized antiretroviral drug trial [AIDS Clinical Trials Group (ACTG) Study 384] [14,15]. This study has demonstrated that regimens containing didanosine (ddI) plus stavudine (d4T) had high rates of peripheral neuropathy and laboratory toxicities. Another major finding was that the potency of an antiretroviral drug varied depending on the other drugs in the regimen. Among the three-drug regimens evaluated in ACTG 384, an initial regimen containing efavirenz was superior to nelfinavir when combined with the dual NRTI combination of zidovudine (ZDV)/lamivudine(3TC) (but not ddI/d4T). Starting with ZDV/3TC was superior to ddI/d4T when combined with efavirenz but not with nelfinavir [14]. The four-drug regimens that included both nelfinavir and efavirenz combined with dual NNRTI were similar in efficacy and were no better than the best of the three-drug combinations: ZDV/3TC and efavirenz [15].Initial reports from cross-sectional studies implicated protease inhibitors as causal in the morphological and metabolic complications of antiretroviral therapy [3]. Therefore, our primary hypothesis was that use of the protease inhibitor nelfinavir, compared with the NNRTI efavirenz, would be associated with greater insulin resistance, dyslipidemia, central obesity, and peripheral lipoatrophy.MethodsSubjectsHIV-infected individuals were eligible for entry into ACTG 384 [14,15] if they had < 7 days prior antiretroviral experience and HIV-1 RNA > 500 copies/ml. This substudy, A5005s, enrolled a total of 334 of the 980 ACTG 384 subjects at 23 participating sites in the United States from 1998 to 1999; study follow-up continued through 2001. Subjects were excluded from this substudy if they had uncontrolled hypogonadism, were receiving supraphysiological doses of androgens or glucocorticoids, had serum triglycerides > 750 mg/dl, or had any history of Cushing disease or diabetes mellitus. Subjects were not excluded if they took lipid-lowering drugs. Two subjects were taking lipid-lowering drugs at entry. All subjects provided written informed consent based on the guidelines of each site's Institutional Review Board.Drug treatmentSubjects were randomized to one of six treatment arms using a factorial design to receive nelfinavir, efavirenz, or both drugs, in a blinded fashion, combined with open-label ZDV/3TC or ddI/d4T [14,15] (Figure 1). Dosage of ddI was 400 mg (250 mg if < 60 kg body weight) once daily; d4T was 40 mg (30 mg if < 60 kg) twice daily; 3TC was 150 mg twice daily; and ZDV was 300 mg twice daily. Efavirenz and nelfinavir were double-blinded via matching placebos: efavirenz 600 mg once at night and nelfinavir 1250 mg twice daily. Subjects with intolerance to ZDV or ddI were allowed to switch to d4T or 3TC, respectively, while continuing the remainder of the originally assigned regimen. Subjects assigned to a three-drug regimen who experienced failure for virological or toxicity reasons were switched twice: from the originally assigned nelfinavir or efavirenz to the other drug, and, simultaneously, from the originally assigned NRTI to the other pair. Subjects assigned to a three-drug regimen who experienced failure of the second three-drug regimen, and those assigned to a four-drug regimen who experienced failure for virological or toxicity reasons, had reached a primary study endpoint and subsequently received salvage therapy. Further details are available elsewhere [14,15].Fig. 1. Study design. For the primary analyses, comparisons between the nelfinavir- and efavirenz-containing regimens were pooled across both NRTI groups (the nelfinavir plus efavirenz group was not included in these analyses) and comparisons between the regimens containing zidovudine/lamivudine or didanosine/stavudine were pooled across all three PI/NNRTI groups. Numbers represent the numbers in each initial treatment group. PI, protease inhibitor; NNRTI, non-nucleoside reverse transcriptase inhibitor; NRTI, nucleoside reverse transcriptase inhibitor.EvaluationsSubjects underwent fasting venipuncture collections at entry and at 8 and 16 weeks, then every 16 weeks thereafter.AssaysAssays through week 64 were performed at Quest Diagnostics Incorporated (Baltimore Maryland, USA) on specimens stored at −70°C. Plasma glucose concentrations were measured on specimens stored in sodium fluoride–potassium oxalate using a hexokinase technique. Plasma insulin concentration was measured on heparinized specimens by a two-site chemiluminescent enzyme-labeled immunometric assay using a technique insensitive to proinsulin (DPC Immulite 2000; Quest Diagnostics). Total cholesterol, high density lipoprotein (HDL) cholesterol, and triglycerides were measured using enzymatic techniques. Low density lipoprotein (LDL) cholesterol was calculated by the Friedewald equation [16]. Non-HDL cholesterol was calculated as total cholesterol minus HDL cholesterol.Results are given in non-SI units: to convert glucose as mg/dl to mmol/l, multiply by 0.0555; to convert insulin values from mU/ml to pmol/l, multiply by 7.175; to convert C-peptide from ng/ml to nmol/l, multiply by 0.33; to convert cholesterol from mg/dl to mmol/l multiply by 0.0259; to convert triglycerides from mg/dl to mmol/l multiply by 0.0113.Dual-energy X-ray absorptiometry scansWhole-body scans were performed on a subset of subjects at 18 sites at entry and every 16 weeks thereafter. Sites participating in the dual-energy X-ray absorptiometry (DEXA) scan substudy offered participation in this part of the trial as an additional option to any eligible subject. Regional analysis was performed centrally at Tufts University by one of the authors (R. Roubenoff), who was unaware of treatment assignment. A standard phantom was scanned at each site with each scanner used in the study. The same scanner at one site was used for all evaluations on any individual subject where possible. Total limb fat was the sum of arm and leg fat mass.Statistical analysesThe primary endpoints of the study were changes from baseline in measures of glucose metabolism by the homeostasis model assessment-insulin resistance (HOMA-IR) method [17] and lipid metabolism (total, HDL, and LDL cholesterol and triglycerides). HOMA-IR was chosen as the primary glucose metabolism measure during study design because of its requirement for only fasting measurements, its applicability to large studies [18], its good correlation with hyperinsulinemic clamp-derived measures of insulin resistance [19], and its superiority to simple fasting insulin for this purpose. The primary objective was to compare the results with the nelfinavir- and efavirenz-containing regimens (pooling across both NRTI groups), in order to isolate the effects of a protease inhibitor-based regimen compared with an NNRTI-based regimen. Subjects randomized to both nelfinavir plus efavirenz were, therefore, not included in these primary analyses. Secondary objectives included comparing regimens containing ZDV/3TC with those with ddI/d4T (pooling across all three protease inhibitor and/or NNRTI groups) (Figure 1). Analyses were limited to the first 64 weeks of study, a period which was chosen to coincide with the available metabolic data. This was also considered reasonable because of a greater frequency of treatment arm switches after week 64. Preplanned primary analyses were intent-to-treat, based on initial treatment group assignments. Secondary analyses included on-treatment analyses with censoring at the time of a regimen change (metabolic endpoints) or 28 days after a regimen change (DEXA endpoints), where a regimen change involved switching both the administered protease inhibitor/NNRTI and the NRTI drugs at the same time. The study was powered to detect a 50 mg/dl difference in fasting triglyceride concentrations between the efavirenz and nelfinavir groups with αP = 0.05 and βP = 0.80.Baseline variables were compared between groups using the Wilcoxon rank sum test (continuous data) or contingency table methods for categorical variables. Changes over time were assessed within groups using the Wilcoxon signed rank test. Mixed models analysis of variance (MMANOVA) was used to assess the overall pattern of changes over time. Missing data were not imputed because MMANOVA does not require complete data on each participant. This analysis adjusted for time trend and utilized a heterogeneous Toeplitz correlation structure between measurements within a participant. This structure allows for different variances for each time point and does not impose a structure on how the correlation between measurements changes as the interval between the measurements increases. For comparisons between groups, our model adjusted for time trend, treatment group, and a time × treatment group interaction. P values were adjusted for baseline values if there was evidence that the baseline value might be important (P < 0.10 in the final model). Absolute change from baseline was analyzed for metabolic parameters and percentage change from baseline for DEXA measurements. MMANOVA allowing for the protease inhibitor/NNRTI group assignment, the NRTI group assignment, and a potential interaction between the two was done to ensure that conclusions about one treatment were robust to the other treatment effect. Such analyses excluded subjects on combined efavirenz and nelfinavir and reduced the power to detect a difference between the ZDV/3TC and the ddI/d4T groups. Logistic regression was used to assess the effect of treatment group on occurrence of lipoatrophy at week 64 after adjustment for potential baseline predictors specified in the analysis plan. All analyses were performed using SAS release 8.02 (SAS Institute, Cary, North Carolina, USA).ResultsBaseline demographic, clinical and laboratory features are shown in Tables 1 and 2 and the randomization protocol in Fig. 1. Up until the week 64 visit, 18% of subjects switched from efavirenz to nelfinavir and 43% switched from nelfinavir to efavirenz; 23% switched from ZDV/3TC to ddI/d4T, and 28% made the opposite switch.Table 1. Baseline data for protease inhibitor (nelfinavir) versus non-nucleoside reverse transcriptase inhibitor (efavirenz) assignment.Table 2. Baseline data for nucleoside reverse transcriptase inhibitor assignment: didanosine plus stavudine verus zidovudine plus lamivudine.Glucose metabolismNo significant differences were found between groups at baseline. Figure 2 shows the median change from baseline in HOMA-IR over 64 weeks of study. No significant between-groups changes occurred. A modest 10% increase from baseline in HOMA-IR occurred in the study population as a whole at week 64 (MMANOVA P = 0.03 for trend over time).Fig. 2. Median changes from baseline in fasting homeostasis model assessment–insulin resistance (HOMA-IR) by treatment assignment. Numbers are paired data from baseline and at that time point. MMANOVA, mixed models analysis of variance; NFV, nelfinavir; EFV, efavirenz; ZDV, zidovudine; 3TC, lamivudine; ddI, didanosine; d4T, stavudine.Lipid metabolismMedian baseline cholesterol tended to be higher in the nelfinavir group (Table 1; 169 versus 158 mg/dl with efavirenz; P = 0.08). As shown in Fig. 3a, median increases in total cholesterol, triglycerides, and non-HDL cholesterol were similar for nelfinavir and efavirenz, but there were greater increases in HDL cholesterol with efavirenz (MMANOVA P = 0.005), which resulted in a lower total:HDL cholesterol ratio (data not shown). There were no between-arm differences in the proportion of subjects at week 64 with total cholesterol > 200 mg/dl, LDL cholesterol > 130 mg/dl, or triglycerides > 200 mg/dl (data not shown). One subject assigned to nelfinavir and four subjects assigned to efavirenz started lipid-lowering drugs during the 64 weeks.Fig. 3. Median changes in fasting lipids depending on therapy. (a) Comparison of a protease inhibitor (nelfinavir) with a non-nucleoside reverse transcriptase inhibitor (efavirenz). (b) Comparison of nucleoside reverse transcriptase inhibitors (didanosine/stavudine compared with zidovudine/lamivudine). Numbers represent paired data from baseline and at that time point. To convert cholesterol from mg/dl to mmol/l multiply by 0.0259; to convert triglycerides from mg/dl to mmol/l multiply by 0.0113; HDL, high density lipoprotein; MMANOVA, mixed models analysis of variance; NFV, nelfinavir; EFV, efavirenz; ZDV, zidovudine; 3TC, lamivudine; ddI, didanosine; d4T, stavudine.Fig. 3. (continued)Greater increases in total, HDL, and non-HDL cholesterol were seen with ddI/d4T compared with ZDV/3TC, while triglycerides were similar (Fig. 3b). There was no evidence for an interaction of the effect of nelfinavir or efavirenz assignment with the effect of the NRTI assignment for any glucose or lipid outcome. There were no between-arm differences in the proportion of subjects at week 64 with total cholesterol > 200 mg/dl, LDL cholesterol > 130 mg/dl, or triglycerides > 200 mg/dl (data not shown). Four subjects assigned to ddI/d4T and six assigned to ZDV/3TC started lipid-lowering drugs during the 64 weeks.Dual-energy X-ray absorptiometry scansSubjects who had DEXA scans had similar baseline characteristics compared with the whole study population (data not shown).Data for 157 subjects who participated in the DEXA substudy are shown in Tables 3 and 4. Limb fat increased initially and tended to peak at week 16; it then tended to decrease thereafter (Fig. 4). With ddI/d4T, limb fat decreased by 16.8% [interquartile range (IQR), −34.0 to 11.0] from baseline at week 64 (P = 0.009 for within-group change). At weeks 48 and 64, subjects assigned to ddI/d4T had significantly greater loss of limb fat than those assigned to ZDV/3TC, and the overall difference was highly significant (MMANOVA, P < 0.001). When analyzed by subjects who remained on their original treatment arm assignment, the association of limb fat loss with ddI/d4T use remained (MMANOVA, P < 0.001). Using logistic regression modeling to predict limb fat loss of at least 10% from baseline, the effect of NRTI drug pair assignment was significant after adjustment for age, sex, race/ethnicity, baseline body mass index (BMI), log HIV RNA, and CD4 cell count. After adjustment for these six factors, subjects assigned to ddI/d4T were 3.3 times as likely to have a limb fat loss of > 10% than were subjects on ZDV/3TC (95% confidence interval, 1.2 to 8.6; P = 0.02).Table 3. Baseline and on-treatment dual-energy X-ray absorptiometry (DEXA) scans, based on initial treatment assignment for protease inhibitor (nelfinavir) or non-nucleoside reverse transcriptase inhibitor (efavirenz)a.Table 4. Baseline and on-treatment dual-energy X-ray absorptiometry (DEXA) scans based on initial treatment assignment for nucleoside reverse transcriptase inhibitor (didanosine plus stavudine or zidovudine plus lamivudine)a.Fig. 4. Median percentage change in limb fat and trunk fat estimated by dual-energy X-ray absorptiometry (DEXA) scans over 64 weeks of antiretroviral therapy. (a) Comparison of a protease inhibitor (nelfinavir) with a non-nucleoside reverse transcriptase inhibitor (efavirenz). (b) Comparison of nucleoside reverse transcriptase inhibitors (didanosine/stavudine and zidovudine/lamivudine). Numbers represent paired data from baseline and at that time point. MMANOVA, mixed models analysis of variance; NFV, nelfinavir; EFV, efavirenz; ZDV, zidovudine; 3TC, lamivudine; ddI, didanosine; d4T, stavudine.At week 64, subjects assigned to nelfinavir had lost 13.1% (IQR, −30.2 to 6.1) of limb fat from baseline compared with an increase of 1.8% (IQR −21.2 to 31.1) with efavirenz. The time pattern was significantly different between groups (MMANOVA, P = 0.003). When the analysis was limited only to those subjects remaining on their original treatment arm assignment, the limb fat loss with nelfinavir was similar in magnitude but did not achieve statistical significance (MMANOVA, P = 0.053). Using logistic regression modeling to predict limb fat loss of at least 10% from baseline, after adjustment for age, sex, race/ethnicity, baseline BMI, log HIV RNA, CD4 cell count, and NRTI assignment, there was some evidence that the effect of assignment to nelfinavir or efavirenz on the percentage change in limb fat from baseline was important (P = 0.06).Trunk fat (Fig. 4 and Tables 3 and 4) tended to increase in all groups. There were differences in the pattern of trunk fat increases over time with ZDV/3TC compared with ddI/d4T (MMANOVA P = 0.01) and with efavirenz compared with nelfinavir (MMANOVA P = 0.03), as well as for the pattern of total body fat (MMANOVA P = 0.004 and P = 0.003, respectively). There was no evidence of an interaction of the effect of nelfinavir or efavirenz assignment with the effect of the NRTI assignment for any DEXA outcomes.DiscussionThis prospective metabolic and body composition study nested in a large randomized trial of potent antiretroviral regimens demonstrates clear differences between the tendency of particular antiretroviral drug-containing regimens to induce limb fat loss compared with baseline measurements. When combined with a protease inhibitor (nelfinavir), an NNRTI (efavirenz), or both, assignment to the combination of ddI/d4T was associated with greater loss of limb fat than was the combination of ZDV/3TC. When combined with dual NRTI, assignment to the protease inhibitor nelfinavir was associated with greater loss of limb fat than was the NNRTI efavirenz, although the magnitude of the difference was smaller than that with the NRTI drugs and the on-treatment analysis did not reach statistical significance. Contrary to our expectations, use of nelfinavir in combination with a pair of NRTI did not induce greater insulin resistance or dyslipidemia than use of efavirenz.The use of antiretroviral therapy that includes protease inhibitors has been associated with new-onset diabetes mellitus [1,2,20] and insulin resistance [3–5,7,21,22]. However, indinavir is the only protease inhibitor clearly associated with early (within 8 weeks or less) reduction of insulin sensitivity [21–23], likely in part via inhibition of the function of the insulin-sensitive glucose transporter GLUT4 [24,25]. There is human clinical evidence that amprenavir [26] and atazanavir [27,28] do not cause early insulin resistance, while conflicting data exist for lopinavir–ritonavir [28,29]. There was no evidence of an effect on insulin sensitivity in this study with nelfinavir at 8 weeks, suggesting that an early, direct effect on insulin resistance also does not occur with this particular protease inhibitor.Lipid measures, including total and non-HDL cholesterol and triglycerides, increased comparably with both nelfinavir- and efavirenz-based treatment. Similar results have been presented in another preliminary report [30]. Of note were the substantial increases in HDL cholesterol with both treatments (median increase of 5–7 mg/dl, or approximately 20–25%). With efavirenz, there was a modest advantage in HDL cholesterol, resulting in a more favorable total cholesterol to HDL cholesterol ratio, suggesting lesser cardiovascular risk [31]. Non-HDL cholesterol, a risk marker that may be more predictive than LDL cholesterol for cardiovascular events [32], increased comparably by approximately 25 mg/dl in both groups. The net effect of these changes on long-term cardiovascular risk in patients with HIV is unknown.Protease inhibitors may contribute to an increased risk of lipoatrophy when administered with an NRTI. In a descriptive cohort study, dual NRTI therapy plus a protease inhibitor was associated with a more rapid time to fat wasting than was dual NRTI alone [33]. Moreover, as compared with time on nevirapine, cumulative time on protease inhibitors was associated with an increased risk of fat wasting, suggesting that protease inhibitors may accelerate the fat wasting effects of NRTI drugs [33]. When not administered with NRTI agents, the incidence of lipoatrophy with the protease inhibitor combination ritonavir plus saquinavir was low [34]. In the present study, we report evidence from a prospective, randomized trial of an independent effect of assignment to the protease inhibitor nelfinavir on limb fat loss, albeit an effect smaller in magnitude than the effect of assignment to ddI/d4T. Our findings are consistent with in vitro studies in which certain protease inhibitors, including nelfinavir, have been shown to inhibit adipocyte differentiation [35–37]. These results, however, may not be generalizable to all protease inhibitors. The on-treatment analysis was limited by a high frequency of treatment switching, reducing the number of subjects observed. We feel that, because lipoatrophy represents a cumulative toxicity, the on-treatment analysis (which censors subjects after a treatment arm change) is less valuable than our primary, intent-to-treat analysis.Randomization to ddI/d4T led to a greater loss of limb fat than did ZDV/3TC. A secondary analysis that censored subjects at the time of regimen changes was also statistically significant, and there was no evidence for interaction between treatment group assignments. Many studies have linked d4T use with lipoatrophy [13,33,38,39] and substitution of other NRTI for d4T has improved lipoatrophy [40–42]. A randomized trial that compared d4T or tenofovir in combination with 3TC and efavirenz reported greater limb fat by DEXA among tenofovir recipients at weeks 96 and 144, but did not include baseline DEXA measurements [39] and so could not evaluate the longitudinal patterns of fat gain or loss with the different therapies. The current report from a prospective randomized study among initially antiretroviral-naive subjects using objective measures clearly links use of a particular NRTI combination with loss of limb fat over time compared with baseline values. However, our data cannot address the relative contribution of the individual components (ddI or d4T) to the observed effects. Nonetheless, it is clear that d4T contributes to lipoatrophy risk even when combined with 3TC [39], while the individual contribution of ddI is less certain. Because of the risk of side effects, this drug combination is no longer recommended [43].A limitation of the body composition analyses in this report is the relatively short follow-up period, 64 weeks. This period was chosen to coincide with the available metabolic data, which were limited to 64 weeks. It is possible that with more extended observation, differences between treatment groups may become even greater, or they may equilibrate over time.Unlike limb fat, trunk fat tended to remain above baseline values in all groups. Similar increases in DEXA-derived central abdominal fat have been reported in a prospective, non-randomized observational study [44]. It is possible that the early increases in limb fat and the persistent increases in trunk fat represent a generalized ‘return-to-health’ phenomenon associated with viral suppression and immune reconstitution. This study provides evidence that the subsequent decreases in limb fat are related to use of particular antiretroviral drugs. The treatments that spared limb fat over 64 weeks (ZDV/3TC, efavirenz) were also associated with overall greater increases in trunk fat and total body fat. This may represent a generalized increase in adiposity that preferentially affects trunk fat. If such an increase reflects increased visceral fat, it is a potentially adverse consequence. DEXA scans, however, do not differentiate between visceral and subcutaneous trunk fat.Our results illustrate the importance of prospective studies to determine the particular roles of individual antiretroviral agents and combinations in the development of metabolic and morphological complications. Extended follow-up will be necessary to define the long-term course of these complications, particularly as individuals are treated with multiple different antiretroviral agents from multiple drug classes. It will be crucial to develop new, less-toxic antiretroviral agents and combination regimens in order to minimize the cardiovascular risks associated with antiretroviral therapy [45,46] and the stigma, non-adherence [47–49], and metabolic disturbances [8] associated with lipodystrophy.AcknowledgementsA5005s team members who contributed to the design and conduct of the trial were Thomas A. Buchanan (University of Southern California), Kevin Yarasheski, (Washington University, St Louis), and Jeff Taylor (ACTG Community Constituency Group representative, San Diego).We are grateful to the subjects who volunteered for these experiments, without whom this work would not have been possible. The authors acknowledge the invaluable assistance of Gina-Bob Dubé and Kathy L. Flynn with managing the references, Lawrence A. Hirsch of Quest Diagnostics for coordinating laboratory assays, and Jodi L. Weiner, of the Friedman School of Nutrition Science and Policy at Tufts University for DEXA scan management.Sponsorship: Supported by grants to the AIDS Clinical Trials Group from the National Institute of Allergy and Infectious Diseases (AI38855 and AI38858). The parent protocol (ACTG 384) was supported in part by Agouron Pharmaceuticals, Inc., Bristol-Myers Squibb Company, DuPont Pharmaceutical Company, GlaxoSmithKline, Inc., and Merck and Co., Inc.Note: These data were presented, in part, at the 4th International Workshop on Adverse Drug Reactions and Lipodystrophy in HIV, September 2002, San Diego, CA, and at the 11th Conference on Retroviruses and Opportunistic Infections, February 2004, San Francisco, CA.References1. Dubé MP, Johnson DL, Currier JS, Leedom JM. Protease inhibitor-associated hyperglycaemia. Lancet 1997; 350:713–714. [CrossRef] [Full Text] [Medline Link] [Context Link]2. Visnegarwala F, Krause KL, Musher DM. Severe diabetes associated with protease inhibitor therapy. Ann Intern Med 1997; 127:947. [CrossRef] [Full Text] [Medline Link] [Context Link]3. Carr A, Samaras K, Burton S, Law M, Freund J, Chisholm DJ, et al. A syndrome of peripheral lipodystrophy, hyperlipidaemia and insulin resistance due to HIV protease inhibitors. AIDS 1998; 12:F51–F58. [CrossRef] [Full Text] [Medline Link] [Context Link]4. Walli R, Herfort O, Michl GM, Demant T, Jager H, Dieterle C, et al. Treatment with protease inhibitors associated with peripheral insulin resistance and impaired oral glucose tolerance in HIV-1-infected patients. AIDS 1998; 12:F167–F173. [CrossRef] [Full Text] [Medline Link] [Context Link]5. Behrens G, Dejam A, Schmidt H, Balks HJ, Brabant G, Korner T, et al. Impaired glucose tolerance, beta cell function and lipid metabolism in HIV patients under treatment with protease inhibitors. AIDS 1999; 13:F63–F70. [CrossRef] [Full Text] [Medline Link] [Context Link]6. Periard D, Telenti A, Sudre P, Cheseaux JJ, Halfon P, Reymond MJ, et al. Atherogenic dyslipidemia in HIV-infected individuals treated with protease inhibitors. the Swiss HIV Cohort Study. Circulation 1999; 100:700–705. [CrossRef] [Full Text] [Medline Link] [Context Link]7. Mulligan K, Grunfeld C, Tai VW, Algran H, Pang M, Chernoff DN, et al. Hyperlipidemia and insulin resistance are induced by protease inhibitors independent of changes in body composition in patients with HIV infection. J Acquir Immune Defic Syndr 2000; 23:35–43. [CrossRef] [Full Text] [Medline Link] [Context Link]8. Hadigan C, Meigs JB, Corcoran C, Rietschel P, Piecuch S, Basgoz N, et al. Metabolic abnormalities and cardiovascular disease risk factors in adults with human immunodeficiency virus infection and lipodystrophy. Clin Infect Dis 2001; 32:130–139. [CrossRef] [Full Text] [Medline Link] [Context Link]9. Schambelan M, Benson CA, Carr A, Currier JS, Dube MP, Gerber JG, et al. Management of metabolic complications associated with antiretroviral therapy for HIV-1 Infection: recommendations of an International AIDS Society–USA Panel. J Acquir Immune Defic Syndr 2002; 31:257–275. [CrossRef] [Full Text] [Medline Link] [Context Link]10. Dubé MP, Stein JH, Aberg JA, Fichtenbaum CJ, Gerber JG, Tashima KT, et al. Guidelines for the evaluation and management of dyslipidemia in HIV-infected adults receiving antiretroviral therapy. Clin Infect Dis 2003; 37:613–627. [Context Link]11. Kotler DP, Rosenbaum K, Wang J, Pierson RN. Studies of body composition and fat distribution in HIV-infected and control subjects. J Acquir Immune Defic Syndr 1999; 20:228–237. [Context Link]12. Gervasoni C, Ridolfo AL, Trifiro G, Santambrogio S, Norbiato G, Musicco M, et al. Redistribution of body fat in HIV-infected women undergoing combined antiretroviral therapy. AIDS 1999; 13:465–471. [CrossRef] [Full Text] [Medline Link] [Context Link]13. Lichtenstein KA, Ward DJ, Moorman AC, Delaney KM, Young B, Palella FJ Jr, et al. Clinical assessment of HIV-associated lipodystrophy in an ambulatory population. AIDS 2001; 15:1389–1398. [CrossRef] [Full Text] [Medline Link] [Context Link]14. Robbins GK, de Gruttola V, Shafer RW, Smeaton LM, Snyder SW, Pettinelli C, et al. Comparison of sequential three-drug regimens as initial therapy for HIV-1 infection. N Engl J Med 2003; 349:2293–2303. [CrossRef] [Full Text] [Medline Link] [Context Link]15. Shafer RW, Smeaton LM, Robbins GK, de Gruttola V, Snyder SW, D'Aquila RT, et al. Comparison of four-drug regimens and pairs of sequential three-drug regimens as initial therapy for HIV-1 infection. N Engl J Med 2003; 349:2304–2315. [CrossRef] [Full Text] [Medline Link] [Context Link]16. Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972; 18:499–502. [Context Link]17. Matthews DR, Hosker JP, Rudenski AS, Naylor DF, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and B-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28:412–419. [CrossRef] [Medline Link] [Context Link]18. Haffner SM, Miettinen H, Stern MP. The homeostasis model in the San Antonio Heart Study. Diabetes Care 1997; 20:1087–1092. [CrossRef] [Full Text] [Medline Link] [Context Link]19. Bonora E, Targher G, Alberiche M, Bonadonna RC, Saggiani F, Zenere MB, et al. Homeostasis model assessment closely mirrors the glucose clamp technique in the assessment of insulin sensitivity: studies in subjects with various degrees of glucose tolerance and insulin sensitivity. Diabetes Care 2000; 23:57–63. [CrossRef] [Full Text] [Medline Link] [Context Link]20. Lumpkin MM. Reports of Diabetes and Hyperglycemia in Patients Receiving Protease Inhibitors for the Treatment of Human Immunodeficiency Virus (HIV). Washington, DC: FDA Public Health Advisory Board; 1997. [Context Link]21. Noor MA, Lo JC, Mulligan K, Schwarz JM, Halvorsen RA, Schambelan M, et al. Metabolic effects of indinavir in healthy HIV-seronegative men. AIDS 2001; 15:F11–F18. [Context Link]22. Dubé MP, Edmondson-Melançon H, Qian D, Aqeel R, Johnson DJ, Buchanan TA. Prospective evaluation of the effect of initiating indinavir-based therapy on insulin sensitivity and B-cell function in HIV-infected patients. J Acquir Immune Defic Syndr 2001; 27:130–134. [CrossRef] [Full Text] [Medline Link] [Context Link]23. Noor MA, Seneviratne T, Aweeka FT, Lo JC, Schwarz J, Mulligan K, et al. Indinavir acutely inhibits insulin-stimulated glucose disposal in humans: A randomized, placebo-controlled study. AIDS 2002; 16:F1–F8. [CrossRef] [Full Text] [Medline Link] [Context Link]24. Murata H, Hruz PW, Mueckler M. Indinavir inhibits the glucose transporter isoform Glut4 at physiologic concentrations. AIDS 2002; 16:859–863. [CrossRef] [Full Text] [Medline Link] [Context Link]25. Murata H, Hruz PW, Mueckler M. The mechanism of insulin resistance caused by HIV protease inhibitor therapy. J Biol Chem 2000; 275:20251–20254. [CrossRef] [Medline Link] [Context Link]26. Dubé MP, Qian D, Edmondson-Melançon H, Sattler FR, Goodwin D, Martinez C, et al. Prospective, 48-week, intensive metabolic study of amprenavir-based therapy. Clin Infect Dis 2002; 35:475–481. [Context Link]27. Squires K, Lazzarin A, Gatell JM, Powderly WG, Pokrovskiy V, Delfraissy JF, et al. Comparison of once-daily atazanavir with efavirenz, each in combination with fixed-dose zidovudine and lamivudine, as initial therapy for patients infected with HIV. J Acquir Immune Defic Syndr 2004; 36:1011–1019. [CrossRef] [Full Text] [Medline Link] [Context Link]28. Noor MA, Parker RA, O'Mara E, Grasela DM, Currie A, Hodder SL, et al. The effects of HIV protease inhibitors atazanavir and lopinavir/ritonavir on insulin sensitivity in HIV-seronegative healthy adults. AIDS 2004; 18:2137–2144. [Context Link]29. Lee GA, Seneviratne T, Noor MA, Lo JC, Schwarz J, Aweeka FT, et al. The metabolic effects of lopinavir/ritonavir in HIV negative men. AIDS 2004; 18:641–649. [Context Link]30. Haubrich R, Miller C, Gathe J, Pearce D, Dretler R, Petersen C. The effect of NFV versus EFV on fasting lipid levels: interim analysis from a prospective randomized study in treatment naive patients (AG1127). 42th Interscience Conference on Antimicrobial Agents and Chemotherapy. San Diego, September 2002 [poster H1914]. [Context Link]31. Kinosian B, Glick H, Garland G. Cholesterol and coronary heart disease: predicting risks by levels and ratios. Ann Intern Med 1994; 121:641–647. [CrossRef] [Full Text] [Medline Link] [Context Link]32. Cui Y, Blumenthal RS, Flaws JA, Whiteman MK, Langenberg P, Bachorik PS, et al. Non high-density lipoprotein cholesterol level as a predictor of cardiovascular disease mortality. Arch Intern Med 2001; 161:1413–1419. [CrossRef] [Full Text] [Medline Link] [Context Link]33. Mallal SA, John M, Moore CB, James IR, McKinnon EJ. Contribution of nucleoside analogue reverse transcripatase inhibitors to subcutaneous fat wasting in patients with HIV infection. AIDS 2000; 14:1309–1316. [Context Link]34. van der Valk M, Gisolf EH, Reiss P, Wit FW, Japour A, Weverling GJ, et al. Increased risk of lipodystrophy when nucleoside analogue reverse transcriptase inhibitors are included with protease inhibitors in the treatment of HIV-1 infection. AIDS 2001; 15:847–855. [CrossRef] [Full Text] [Medline Link] [Context Link]35. Dowell P, Flexner C, Kwiterovich PO, Lane MD. Suppression of preadipocyte differentiation and promotion of adipocyte death by HIV protease inhibitors. J Biol Chem 2000; 275:41325–41332. [CrossRef] [Medline Link] [Context Link]36. Vernochet C, Azoulay S, Duval D, Guedj R, Ailhaud G, Dani C. Differential effect of HIV protease inhibitors on adipogenesis: intracellular ritonavir is not sufficient to inhibit differentiation. AIDS 2003; 17:2177–2180. [CrossRef] [Full Text] [Medline Link] [Context Link]37. Caron M, Auclair M, Sterlingot H, Kornprobst M, Capeau J. Some HIV protease inhibitors alter lamin A/C maturation and stability, SREBP-1 nuclear localization and adipocyte differentiation. AIDS 2003; 17:2437–2444. [CrossRef] [Full Text] [Medline Link] [Context Link]38. Joly V, Flandre P, Meiffredy V, Leturque N, Harel M, Aboulker JP, et al. Increased risk of lipoatrophy under stavudine in HIV-1-infected patients: results of a substudy from a comparative trial. AIDS 2002; 16:2447–2454. [CrossRef] [Full Text] [Medline Link] [Context Link]39. Gallant JE, Staszewski S, Pozniak AL, DeJesus E, Suleiman JM, Miller MD, et al. Efficacy and safety of tenofovir DF vs stavudine in combination therapy in antiretroviral-naive patients: a 3-year randomized trial. JAMA 2004; 292:191–201. [CrossRef] [Full Text] [Medline Link] [Context Link]40. Carr A, Workman C, Smith DE, Hoy J, Hudson J, Doong N, et al. Abacavir substitution for nucleoside analogs in patients with HIV lipoatrophy: a randomized trial. JAMA 2002; 288:207–215. [CrossRef] [Full Text] [Medline Link] [Context Link]41. Saint-Marc T, Touraine JL. The effects of discontinuing stavudine therapy on clinical and metabolic abnormalities in patients suffering from lipodystrophy. AIDS 1999; 13:2188–2189. [CrossRef] [Full Text] [Medline Link] [Context Link]42. Wohl DA, Pilcher CD, Evans S, Revuelta M, McComsey G, Yang Y, et al. Absence of sustained hyperlactatemia in HIV-infected patients with risk factors for mitochondrial toxicity. J Acquir Immune Defic Syndr 2004; 35:274–278. [CrossRef] [Full Text] [Medline Link] [Context Link]43. Panel on Clinical Practices for Treatment of HIV Infection. Guidelines for the Use of Antiretroviral Agents in HIV-1-Infected Adults and Adolescents. Washington, DC: Department of Health and Human Services; 2003. http://www.aidsinfo.nih.gov/guidelines/adult%5CAA_111003.pdf . [Context Link]44. Mallon PW, Miller J, Cooper DA, Carr A. Prospective evaluation of the effects of antiretroviral therapy on body composition in HIV-1-infected men starting therapy. AIDS 2003; 17:971–979. [CrossRef] [Full Text] [Medline Link] [Context Link]45. Friis-Møller N, Sabin CA, Weber R, d'Arminio Monforte A, El-Sadr WM, Reiss P, et al. Combination antiretroviral therapy and the risk of myocardial infarction. N Engl J Med 2003; 349:1993–2003. [CrossRef] [Full Text] [Medline Link] [Context Link]46. Friis-Møller N, Weber R, Reiss P, Thiebaut R, Kirk O, d'Arminio Monforte A, et al. Cardiovascular disease risk factors in HIV patients–association with antiretroviral therapy. Results from the DAD study. AIDS 2003; 17:1179–1193. [CrossRef] [Full Text] [Medline Link] [Context Link]47. Duran S, Saves M, Spire B, Cailleton V, Sobel A, Carrieri P, et al. Failure to maintain long-term adherence to highly active antiretroviral therapy: the role of lipodystrophy. AIDS 2001; 15:2441–2444. [CrossRef] [Full Text] [Medline Link] [Context Link]48. Power R, Tate HL, McGill SM, Taylor C. A qualitative study of the psychosocial implications of lipodystrophy syndrome on HIV positive individuals. Sex Transm Infect 2003; 79:137–141. [CrossRef] [Full Text] [Medline Link] [Context Link]49. Ammassari A, Antinori A, Cozzi-Lepri A, Trotta MP, Nasti G, Ridolfo AL, et al. Relationship between HAART adherence and adipose tissue alterations. J Acquir Immune Defic Syndr 2002; 31:S140–S144. [CrossRef] [Full Text] [Medline Link] [Context Link]AppendixThe following ACTG investigators and sites participated in this study: Barbara M. Gripshover and Kathleen Burgner (Case Western Reserve University, A2501), Ian Frank and Isabel Matozzo (University of Pennsylvania, Philadelphia, A 6201), Laura Laughlin and Diane Gochnour (Ohio State University, A2301, grant U01 AI025924); Tammy Powell and Pamposh Kaul (University of Cincinnati, A2401, grant AI25897); Debra deMarco and John Stoneman (Washington University, St Louis, A2101, grant AI25903 and RR-00036); Connie A. Funk and Kathleen E. Squires (University of Southern California, A1201, grant U01A127673); Margaret A. Fischl and Leslie Thompson (University of Miami, A0901, grant AI27675); Mitch Goldman and Helen Rominger (Indiana University Hospital, A2601, grant U01AI25859 and RR-00750); Linda Meixner and Tari Gilbert (University of California, San Diego, A0701, grant AI27670); Christine Fietzer and Kathy A. Fox (University of Minnesota, A1501), Eileen Chusid and Donna Mildvan (Beth Israel Medical Center, Mount Sinai Medical Center, New York, A1801, grant AI 46370; University of North Carolina, A3201; Howard University, A5301); Lynn Dumas (Beth Israel-Deaconess Hospital) and Betsy Adams (Boston Medical Center) (Harvard, Massachusetts General Hospital, A0101); Mallory Witt and Tomasa Maldonado (Harbor General/UCLA School of Medicine, A0601); Juan J. L. Lertora and Rebecca Clark (Tulane University, A1701, grant IU01AI3844 and GCRC grant PHS NCRR M01 RR05096); Pat Cain and Sylvia Stoudt (Stanford University, A0501; NYU/Bellevue, A0401); Harold A. Kessler and Ruth M. Davis (Rush-Presbyterian/St. Lukes, Chicago, A2702, grant UO1 AI025915); Santiago Marrero and Irma Torres (University of Puerto Rico, A5401, grant A134832-12); Diane Havlir and Jody Lawrence (San Francisco General Hospital, A0801; University of Hawaii, A5201; University of Rochester Medical Center, A1101); Clifford Gunthel and Ericka Patrick (Emory University, A5802); Michael J. Borucki and Gerianne Casey (University of Texas, Galveston, A6301, grant AI32782); Ilene Wiggins and Dorcas Baker (Johns Hopkins University, A0201, grant RR00052 and AI27668); Carol Dukes-Hamilton and Shelia Tedder (Duke University Medical Center, A1601); Valery Hughes and Todd Stroberg (Cornell University, A2201, grant AI46386); Sally Canmann and Cathi Basler (University of Colorado Health Sciences Center, Denver, A6101); Beck Royer and N. Jeanne Conley (University of Washington Seattle, A1401, grant AI27664). antiretroviral drugs; dyslipidemia; HIV; insulin resistance; lipodystrophyovid.com:/bib/ovftdb/00002030-200511040-0000900005531_1997_350_713_dube_hyperglycaemia_|00002030-200511040-00009#xpointer(id(R1-9))|11065213||ovftdb|00005531-199709060-00017SL00005531199735071311065213P76[CrossRef]10.1016%2FS0140-6736%2805%2963513-1ovid.com:/bib/ovftdb/00002030-200511040-0000900005531_1997_350_713_dube_hyperglycaemia_|00002030-200511040-00009#xpointer(id(R1-9))|11065404||ovftdb|00005531-199709060-00017SL00005531199735071311065404P76[Full Text]00005531-199709060-00017ovid.com:/bib/ovftdb/00002030-200511040-0000900005531_1997_350_713_dube_hyperglycaemia_|00002030-200511040-00009#xpointer(id(R1-9))|11065405||ovftdb|00005531-199709060-00017SL00005531199735071311065405P76[Medline Link]9291911ovid.com:/bib/ovftdb/00002030-200511040-0000900000605_1997_127_947_visnegarwala_associated_|00002030-200511040-00009#xpointer(id(R2-9))|11065213||ovftdb|00000605-199711150-00016SL00000605199712794711065213P77[CrossRef]10.7326%2F0003-4819-127-10-199711150-00016ovid.com:/bib/ovftdb/00002030-200511040-0000900000605_1997_127_947_visnegarwala_associated_|00002030-200511040-00009#xpointer(id(R2-9))|11065404||ovftdb|00000605-199711150-00016SL00000605199712794711065404P77[Full Text]00000605-199711150-00016ovid.com:/bib/ovftdb/00002030-200511040-0000900000605_1997_127_947_visnegarwala_associated_|00002030-200511040-00009#xpointer(id(R2-9))|11065405||ovftdb|00000605-199711150-00016SL00000605199712794711065405P77[Medline Link]9382374ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1998_12_f51_carr_hyperlipidaemia_|00002030-200511040-00009#xpointer(id(R3-9))|11065213||ovftdb|00002030-199807000-00003SL00002030199812f5111065213P78[CrossRef]10.1097%2F00002030-199807000-00003ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1998_12_f51_carr_hyperlipidaemia_|00002030-200511040-00009#xpointer(id(R3-9))|11065404||ovftdb|00002030-199807000-00003SL00002030199812f5111065404P78[Full Text]00002030-199807000-00003ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1998_12_f51_carr_hyperlipidaemia_|00002030-200511040-00009#xpointer(id(R3-9))|11065405||ovftdb|00002030-199807000-00003SL00002030199812f5111065405P78[Medline Link]9619798ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1998_12_f167_walli_inhibitors_|00002030-200511040-00009#xpointer(id(R4-9))|11065213||ovftdb|00002030-199815000-00001SL00002030199812f16711065213P79[CrossRef]10.1097%2F00002030-199815000-00001ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1998_12_f167_walli_inhibitors_|00002030-200511040-00009#xpointer(id(R4-9))|11065404||ovftdb|00002030-199815000-00001SL00002030199812f16711065404P79[Full Text]00002030-199815000-00001ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1998_12_f167_walli_inhibitors_|00002030-200511040-00009#xpointer(id(R4-9))|11065405||ovftdb|00002030-199815000-00001SL00002030199812f16711065405P79[Medline Link]9814858ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1999_13_f63_behrens_metabolism_|00002030-200511040-00009#xpointer(id(R5-9))|11065213||ovftdb|00002030-199907090-00001SL00002030199913f6311065213P80[CrossRef]10.1097%2F00002030-199907090-00001ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1999_13_f63_behrens_metabolism_|00002030-200511040-00009#xpointer(id(R5-9))|11065404||ovftdb|00002030-199907090-00001SL00002030199913f6311065404P80[Full Text]00002030-199907090-00001ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1999_13_f63_behrens_metabolism_|00002030-200511040-00009#xpointer(id(R5-9))|11065405||ovftdb|00002030-199907090-00001SL00002030199913f6311065405P80[Medline Link]10416516ovid.com:/bib/ovftdb/00002030-200511040-0000900003017_1999_100_700_periard_dyslipidemia_|00002030-200511040-00009#xpointer(id(R6-9))|11065213||ovftdb|00003017-199908170-00004SL00003017199910070011065213P81[CrossRef]10.1161%2F01.CIR.100.7.700ovid.com:/bib/ovftdb/00002030-200511040-0000900003017_1999_100_700_periard_dyslipidemia_|00002030-200511040-00009#xpointer(id(R6-9))|11065404||ovftdb|00003017-199908170-00004SL00003017199910070011065404P81[Full Text]00003017-199908170-00004ovid.com:/bib/ovftdb/00002030-200511040-0000900003017_1999_100_700_periard_dyslipidemia_|00002030-200511040-00009#xpointer(id(R6-9))|11065405||ovftdb|00003017-199908170-00004SL00003017199910070011065405P81[Medline Link]10449690ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2000_23_35_mulligan_hyperlipidemia_|00002030-200511040-00009#xpointer(id(R7-9))|11065213||ovftdb|00126334-200001010-00005SL000052202000233511065213P82[CrossRef]10.1097%2F00042560-200001010-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2000_23_35_mulligan_hyperlipidemia_|00002030-200511040-00009#xpointer(id(R7-9))|11065404||ovftdb|00126334-200001010-00005SL000052202000233511065404P82[Full Text]00126334-200001010-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2000_23_35_mulligan_hyperlipidemia_|00002030-200511040-00009#xpointer(id(R7-9))|11065405||ovftdb|00126334-200001010-00005SL000052202000233511065405P82[Medline Link]10708054ovid.com:/bib/ovftdb/00002030-200511040-0000900001691_2001_32_130_hadigan_immunodeficiency_|00002030-200511040-00009#xpointer(id(R8-9))|11065213||ovftdb|01451458-200101010-00017SL0000169120013213011065213P83[CrossRef]10.1086%2F317541ovid.com:/bib/ovftdb/00002030-200511040-0000900001691_2001_32_130_hadigan_immunodeficiency_|00002030-200511040-00009#xpointer(id(R8-9))|11065404||ovftdb|01451458-200101010-00017SL0000169120013213011065404P83[Full Text]01451458-200101010-00017ovid.com:/bib/ovftdb/00002030-200511040-0000900001691_2001_32_130_hadigan_immunodeficiency_|00002030-200511040-00009#xpointer(id(R8-9))|11065405||ovftdb|01451458-200101010-00017SL0000169120013213011065405P83[Medline Link]11118392ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2002_31_257_schambelan_recommendations_|00002030-200511040-00009#xpointer(id(R9-9))|11065213||ovftdb|00126334-200211010-00001SL0000522020023125711065213P84[CrossRef]10.1097%2F00126334-200211010-00001ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2002_31_257_schambelan_recommendations_|00002030-200511040-00009#xpointer(id(R9-9))|11065404||ovftdb|00126334-200211010-00001SL0000522020023125711065404P84[Full Text]00126334-200211010-00001ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2002_31_257_schambelan_recommendations_|00002030-200511040-00009#xpointer(id(R9-9))|11065405||ovftdb|00126334-200211010-00001SL0000522020023125711065405P84[Medline Link]12439201ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1999_13_465_gervasoni_redistribution_|00002030-200511040-00009#xpointer(id(R12-9))|11065213||ovftdb|00002030-199903110-00004SL0000203019991346511065213P87[CrossRef]10.1097%2F00002030-199903110-00004ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1999_13_465_gervasoni_redistribution_|00002030-200511040-00009#xpointer(id(R12-9))|11065404||ovftdb|00002030-199903110-00004SL0000203019991346511065404P87[Full Text]00002030-199903110-00004ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1999_13_465_gervasoni_redistribution_|00002030-200511040-00009#xpointer(id(R12-9))|11065405||ovftdb|00002030-199903110-00004SL0000203019991346511065405P87[Medline Link]10197374ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2001_15_1389_lichtenstein_lipodystrophy_|00002030-200511040-00009#xpointer(id(R13-9))|11065213||ovftdb|00002030-200107270-00008SL00002030200115138911065213P88[CrossRef]10.1097%2F00002030-200107270-00008ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2001_15_1389_lichtenstein_lipodystrophy_|00002030-200511040-00009#xpointer(id(R13-9))|11065404||ovftdb|00002030-200107270-00008SL00002030200115138911065404P88[Full Text]00002030-200107270-00008ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2001_15_1389_lichtenstein_lipodystrophy_|00002030-200511040-00009#xpointer(id(R13-9))|11065405||ovftdb|00002030-200107270-00008SL00002030200115138911065405P88[Medline Link]11504960ovid.com:/bib/ovftdb/00002030-200511040-0000900006024_2003_349_2293_robbins_comparison_|00002030-200511040-00009#xpointer(id(R14-9))|11065213||ovftdb|00006024-200312110-00005SL000060242003349229311065213P89[CrossRef]10.1056%2FNEJMoa030264ovid.com:/bib/ovftdb/00002030-200511040-0000900006024_2003_349_2293_robbins_comparison_|00002030-200511040-00009#xpointer(id(R14-9))|11065404||ovftdb|00006024-200312110-00005SL000060242003349229311065404P89[Full Text]00006024-200312110-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900006024_2003_349_2293_robbins_comparison_|00002030-200511040-00009#xpointer(id(R14-9))|11065405||ovftdb|00006024-200312110-00005SL000060242003349229311065405P89[Medline Link]14668455ovid.com:/bib/ovftdb/00002030-200511040-0000900006024_2003_349_2304_shafer_comparison_|00002030-200511040-00009#xpointer(id(R15-9))|11065213||ovftdb|00006024-200312110-00006SL000060242003349230411065213P90[CrossRef]10.1056%2FNEJMoa030265ovid.com:/bib/ovftdb/00002030-200511040-0000900006024_2003_349_2304_shafer_comparison_|00002030-200511040-00009#xpointer(id(R15-9))|11065404||ovftdb|00006024-200312110-00006SL000060242003349230411065404P90[Full Text]00006024-200312110-00006ovid.com:/bib/ovftdb/00002030-200511040-0000900006024_2003_349_2304_shafer_comparison_|00002030-200511040-00009#xpointer(id(R15-9))|11065405||ovftdb|00006024-200312110-00006SL000060242003349230411065405P90[Medline Link]14668456ovid.com:/bib/ovftdb/00002030-200511040-0000900003441_1985_28_412_matthews_concentrations_|00002030-200511040-00009#xpointer(id(R17-9))|11065213||ovftdb|SL0000344119852841211065213P92[CrossRef]10.1007%2FBF00280883ovid.com:/bib/ovftdb/00002030-200511040-0000900003441_1985_28_412_matthews_concentrations_|00002030-200511040-00009#xpointer(id(R17-9))|11065405||ovftdb|SL0000344119852841211065405P92[Medline Link]3899825ovid.com:/bib/ovftdb/00002030-200511040-0000900003458_1997_20_1087_haffner_homeostasis_|00002030-200511040-00009#xpointer(id(R18-9))|11065213||ovftdb|00003458-199707000-00008SL00003458199720108711065213P93[CrossRef]10.2337%2Fdiacare.20.7.1087ovid.com:/bib/ovftdb/00002030-200511040-0000900003458_1997_20_1087_haffner_homeostasis_|00002030-200511040-00009#xpointer(id(R18-9))|11065404||ovftdb|00003458-199707000-00008SL00003458199720108711065404P93[Full Text]00003458-199707000-00008ovid.com:/bib/ovftdb/00002030-200511040-0000900003458_1997_20_1087_haffner_homeostasis_|00002030-200511040-00009#xpointer(id(R18-9))|11065405||ovftdb|00003458-199707000-00008SL00003458199720108711065405P93[Medline Link]9203442ovid.com:/bib/ovftdb/00002030-200511040-0000900003458_2000_23_57_bonora_homeostasis_|00002030-200511040-00009#xpointer(id(R19-9))|11065213||ovftdb|00003458-200001000-00011SL000034582000235711065213P94[CrossRef]10.2337%2Fdiacare.23.1.57ovid.com:/bib/ovftdb/00002030-200511040-0000900003458_2000_23_57_bonora_homeostasis_|00002030-200511040-00009#xpointer(id(R19-9))|11065404||ovftdb|00003458-200001000-00011SL000034582000235711065404P94[Full Text]00003458-200001000-00011ovid.com:/bib/ovftdb/00002030-200511040-0000900003458_2000_23_57_bonora_homeostasis_|00002030-200511040-00009#xpointer(id(R19-9))|11065405||ovftdb|00003458-200001000-00011SL000034582000235711065405P94[Medline Link]10857969ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2001_27_130_dube_prospective_|00002030-200511040-00009#xpointer(id(R22-9))|11065213||ovftdb|00126334-200106010-00005SL0000522020012713011065213P97[CrossRef]10.1097%2F00042560-200106010-00006ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2001_27_130_dube_prospective_|00002030-200511040-00009#xpointer(id(R22-9))|11065404||ovftdb|00126334-200106010-00005SL0000522020012713011065404P97[Full Text]00126334-200106010-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2001_27_130_dube_prospective_|00002030-200511040-00009#xpointer(id(R22-9))|11065405||ovftdb|00126334-200106010-00005SL0000522020012713011065405P97[Medline Link]11404534ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2002_16_f1_noor_stimulated_|00002030-200511040-00009#xpointer(id(R23-9))|11065213||ovftdb|00002030-200203290-00002SL00002030200216f111065213P98[CrossRef]10.1097%2F00002030-200203290-00002ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2002_16_f1_noor_stimulated_|00002030-200511040-00009#xpointer(id(R23-9))|11065404||ovftdb|00002030-200203290-00002SL00002030200216f111065404P98[Full Text]00002030-200203290-00002ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2002_16_f1_noor_stimulated_|00002030-200511040-00009#xpointer(id(R23-9))|11065405||ovftdb|00002030-200203290-00002SL00002030200216f111065405P98[Medline Link]11964551ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2002_16_859_murata_concentrations_|00002030-200511040-00009#xpointer(id(R24-9))|11065213||ovftdb|00002030-200204120-00005SL0000203020021685911065213P99[CrossRef]10.1097%2F00002030-200204120-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2002_16_859_murata_concentrations_|00002030-200511040-00009#xpointer(id(R24-9))|11065404||ovftdb|00002030-200204120-00005SL0000203020021685911065404P99[Full Text]00002030-200204120-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2002_16_859_murata_concentrations_|00002030-200511040-00009#xpointer(id(R24-9))|11065405||ovftdb|00002030-200204120-00005SL0000203020021685911065405P99[Medline Link]11919487ovid.com:/bib/ovftdb/00002030-200511040-0000900004613_2000_275_20251_murata_resistance_|00002030-200511040-00009#xpointer(id(R25-9))|11065213||ovftdb|SL0000461320002752025111065213P100[CrossRef]10.1074%2Fjbc.C000228200ovid.com:/bib/ovftdb/00002030-200511040-0000900004613_2000_275_20251_murata_resistance_|00002030-200511040-00009#xpointer(id(R25-9))|11065405||ovftdb|SL0000461320002752025111065405P100[Medline Link]10806189ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2004_36_1011_squires_combination_|00002030-200511040-00009#xpointer(id(R27-9))|11065213||ovftdb|00126334-200408150-00003SL00005220200436101111065213P102[CrossRef]10.1097%2F00126334-200408150-00003ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2004_36_1011_squires_combination_|00002030-200511040-00009#xpointer(id(R27-9))|11065404||ovftdb|00126334-200408150-00003SL00005220200436101111065404P102[Full Text]00126334-200408150-00003ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2004_36_1011_squires_combination_|00002030-200511040-00009#xpointer(id(R27-9))|11065405||ovftdb|00126334-200408150-00003SL00005220200436101111065405P102[Medline Link]15247553ovid.com:/bib/ovftdb/00002030-200511040-0000900000605_1994_121_641_kinosian_cholesterol_|00002030-200511040-00009#xpointer(id(R31-9))|11065213||ovftdb|00000605-199411010-00002SL00000605199412164111065213P106[CrossRef]10.7326%2F0003-4819-121-9-199411010-00002ovid.com:/bib/ovftdb/00002030-200511040-0000900000605_1994_121_641_kinosian_cholesterol_|00002030-200511040-00009#xpointer(id(R31-9))|11065404||ovftdb|00000605-199411010-00002SL00000605199412164111065404P106[Full Text]00000605-199411010-00002ovid.com:/bib/ovftdb/00002030-200511040-0000900000605_1994_121_641_kinosian_cholesterol_|00002030-200511040-00009#xpointer(id(R31-9))|11065405||ovftdb|00000605-199411010-00002SL00000605199412164111065405P106[Medline Link]7944071ovid.com:/bib/ovftdb/00002030-200511040-0000900000779_2001_161_1413_cui_cardiovascular_|00002030-200511040-00009#xpointer(id(R32-9))|11065213||ovftdb|00000779-200106110-00006SL000007792001161141311065213P107[CrossRef]10.1001%2Farchinte.161.11.1413ovid.com:/bib/ovftdb/00002030-200511040-0000900000779_2001_161_1413_cui_cardiovascular_|00002030-200511040-00009#xpointer(id(R32-9))|11065404||ovftdb|00000779-200106110-00006SL000007792001161141311065404P107[Full Text]00000779-200106110-00006ovid.com:/bib/ovftdb/00002030-200511040-0000900000779_2001_161_1413_cui_cardiovascular_|00002030-200511040-00009#xpointer(id(R32-9))|11065405||ovftdb|00000779-200106110-00006SL000007792001161141311065405P107[Medline Link]11386890ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2001_15_847_valk_lipodystrophy_|00002030-200511040-00009#xpointer(id(R34-9))|11065213||ovftdb|00002030-200105040-00005SL0000203020011584711065213P109[CrossRef]10.1097%2F00002030-200105040-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2001_15_847_valk_lipodystrophy_|00002030-200511040-00009#xpointer(id(R34-9))|11065404||ovftdb|00002030-200105040-00005SL0000203020011584711065404P109[Full Text]00002030-200105040-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2001_15_847_valk_lipodystrophy_|00002030-200511040-00009#xpointer(id(R34-9))|11065405||ovftdb|00002030-200105040-00005SL0000203020011584711065405P109[Medline Link]11399957ovid.com:/bib/ovftdb/00002030-200511040-0000900004613_2000_275_41325_dowell_differentiation_|00002030-200511040-00009#xpointer(id(R35-9))|11065213||ovftdb|SL0000461320002754132511065213P110[CrossRef]10.1074%2Fjbc.M006474200ovid.com:/bib/ovftdb/00002030-200511040-0000900004613_2000_275_41325_dowell_differentiation_|00002030-200511040-00009#xpointer(id(R35-9))|11065405||ovftdb|SL0000461320002754132511065405P110[Medline Link]11018036ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_2177_vernochet_differentiation_|00002030-200511040-00009#xpointer(id(R36-9))|11065213||ovftdb|00002030-200310170-00005SL00002030200317217711065213P111[CrossRef]10.1097%2F00002030-200310170-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_2177_vernochet_differentiation_|00002030-200511040-00009#xpointer(id(R36-9))|11065404||ovftdb|00002030-200310170-00005SL00002030200317217711065404P111[Full Text]00002030-200310170-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_2177_vernochet_differentiation_|00002030-200511040-00009#xpointer(id(R36-9))|11065405||ovftdb|00002030-200310170-00005SL00002030200317217711065405P111[Medline Link]14523274ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_2437_caron_differentiation_|00002030-200511040-00009#xpointer(id(R37-9))|11065213||ovftdb|00002030-200311210-00005SL00002030200317243711065213P112[CrossRef]10.1097%2F00002030-200311210-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_2437_caron_differentiation_|00002030-200511040-00009#xpointer(id(R37-9))|11065404||ovftdb|00002030-200311210-00005SL00002030200317243711065404P112[Full Text]00002030-200311210-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_2437_caron_differentiation_|00002030-200511040-00009#xpointer(id(R37-9))|11065405||ovftdb|00002030-200311210-00005SL00002030200317243711065405P112[Medline Link]14600514ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2002_16_2447_joly_lipoatrophy_|00002030-200511040-00009#xpointer(id(R38-9))|11065213||ovftdb|00002030-200212060-00010SL00002030200216244711065213P113[CrossRef]10.1097%2F00002030-200212060-00010ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2002_16_2447_joly_lipoatrophy_|00002030-200511040-00009#xpointer(id(R38-9))|11065404||ovftdb|00002030-200212060-00010SL00002030200216244711065404P113[Full Text]00002030-200212060-00010ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2002_16_2447_joly_lipoatrophy_|00002030-200511040-00009#xpointer(id(R38-9))|11065405||ovftdb|00002030-200212060-00010SL00002030200216244711065405P113[Medline Link]12461419ovid.com:/bib/ovftdb/00002030-200511040-0000900005407_2004_292_191_gallant_antiretroviral_|00002030-200511040-00009#xpointer(id(R39-9))|11065213||ovftdb|00005407-200407140-00027SL00005407200429219111065213P114[CrossRef]10.1001%2Fjama.292.2.191ovid.com:/bib/ovftdb/00002030-200511040-0000900005407_2004_292_191_gallant_antiretroviral_|00002030-200511040-00009#xpointer(id(R39-9))|11065404||ovftdb|00005407-200407140-00027SL00005407200429219111065404P114[Full Text]00005407-200407140-00027ovid.com:/bib/ovftdb/00002030-200511040-0000900005407_2004_292_191_gallant_antiretroviral_|00002030-200511040-00009#xpointer(id(R39-9))|11065405||ovftdb|00005407-200407140-00027SL00005407200429219111065405P114[Medline Link]15249568ovid.com:/bib/ovftdb/00002030-200511040-0000900005407_2002_288_207_carr_substitution_|00002030-200511040-00009#xpointer(id(R40-9))|11065213||ovftdb|00005407-200207100-00025SL00005407200228820711065213P115[CrossRef]10.1001%2Fjama.288.2.207ovid.com:/bib/ovftdb/00002030-200511040-0000900005407_2002_288_207_carr_substitution_|00002030-200511040-00009#xpointer(id(R40-9))|11065404||ovftdb|00005407-200207100-00025SL00005407200228820711065404P115[Full Text]00005407-200207100-00025ovid.com:/bib/ovftdb/00002030-200511040-0000900005407_2002_288_207_carr_substitution_|00002030-200511040-00009#xpointer(id(R40-9))|11065405||ovftdb|00005407-200207100-00025SL00005407200228820711065405P115[Medline Link]12095385ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1999_13_2188_saint_discontinuing_|00002030-200511040-00009#xpointer(id(R41-9))|11065213||ovftdb|00002030-199910220-00035SL00002030199913218811065213P116[CrossRef]10.1097%2F00002030-199910220-00035ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1999_13_2188_saint_discontinuing_|00002030-200511040-00009#xpointer(id(R41-9))|11065404||ovftdb|00002030-199910220-00035SL00002030199913218811065404P116[Full Text]00002030-199910220-00035ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_1999_13_2188_saint_discontinuing_|00002030-200511040-00009#xpointer(id(R41-9))|11065405||ovftdb|00002030-199910220-00035SL00002030199913218811065405P116[Medline Link]10546885ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2004_35_274_wohl_hyperlactatemia_|00002030-200511040-00009#xpointer(id(R42-9))|11065213||ovftdb|00126334-200403010-00008SL0000522020043527411065213P117[CrossRef]10.1097%2F00126334-200403010-00008ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2004_35_274_wohl_hyperlactatemia_|00002030-200511040-00009#xpointer(id(R42-9))|11065404||ovftdb|00126334-200403010-00008SL0000522020043527411065404P117[Full Text]00126334-200403010-00008ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2004_35_274_wohl_hyperlactatemia_|00002030-200511040-00009#xpointer(id(R42-9))|11065405||ovftdb|00126334-200403010-00008SL0000522020043527411065405P117[Medline Link]15076242ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_971_mallon_antiretroviral_|00002030-200511040-00009#xpointer(id(R44-9))|11065213||ovftdb|00002030-200305020-00005SL0000203020031797111065213P119[CrossRef]10.1097%2F00002030-200305020-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_971_mallon_antiretroviral_|00002030-200511040-00009#xpointer(id(R44-9))|11065404||ovftdb|00002030-200305020-00005SL0000203020031797111065404P119[Full Text]00002030-200305020-00005ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_971_mallon_antiretroviral_|00002030-200511040-00009#xpointer(id(R44-9))|11065405||ovftdb|00002030-200305020-00005SL0000203020031797111065405P119[Medline Link]12700446ovid.com:/bib/ovftdb/00002030-200511040-0000900006024_2003_349_1993_moller_antiretroviral_|00002030-200511040-00009#xpointer(id(R45-9))|11065213||ovftdb|00006024-200311200-00003SL000060242003349199311065213P120[CrossRef]10.1056%2FNEJMoa030218ovid.com:/bib/ovftdb/00002030-200511040-0000900006024_2003_349_1993_moller_antiretroviral_|00002030-200511040-00009#xpointer(id(R45-9))|11065404||ovftdb|00006024-200311200-00003SL000060242003349199311065404P120[Full Text]00006024-200311200-00003ovid.com:/bib/ovftdb/00002030-200511040-0000900006024_2003_349_1993_moller_antiretroviral_|00002030-200511040-00009#xpointer(id(R45-9))|11065405||ovftdb|00006024-200311200-00003SL000060242003349199311065405P120[Medline Link]14627784ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_1179_moller_cardiovascular_|00002030-200511040-00009#xpointer(id(R46-9))|11065213||ovftdb|00002030-200305230-00010SL00002030200317117911065213P121[CrossRef]10.1097%2F00002030-200305230-00010ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_1179_moller_cardiovascular_|00002030-200511040-00009#xpointer(id(R46-9))|11065404||ovftdb|00002030-200305230-00010SL00002030200317117911065404P121[Full Text]00002030-200305230-00010ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2003_17_1179_moller_cardiovascular_|00002030-200511040-00009#xpointer(id(R46-9))|11065405||ovftdb|00002030-200305230-00010SL00002030200317117911065405P121[Medline Link]12819520ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2001_15_2441_duran_antiretroviral_|00002030-200511040-00009#xpointer(id(R47-9))|11065213||ovftdb|00002030-200112070-00012SL00002030200115244111065213P122[CrossRef]10.1097%2F00002030-200112070-00012ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2001_15_2441_duran_antiretroviral_|00002030-200511040-00009#xpointer(id(R47-9))|11065404||ovftdb|00002030-200112070-00012SL00002030200115244111065404P122[Full Text]00002030-200112070-00012ovid.com:/bib/ovftdb/00002030-200511040-0000900002030_2001_15_2441_duran_antiretroviral_|00002030-200511040-00009#xpointer(id(R47-9))|11065405||ovftdb|00002030-200112070-00012SL00002030200115244111065405P122[Medline Link]11740195ovid.com:/bib/ovftdb/00002030-200511040-0000900115314_2003_79_137_power_lipodystrophy_|00002030-200511040-00009#xpointer(id(R48-9))|11065213||ovftdb|00115314-200304000-00017SL0011531420037913711065213P123[CrossRef]10.1136%2Fsti.79.2.137ovid.com:/bib/ovftdb/00002030-200511040-0000900115314_2003_79_137_power_lipodystrophy_|00002030-200511040-00009#xpointer(id(R48-9))|11065404||ovftdb|00115314-200304000-00017SL0011531420037913711065404P123[Full Text]00115314-200304000-00017ovid.com:/bib/ovftdb/00002030-200511040-0000900115314_2003_79_137_power_lipodystrophy_|00002030-200511040-00009#xpointer(id(R48-9))|11065405||ovftdb|00115314-200304000-00017SL0011531420037913711065405P123[Medline Link]12690137ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2002_31_s140_ammassari_relationship_|00002030-200511040-00009#xpointer(id(R49-9))|11065213||ovftdb|00126334-200212153-00011SL00005220200231s14011065213P124[CrossRef]10.1097%2F00126334-200212153-00011ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2002_31_s140_ammassari_relationship_|00002030-200511040-00009#xpointer(id(R49-9))|11065404||ovftdb|00126334-200212153-00011SL00005220200231s14011065404P124[Full Text]00126334-200212153-00011ovid.com:/bib/ovftdb/00002030-200511040-0000900005220_2002_31_s140_ammassari_relationship_|00002030-200511040-00009#xpointer(id(R49-9))|11065405||ovftdb|00126334-200212153-00011SL00005220200231s14011065405P124[Medline Link]12562038Glucose metabolism, lipid, and body fat changes in antiretroviral-naive subjects randomized to nelfinavir or efavirenz plus dual nucleosidesDubé, Michael P; Parker, Robert A; Tebas, Pablo; Grinspoon, Steven K; Zackin, Robert A; Robbins, Gregory K; Roubenoff, Ronenn; Shafer, Robert W; Wininger, David A; Meyer, William A III; Snyder, Sally W; Mulligan, KathleenClinical Science1619