Galai, Noya PhD*; Vlahov, David PhD*†‡; Bareta, Joseph C. MS*; Wang, Cunlin MD*; Cohn, Sylvia MSc, MPH*; Sterling, Timothy R. MD*‡§
Numerous studies have shown that survival of HIV-infected individuals has improved since the introduction of highly active antiretroviral therapy (HAART).1-5 Other studies have concentrated on the effect of HAART on survival in the era after these therapies were available, with beneficial effects seen in those receiving medications versus those who have not.6,7 These earlier studies tended to be restricted to cohorts of hemophiliacs, homosexual men, or mixed populations. The extent to which these benefits may be observed in predominantly African-American injection drug users (IDUs) has received limited attention3,8 and remains an open question.
The CD4+ cell count is the most important marker of HIV disease progression and a strong predictor of survival, independent of HIV viral load.7,9 The use of CD4+ cell level as the primary means to evaluate survival among HIV-infected individuals is also supported by the observation that duration of infection has less prognostic value than the CD4+ cell count at a given point in time.10
Using HIV-related mortality rather than clinical AIDS11 as an outcome in studies of disease progression is appropriate, because many HIV-infected persons progress to severe immunosuppression and die without ever having been diagnosed clinically with AIDS. Also, death without clinical AIDS might occur because these patients have subclinical disease, have other symptoms that do not qualify clinically as "AIDS defining," or fail to seek and receive health care (or miss study visits), with their AIDS-defining diagnosis subsequently remaining unreported.
The purpose of the present study was to identify the risk factors for mortality among predominantly African-American IDUs separately at different CD4+ cell count levels, stratifying on calendar time before and after the introduction of HAART.
Participants were from the AIDS Linked to Intravenous Experiences (ALIVE) study in Baltimore, which has been described in detail elsewhere.12 The study started in 1988, with additional recruitments in 1994 and 1998, and has followed more than 3000 IDUs with semiannual visits. These visits have included a comprehensive interview to elicit behavioral and clinical information, a clinical examination, and venipuncture for laboratory assays.
The present analysis is based on 1030 HIV-infected ALIVE participants with CD4+ cell measurements below 500 cells/μL. Of these, 754 (73.2%) were HIV-positive at baseline and 276 (26.8%) seroconverted to HIV during follow-up. Five categories of CD4+ cell count were defined: 500 to 351, 350 to 201, 200 to 101, 100 to 51, and ≤50 CD4+ cells/μL. Entry into a CD4+ cell category was defined as the first date with a measurement at that specified level.13 Participants could contribute time to more than 1 group.
Outcome and Variables Definitions
The outcome of interest was HIV-related death, defined as death after an AIDS diagnosis or a diagnosis of another infectious disease such as sepsis or endocarditis. This definition was based on evidence that IDUs with HIV infection have an elevated risk of developing opportunistic and bacterial infections that are not necessarily AIDS defining.14,15 Non-HIV-related deaths, such as drug overdose or trauma, were considered as censored observations, based on the assumption that these cases would not be affected by stage of HIV disease or by antiretroviral therapy and thus would dilute the estimated effects. Liver disease was considered to be non-HIV related for the analysis, because about 90% of our cohort were already hepatitis C virus (HCV) infected at baseline, confounding the association between liver disease and HIV. Death outcomes were ascertained during clinical follow-up (66%) and through a search of the National Death Index through December 2000, with deaths coded through information on death certificates and review of medical records and medical examiner reports. The HAART era was defined as the calendar period starting from June 30, 1996. Data on constitutional symptoms, drug use, history of sexually transmitted disease (STD), and other clinical or medical history, including medications, were based on self-reports during face to face interviews.
HIV antibody was assayed using commercial assays utilizing standard interpretation. T-cell subset studies were performed using flow cytometry. HIV viral load assessments were obtained for a subset of the cohort (n = 408) and performed on stored specimens using a second-generation branched-DNA assay (Chiron Corp, Emeryville, CA).
Kaplan-Meier estimates were used to evaluate survival time from first entering a given CD4+ cell category to HIV-related death. The analysis was conducted in parallel for each of the 5 subgroups corresponding to CD4+ counts of 500 to 351, 350 to 201, 200 to 101, 100 to 51, and ≤50 cells/μL. These subgroups were partially overlapping, because a person could contribute time to more than 1 group, but the prognostic information used for each group was unique. Thus, the comparison across groups is descriptive in nature. The 5 groups represent different stages of HIV infection; for each, we describe the composition of the groups in terms of sociodemographic factors, past drug use behavior, clinical status, and treatment history. The 25th percentile of survival time was compared across categories, because this percentile could be estimated for all groups.
Separate Cox proportional hazards models were constructed to assess the independent effects on survival of various factors measured at or before the visit when participants first entered each CD4+ cell group. Comparisons of pre-HAART and HAART periods were done using a delayed entry model16 for the HAART era (included as a time-dependent factor); that is, for the pre-HAART period, observations were censored on June 30, 1996, and individuals who had follow-up in both periods entered the HAART era risk set at the time corresponding to the length of the interval spent from first reaching the given CD4+ cell count category until June 30, 1996. An additional variable was added to the models indicating participants whose complete follow-up since entering the CD4+ category was in the HAART era. Thus, the interpretation of the prognostic value of the various factors consistently refers to the survival time measured from first reaching a given CD4+ cell level interval. The final model was chosen to include all the covariates that were significant for at least 1 subgroup and was adjusted for age, gender, and a history of any anti-antiretroviral therapy at entry.
Because a question of interest was whether the effect of various factors differed in the HAART era compared with the pre-HAART era, exploratory multivariate models were run separately for these periods. Where a different effect was indicated, an interaction term (factor × period) was considered in the development of the multivariate models and competed for inclusion in the final models.
In this cohort of 1030 HIV-infected IDUs with CD4 cell counts below 500 cells/μL, a total of 424 deaths were observed during the 12 years of follow-up, 275 (64.9%) of which were HIV-related. The 149 non-HIV-related deaths were caused by drug overdose (56 [38%]), trauma (15 [10.1%]), neurologic (12 [8%]), cardiac failure (11 [7%]), liver failure (10 [7%]), cancer (10 [7%]), pulmonary (10 [7%]), renal failure (8 [5%]), chronic drug use (5 [3%]), and unknown (12 [8%]).
The study group was 22.3% female and 96.8% African-American. At enrollment, the median age was 34 years (range: 19-68 years) and the median number of years of injection drug use was 17 (interquartile range: 11-24 years).
Table 1 describes the profile of the groups on first entering each CD4+ cell category. As expected, the proportion of individuals having HIV symptoms or an AIDS diagnosis before entering a specific CD4+ cell category increased with the decline of CD4+ cell level. Parallel to this increase in symptoms was an increase in the proportion of participants who had a history of anti-antiretroviral therapy (predominantly monotherapy) and anti-Pneumocystis carinii pneumonia [PCP] medications (mostly prophylaxis).
Looking across the rows in Table 1, we observed a general decline in the percentage of individuals engaging in high-risk behaviors, including frequent drug injection (more than daily) and noninjection cocaine use, whereas crack use increased somewhat. Participation in methadone maintenance programs remained fairly stable at entry visits, whereas reports of being in detoxification programs decreased with CD4+ cell levels.
The progressive changes in laboratory markers across the CD4+ cell categories also follow patterns expected with HIV disease progression. Hemoglobin concentrations and CD8+ cell levels decreased with the decline of CD4+ values, whereas higher levels of HIV viral load were observed at lower CD4+ cell levels.
Table 2 and Figure 1 show the crude survival estimates by CD4+ cell category and calendar period before and after the introduction of HAART. The estimated crude mortality rates and the lower quartile of survival time are shown in Table 2. For example, the 25th percentile of survival for the highest CD4+ group (500-351 cells/μL) was 5.85 years before HAART and 9.53 years in HAART era. Similarly, for the lowest CD4+ group (≤50 cells/μL), the values were 1.03 years before HAART and 2.22 years in the HAART era.
Figure 1 shows the crude hazard ratios and 95% confidence intervals for survival for before versus after the introduction of HAART. Relative to the groups with CD4+ counts at entry greater than 200 cells/μL, the protective survival effect associated with being in the HAART era was stronger for the lower CD4+ cell group. The corresponding hazard ratios for HAART era versus the pre-HAART era in the specific CD4+ cell groups of 500 to 351, 350 to 201, 200 to 101, 100 to 51, and ≤50 cells/μL were 0.42, 0.36, 0.24, 0.21, and 0.25, respectively.
Table 3 shows the multivariate associations of prognostic factors with survival based on CD4+ category. HIV viral load was not included in these models because it was available for only approximately 40% of the participants at the index visit (see Table 1). Adjusted for age, sex, receipt of any prior antiretroviral therapy, and the factors shown in Table 1, being in the HAART era was associated with improved survival, with adjusted hazard ratios of 0.52, 0.35, 0.21, 0.20, and 0.39 for the CD4+ cell categories 351 to 500, 201 to 350, 101 to 200, 51 to 100, and ≤50 cells/μL, respectively. Participants whose index visit was after June 30, 1996, had additional highly significant survival benefit compared with those who started before HAART but had continued follow-up into HAART-era.
Prior hospitalization and AIDS diagnosis were independent consistent risk factors for HIV mortality, whereas outpatient/emergency room (ER) visits, sepsis or endocarditis, and alcohol use were significantly associated with higher mortality, specifically for the low CD4+ cell count group. Recently active versus former drug injection did not distinguish mortality in these groups. From the protective side, platelets were associated with better survival. Report of an STD at entry was a significant risk indicator among the higher CD4+ cell groups, and crack use was associated with better survival.
We found that most factors had nonsignificantly different effects in the period before and after HAART introduction. One exception was treatment with anti-PCP medications, which was strongly protective before HAART but a risk factor in the HAART period.
Results of a subanalysis that included plasma HIV viral load (categorized as above or below the median for each group) in addition to all the other variables in the final model indicated that higher viral load was a consistent significant prognostic factor for shorter survival, whereas treatment during the HAART era remained significantly protective (data not shown).
This study was based on data obtained from a community-based cohort of HIV-infected IDUs who were followed for a 12-year period. Because IDUs constitute a large HIV risk group, describing the population at different stages of disease, showing estimated subsequent survival before and after the introduction of HAART, and identifying prognostic factors is important for clinicians. IDUs who often belong to racial/ethnic minorities and have a low income and low education level have been less likely to use HIV care/treatment options.17-19 IDUs tend to have less advanced medication20 and to initiate treatment later in the course of infection than other groups infected with HIV.21-23 This limited access is likely to have an effect on their prognosis for survival. Further, the use of HAART in populations of IDUs is usually coupled with an effort to reduce or stop substance use, motivated by concerns over adherence, resistance, and possible interaction between illicit drugs or alcohol and antiretroviral medications. Therefore, it is of interest to evaluate the prognostic importance of clinical and behavioral factors that could help to guide clinicians who treat IDUs.
The clinical and behavioral profile of the cohort, evaluated when first reaching a specific stage of HIV progression, indicated that with increased prevalence of clinical disease and immunologic deterioration, there was a parallel decrease in substance abuse, including drug injection, alcohol consumption, and heavy smoking. This could be explained either by selective early mortality of the more severely dependent individuals24 or by the fact that as people become sicker, it becomes harder for them to maintain their addictive habits. These possible explanations are somewhat speculative. Still, more than one half of the participants reported drug injection in the 6 months before reaching a CD4+ count <50 cells/μL, and only a few were in drug treatment programs. These data demonstrate the chronic nature of drug abuse and the need to address both HIV infection and substance use addiction when treating this population.
The study showed that survival was longer in the HAART era than in the pre-HAART era. This increase in survival has been shown for numerous other populations and settings and associated with more advanced therapy as well as with increasing use of prophylaxis for HIV-related diseases.25-30 Thus, our findings based on African-American IDUs in a setting where the proportion receiving HAART is suboptimal, are consistent with data from other populations.
The focus of this analysis was not on differentiating the impact of HAART on survival but rather on considering whether prognostic indicators for HIV-related death differ by initial CD4+ cell level and by time (pre-HAART vs. HAART era).
Prognostic indicators for HIV-related death showed some predictable similarities and differences based on initial CD4+ cell level. For example, across CD4+ cell levels, a previous AIDS diagnosis28,31 or hospitalization in the 6 months before the entry visit was associated with shorter survival, reflecting a more advanced course of HIV-related disease. At lower CD4+ counts, endocarditis/sepsis was associated with shorter survival, which is consistent with more advanced clinical immunologic deterioration,32 suggesting that such patients require closer monitoring.
Several findings were counterintuitive. At higher CD4+ cell levels, STD was associated with shorter survival. Although STD is a cofactor for HIV transmission, evidence of STD as a cofactor for HIV progression has been mixed. That this association was seen only at higher CD4+ cell levels suggests that it may have been overwhelmed by other factors at lower CD4+ cell levels or that STD is a marker of a persistently risky lifestyle that presents markers for barriers to health-seeking behavior or access and adherence to care. That crack use was protective against HIV-related death was curious, because epidemiologic studies have demonstrated several adverse effects of crack33,34 and laboratory studies show that cocaine upregulates HIV and is associated with immune dysfunction.35 The crack use variable was not compared against abstinence, however, but was evaluated among persons with prior and current injection drug use. Persons able to use crack may have been less debilitated than persons who were not able to do so. Also, the effect of frequent alcohol use on mortality at low CD4+ cell levels needs to be further explored.
The differential survival between sociodemographic risk groups observed by others36 has been linked to the initial access and continuity of quality HIV-related care. Among our population of predominantly minority and impoverished drug-dependent individuals, sociodemographic factors did not differentiate survival. Outpatient or ER visits before entry into the lower CD4+ cell category were indicators of worse prognosis, however, in agreement with other findings in the United States,37 arguing that limited access to health care results in seeking medical help in the ER or in delayed entry into care.
Immunologic factors associated with mortality in our study included anemia and low platelet counts. These results are consistent with earlier studies showing anemia and thrombocytopenia to be more common in later stages of HIV infection and predictive of faster HIV progression.38,39
Prognostic indicators evaluated before and after 1996 had remarkably similar effects. No sociodemographic subgroup seemed to have experienced a differential change in survival in the period after the introduction of HAART, either as dramatically improved or substantially weakened. This may have been a result of limited power. There was, however, 1 indicator, anti-PCP therapy, which differentially predicted survival before and after the introduction of HAART. One possible consideration for this finding was that before HAART, this therapy was used primarily as prophylaxis, whereas it was used more for treatment of active disease afterward. This hypothesis needs more detailed examination, however. Thus, PCP therapy provides an example of a shift in prognostic indicators, and as HAART access, utilization, and adherence (with progressively less complicated regimens) expand, shifts in other prognostic indicators may become more apparent.
Since 1996, with the advent of HIV viral load testing and potent antiretroviral therapy, the focus on prognostic indicators has centered on viral load and CD4+ cell count almost to the exclusion of other variables that were included in analyses before 1996.38 This reflects the emergence of measures to establish the primacy of HIV's effect on clinical progression and the relative absence of lifestyle effects on HIV progression. Indeed, viral load is an important predictor for the subset in our cohort in which this was measured.40 Some studies indicate that in advanced stages of disease, HIV viral load does not add prognostic information beyond CD4+ cell counts and other clinical and immunologic factors, however.30,41 Recently, it has been suggested that in the HAART era, HIV viral load has lower prognostic value compared with previous years.27
In comparing persons in the same CD4+ cell stratum in the pre-HAART and HAART eras, improved survival in the HAART era was not evident until at least 4 years of follow-up in the group with CD4+ cell counts between 500 and 350 cells/μL and at least 2 years of follow-up in the CD4+ group with 200 to 350 cells/μL. Because most observational cohorts studies of disease progression on HAART published to date have had only 2 to 3 years of follow-up, our data suggest that differences in disease progression may become apparent after longer follow-up.7,28
In summary, our identification of prognostic indicators for survival in a large cohort of IDUs evaluated before and after the introduction of HAART provides information for clinicians managing HIV-infected patients in this population. Increased efforts are needed to make HIV treatment available to this patient population.
The authors thank Lisa Purvis, ALIVE Clinic Coordinator, for her ongoing and tireless work in keeping the study going and Dr. Joseph B. Margolick for performance of T-cell subset studies.
1. Mocroft A, Vella S, Benfield TL. Changing patterns of mortality across Europe in patients infected with HIV-1. Lancet. 1998;352:1725-1730.
2. Detels R, Munoz A, McFarlane G, et al. Effectiveness of potent antiretroviral therapy on time to AIDS and death in men with known HIV infection duration. JAMA. 1998;280:1497-1503.
3. Whitman S, Murphy J, Cohen M, et al. Marked declines in human immunodeficiency virus related mortality in Chicago in women, African-Americans, and injection drug users 1995-1997. Arch Intern Med. 2000; 160:365-369.
4. Palella FJ, Delaney KM, Moorman AC, et al. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infections. N Engl J Med. 1998;338:853-860.
5. Porta D, Rapiti E, Forastiere F, et al. Changes in survival among people with AIDS in Lazio, Italy from 1993 to 1998. AIDS. 1999;13:2125-2131.
6. Hogg RS, Yip B, Chan KJ, et al. Rates of disease progression by baseline CD4 cell count and viral load after initiating triple drug therapy. JAMA. 2001;286:2568-2577.
7. Sterling TR, Chaisson RE, Moore RD. HIV-1 RNA, CD4 T-lymphocytes and clinical response to highly active antiretroviral therapy. AIDS. 2001;15:2251-2257.
8. Poundstone K, Chaisson RE, Moore RD. Difference in HIV disease progression by injection drug use and by sex in the era of highly active antiretroviral therapy. AIDS. 2001;15:1115-1123.
9. Mellors JW, Munoz A, Giorgi JV, et al. Plasma viral load and CD4+ lymphocytes as prognostic markers of HIV-1 infection. Ann Intern Med. 1997;126:946-954.
10. Rezza G, Galai N, Pezzotti P, et al. Markers of response to zidovudine monotherapy among treated HIV seroconverters. Italian Seroconversion Study. Antivir Ther. 1997;2:167-174.
11. Jacobson LJ, Kirby AJ, Polk S, et al. Changes in survival after acquired immunodeficiency syndrome (AIDS) 1989-1991. Am J Epidemiol. 1993;138:852-869.
12. Vlahov D, Anthony JC, Munoz A, et al. The ALIVE study, a longitudinal study of HIV-1 infection in intravenous drug users: description of methods and characteristics of participants. NIDA Res Monogr. 1991;109:75-100.
13. Ehmann WC, Eyster ME, Wilson SE, et al. Relationship of CD4 lymphocyte counts to survival in a cohort of hemophiliacs infected with HIV. Multicenter Hemophilia Cohort Study. J Acquir Immune Defic Syndr Hum Retrovirol. 1994;7:1095-1098.
14. Manoff SB, Vlahov D, Herskovitz A, et al. Human immunodeficiency virus infection and infective endocarditis among injection drug users. Epidemiology. 1996;7:566-570.
15. Selwyn PA, Alcabes P, Hartel D, et al. Clinical manifestations and predictors of disease progression in drug users with human immunodeficiency virus infection. N Engl J Med. 1992;327:1697-1703.
16. Glesby MJ, Hoover DR. Survivor treatment selection bias in observational studies: examples from the AIDS literature. Ann Intern Med. 1996;124:999-1005.
17. Turner BJ, Fleishman JA, Wegner N, et al. Effects of drug abuse and mental disorders on use and type of antiretroviral therapy in HIV-infected persons. J Gen Intern Med. 2001;16:639-641.
18. Andersen R, Bozzette S, Shapiro M, et al. Access of vulnerable groups to antiretroviral therapy among persons in care for HIV disease in the United States. HCSUS Consortium. HIV Cost and Services Utilization Study. Health Services Res. 2000;35:389-416.
19. Junghans C, Low N, Chan P, et al. Uniform risk of clinical progression despite differences in utilization of highly active antiretroviral therapy. Swiss HIV Cohort Study. AIDS. 1999;13:2547-2554.
20. Celentano DD, Galai N, Sethi AK, et al. Time to initiation of highly active antiretroviral therapy among HIV-infected injection drug users. AIDS. 2001;15:1707-1715.
21. McKinney MM, Marconi KM. Delivering HIV services to vulnerable populations: a review of CARE ACT-funded research. Public Health Rep. 2002;117:99-113.
22. Crystal S, Sambamoorthi U, Moynihan PJ, et al. Initiation and continuation of newer antiretroviral treatments among Medicaid recipients with AIDS. J Gen Intern Med. 2001;16:850-859.
23. Hsu LC, Vittinghoff E, Katz MH, et al. Predictors of use of highly active antiretroviral therapy (HAART) among persons with AIDS in San Francisco, 1996-1999. J Acquir Immune Defic Syndr. 2001;28:345-350.
24. Galai N, Safaeian M, Vlahov D, et al. Longitudinal patterns of drug injection behavior in the ALIVE study cohort, 1988-2000: description and determinants. Am J Epidemiol. 2003;158:695-704.
25. CASCADE Collaboration. Changes in the uptake of antiretroviral therapy and survival in people with known duration of HIV infection in Europe: results from CASCADE. HIV Med. 2000;1:224-231.
26. Hendriks JCM, Craib KJP, Veugelers PJ, et al. Secular trends in the survival of HIV-infected homosexual men in Amsterdam and Vancouver estimated from a death-included CD4-staged Markov model. Int J Epidemiol. 2000;29:565-572.
27. Schwarcz SK, Hsu LC, Vittinghoff E, et al. Impact of protease inhibitors and other antiretroviral treatments on acquired immunodeficiency syndrome survival in San Francisco, California, 1987-1996. Am J Epidemiol. 2000;152:178-185.
28. Egger M, May M, Chene G, et al. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet. 2002;360:119-129.
29. Dore GJ, Li Y, McDonald A, et al. Impact of highly active antiretroviral therapy on individual AIDS-defining illness incidence and survival in Australia. J Acquir Immune Defic Syndr. 2002;29:388-395.
30. Coakley EP, Samore MH, Gillis JM, et al. The values of quantitative serum HIV-1 RNA levels and CD4 cell counts for predicting survival time among HIV-positive individuals with CD4 counts of < or = 50 × 10(6) cells/L. AIDS. 2000;14:1147-1153.
31. Macias J, Leal M, Delgado J, et al. Usefulness of route of transmission, absolute CD8+ T-cell counts and levels of serum tumor necrosis factor alpha as predictors of survival of HIV-1-infected patients with very low CD4+ T-cell counts. Eur J Clin Microbiol Infect Dis. 2001;20:253-259.
32. Wilson LE, Thomas DL, Astemborsky JB, et al. Prospective study of infective endocarditis among injection drug users. J Infect Dis. 2002;185:1761-1766.
33. Webber MP, Schoenbaum EE, Gourevitch MN, et al. A prospective study of HIV disease progression in female and male drug users. AIDS. 1999;13:257-262.
34. Vittinghoff E, Hessol NA, Bacchetti P, et al. Cofactors for HIV disease progression in a cohort of homosexual and bisexual men. J Acquir Immune Defic Syndr. 2001;27:308-314.
35. Nair MP, Chandha KC, Hewitt RG, et al. Cocaine differentially modulates chemokine production by mononuclear cells from normal donors and human immunodeficiency virus type 1-infected patients. Clin Diagn Lab Immunol. 2000;7:96-100.
36. Palacio H, Kahn JG, Richards TA, et al. Effect of race and/or ethnicity in use of antiretrovirals and prophylaxis for opportunistic infection: a review of the literature. Public Health Rep. 2002;117:233-251.
37. Montgomery JP, Gillespie BW, Gentry AC, et al. Does access to health care impact survival time after diagnosis of AIDS? AIDS Patient Care STDS. 2002;16:223-231.
38. Munoz A, Vlahov D, Solomon L, et al. Prognostic indicators for development of AIDS among intravenous drug users. J Acquir Immune Defic Syndr Hum Retrovirol. 1992;5:694-700.
39. Semba RD, Shah N, Klein RS, et al, for the Human Immunodeficiency Virus Epidemiology Research Study Group. Prevalence and cumulative incidence of and risk factors of anemia in a multicenter cohort study of human immunodeficiency virus-infected and -uninfected women. CID. 2002;34:260-266.
40. Vlahov D, Graham NMH, Hoover DR, et al. Prognostic indicators for AIDS and infectious disease death in HIV-infected injection drug users: plasma viral load and CD4+ cell count. JAMA. 1998;279:35-40.
41. Giorgi JV, Hultin LE, McKeating JA, et al. Shorter survival in advanced human immunodeficiency virus type 1 infection is more closely associated with T lymphocyte activation than with plasma virus burden or virus chemokine coreceptor usage. J Infect Dis. 1999;179:859-870.
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