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. Author manuscript; available in PMC: 2013 Jul 19.
Published in final edited form as: J Int Assoc Provid AIDS Care. 2013 Feb 19;12(4):270–277. doi: 10.1177/1545109712469684

Predictors of Clinical Progression in HIV-1-Infected Adults Initiating Combination Antiretroviral Therapy with Advanced Disease in the Asia-Pacific Region: Results from the TREAT Asia HIV Observational Database

H Byakwaga 1, K Petoumenos 1, J Ananworanich 2, F Zhang 3, M A Boyd 1, T Sirisanthana 4, P C K Li 5, C Lee 6, C V Mean 7, V Saphonn 7, S F S Omar 8, S Pujari 9, P Phanuphak 2, P L Lim 10, N Kumarasamy 11, Y M A Chen 12, T P Merati 13, S Sungkanuparph 14, R Ditangco 15, S Oka 16, G Tau 17, J Zhou 1, M G Law 1, S Emery 1
PMCID: PMC3716846  NIHMSID: NIHMS464478  PMID: 23422741

Abstract

The majority of HIV-infected patients in developing countries commences combination antiretroviral therapy (cART) with advanced disease. We examined predictors of disease progression in patients initiating cART with CD4 count ≤200 cells/mm3 in the TREAT Asia HIV Observational Database. The main outcome measure was progression to either an AIDS-defining illness or death occurring 6 months after initiation of cART. We used survival analysis methods. A total of 1255 patients contributed 2696 person years of follow-up; 73 were diagnosed with AIDS and 9 died. The rate of progression to the combined end point was 3.0 per 100 person years. The factors significantly associated with a higher risk of disease progression were Indian ethnicity, infection through intravenous drug use, lower CD4 count, and hemoglobin ≤130 g/dL at 6 months. In conclusion, measurements of CD4 count and hemoglobin at month 6 may be useful for early identification of disease progression in resource-limited settings.

Keywords: HIV, disease progression, antiretroviral therapy, resource-limited settings

Background

The increasingly widespread use of combination antiretroviral therapy (cART) since 1996 for the treatment of HIV infection has led to significant reductions in morbidity and mortality in HIV-infected patients. As a result, the prognosis of HIV-infected individuals has improved substantially.14 In recent years, global efforts to expand access to cART have increased significantly. By the end of 2008, about 4 million people were receiving treatment with antiretroviral therapy (ART) in low-to middle-income countries, a 10-fold increase over the preceding 5 years.5 However, in resource-limited settings in Africa, Asia, and South America, where 90%of the people with HIV/AIDS live, access to cART is still limited and the majority of the patients initiates therapy with advanced disease.6,7 Although virologicl and immunologicl responses to ART observed among HIV-1-infected individuals treated in low-income and high-income countries are similar,68 the mortality in low-income countries is approximately 4 times that observed in high-income countries.6

Guidelines and recommendations for commencement of ART are based mainly on CD4 T-lymphocyte count. In high-income countries, plasma HIV RNA load is also considered. These thresholds have been selected based on the risk of disease progression in both prospective and randomized controlled studies.912 Although current ART guidelines recommend the initiation of therapy in patients with AIDS-defining illness, or CD4 count <500 cells/mm3,13 the majority of patients in low-income countries commences ART with advanced disease and with CD4 count <200 cells/mm3.6 Previous studies have shown that the risk of HIV disease progression for individuals commencing ART with CD4 count ≤200 cells/mm3 is generally double the risk for those commencing at CD4 count of 350 cells/mm3.11

Understanding the factors that predict disease progression in these patients commencing cART with advanced disease could facilitate therapeutic monitoring decisions especially in those settings where laboratory testing is not readily available. In this study, we aimed to determine the predictors of progression to either an AIDS-defining illness or death occurring between 6 months and 2 years after initiation of cART in patients initiating cART with CD4 count ≤200 cells/mm3 in the TREAT Asia HIV Observational Database (TAHOD).

Methods

The TAHOD is a collaborative cohort study currently involving 17 sites in the Asia-Pacific region (see Appendix A). Details of the study methodology have been published elsewhere.14 In brief, approximately 200 patients were recruited from each participating clinical site. These included both ART-naive patients and those receiving ART. Recruitment was based on a consecutive series of patients attending regularly at the given site from a particular start-up time. The study was approved by the University of New South Wales Human Research Ethics Committee and by a local ethics committee for each participating site. The data collected included patient demographics: age, sex, and ethnicity; clinical information: weight, height, exposure category, AIDS-defining illness, deaths, past and present antiretroviral (ARV) regimen, and hepatitis status; laboratory measurements: CD4 counts and hemoglobin measurements.

Patients were included in this analysis if they started the first cART regimen after January 1, 1997 and had available CD4 count data at baseline and after 6 months of cART. We used a combined end point of progression to either a new AIDS-defining illness or death occurring between 6 months and 2 years after initiation of cART. We only considered the first AIDS illness that the patient developed during this period of analysis. A modified version of the 1993 US Centers for Disease Control and Prevention AIDS case definition15 was adopted, in which a presumptive diagnosis was available for most illnesses. Deaths from all causes were included. We defined cART as the use of 3 or more ARV agents.

Covariates included patient characteristics at the start of cART: age, sex, exposure category, Hepatitis B surface antigen status (HBV), antihepatitis C virus (HCV) antibody status (note: patients were classified as HBV positive and or HCV positive if they ever had a positive test result), history of previous AIDS illness, body mass index (BMI; calculated as the weight in kilograms divided by the square of the height in meters), CD4 count, and hemoglobin level. We also examined the patient characteristics following 6 months of cART and these included BMI, CD4 count, hemoglobin level, development AIDS illness within the first 6 months of cART, CD4 level after 6 months of cART, and the absolute change in CD4 count within the first 6 months of cART. Because of the changes in trends of treatment, prophylaxis of opportunistic infections, choice of drugs, and diagnostic tests over the period of analysis, we stratified treatment periods into 2 periods: before the year 2000, to represent the period of early use of cART and the second period was >2000 to March 2007 to represent the later use of cART.

Predictors for progression to AIDS or death were assessed by univariable and multivariable analyses using survival analysis. We considered the follow-up as a period from the date cART was initiated (baseline) to the time of first diagnosis of new AIDS illness, and date of death from any cause or the last follow-up visit before 2 years for patients who did not experience clinical progression. The multivariable model was determined using both the forward stepwise and the backward stepwise approaches, considering only covariates that were significant at the 0.10 level in the univariable analysis. The final multivariable model included only covariates that remained significant at the 0.05 level. Analyses were performed using the statistical package STATA version 10 for Windows (StataCorp, College Station, Texas).

Results

Of the 3516 patients recruited to the TAHOD by March 2007, 1664 initiated cART after January 1, 1997 and had available CD4 count data at baseline and after 6 months of therapy. A total of 1255 (75.4%) patients commenced cART with baseline CD4 count ≤200 cells/mm3 were included in this analysis. Table 1 summarizes the characteristics of these patients at commencement of cART. The majority (886, 71%) of the patients were men, with a median age of 36 years (interquartile range [IQR], 32–42 years). The main populations were 527 (42%) Chinese, 310 (25%) Thai, and 193 (15%) Indian. Overall, the majority of patients, 1013 (81%), was infected through heterosexual contact. At initiation of cART, 638 (51%) of the patients had a history of prior AIDS-defining illness, the median CD4 count at commencement of cART was 63 (IQR, 25–130) cells/mm3, the median hemoglobin was 120 (IQR, 106–133) mg/dL, and the median BMI was 19.9 (IQR, 17.8–22.1) kg/m2. In all, 79% of the patients commenced cART after the year 2000. The median CD4 count after 6 months of cART was 175 (IQR, 106–268) with a mean CD4 count increase of 122 (standard deviation, 105) cells/mm3. In all, 76 (6%) patients developed a new AIDS-defining illness within the first 6 months of cART (Table 2).

Table 1.

Patient Characteristics at the Start of Combination Antiretroviral Therapy

No. of Patients %
Total 1255 100.0
Sex
 Male 886 70.6
 Female 369 29.4
Ethinicity
 Chinese 527 42.0
 Indian 193 15.4
 Thai 310 24.7
 Other 225 17.9
Mode of infection
 Heterosexual 1,013 80.7
 Homosexual 125 10.0
 IDU only 27 2.2
 Other 90 7.2
Prior AIDS illness
 No 617 49.2
 Yes 638 50.8
Year of cART start
 ≤2000 264 21.0
 >2000 991 79.0
HBsAg
 Negative 660 52.6
 Positive 102 8.1
 Not tested 493 39.3
HCV antibody
 Negative 641 51.1
 Positive 70 5.6
 Not tested 544 43.4
Median age, y (IQR) 36 (31–42)
Median CD4 count, cells/mm3 (IQR) 63 (25–130)
Median BMI,a kg/m2 (IQR) 19.9 (17.8–22.1)
Median hemoglobinears,a mg/dL (IQR) 120 (106–133)

Abbreviations: IDU, intravenous drug use; cART, combination antiretroviral therapy; HbSAg, Hepatitis B surface antigen; HCV, hepatitis C virus; IQR, interquartile range; BMI, body mass index.

a

Number of patients (%) missing body mass index and hemoglobin measurements at baseline: 610 (48.6%) and 256 (20.4%), respectively.

Table 2.

Patient Characteristics 6 Months after Initiation of Combination Antiretroviral Therapy

No. of Patients %
AIDS event in first 6 months
 No 1179 93.9
 Yes 76 6.1
CD4 count after 6 months of cART, cells/mm3
 ≤50 74 5.9
 51–100 205 16.3
 101–200 451 35.9
 >200 525 41.8
CD4 change from baseline at month 6, cells/mm3
 ≤50 286 22.8
 51–100 347 27.7
 101–200 398 31.7
 >200 224 17.9
Hemoglobin after 6 months of cART, mg/dL
 ≤80 14 1.1
 81–130 508 40.5
 >130 502 40.0
 Missing 231 18.4

Abbreviation: cART, combination antiretroviral therapy.

During a follow-up period of 2696 person years, 73 patients were diagnosed with a new AIDS-defining illness and 9 died. Among the 73 new AIDS-defining illnesses, the most frequent diagnoses were Mycobacterium tuberculosis (either pulmonary or extra pulmonary) 25 (36%), chronic herpes simplex 8 (11%), and Pneumocystis jiroveci pneumonia 7 (10%).

The rate of progression to the combined end point (AIDS or death) was 3.0 per 100 person years. In multivariable analysis, a lower CD4 count at 6 months from the start of cART was significantly associated with a greater risk of disease progression (Table 3). Individuals with injection drug use as mode of HIV transmission were 3.31 times more likely to develop a new AIDS illness or die in comparison to those who acquired HIV infection through heterosexual transmission (95%confidence interval [CI], 1.33–8.24, P = .01), Indian patients were 2.64 times more likely to progress to AIDS or death compared to the Chinese (95% CI, 1.46–4.77, P = .001), and individuals with a hemoglobin level greater than 130 mg/dL at 6 months from the start of cART had a 27% lesser risk of clinical progression compared to those with a hemoglobin level less than 80 mg/dL (95% CI, 0.08–0.90, P = .034).

Table 3.

Univariable and Multivariable Predictors of AIDS or Death Using Cox Proportional Hazards Model

No. of events Person Years Rate,/100 pys Univariable
Multivariable
HR (95% CI) P HR (95% CI) P
Total 82 2696
Sex
 Male 64 1920.0 3.33 1.00
 Female 18 776.1 2.32 0.69 (0.41–1.17) .168 0.74 (0.44–1.25) .260
Age, y
 ≤35 35 1307.0 2.68 1.00
 >35 47 1389.1 3.38 1.26 (0.82–1.96) .295 1.25 (0.80–1.93) .326
Ethinicity
 Chinese 32 1191.9 2.68 1.00
 Indian 20 418.3 4.78 1.83 (1.05–3.19) .034 2.64 (1.46–4.77) .001
 Thai 16 695.6 2.30 0.87 (0.48–1.58) .648 0.90 (0.49–1.63) .720
 Other 14 390.3 3.59 1.26 (0.67–2.37) .469 1.34 (0.71–2.51) .370
Mode of infection
 Heterosexual 63 2196.1 2.87 1.00
 Homosexual 11 272.6 4.03 1.14 (0.74–2.68) .292 1.59 (0.83–3.03) .160
 IDU only 5 46.5 10.76 3.64 (1.46–9.07) .005 3.31 (1.33–8.24) .010
 Other 3 180.9 1.66 0.56 (0.18–1.80) .334 0.58 (0.18–1.83) .350
Prior AIDS illness
 No 40 1305.7 3.06 1.00
 Yes 42 1390.5 3.02 0.99 (0.64–1.52) .956 0.90 (0.58–1.39) .629
Year of cART start
 ≤2000 19 629.4 3.02 1.00
 >2000 63 2066.8 3.05 0.99 (0.59–1.66) .983 1.10 (0.65–1.84) .723
CD4 count before start of cART, cells/mm3
 ≤50 42 1182.2 3.55 1.00
 51–100 17 569.9 2.98 0.85 (0.48–1.49) .561 1.06 (0.59–1.91) .837
 101–200 23 944.0 2.44 0.69 (0.42–1.15) .154 1.08 (0.59–1.98) .798
Baseline hemoglobin, mg/dL
 ≤80 4 64.7 6.18 1.00
 81–130 43 1453.1 2.96 0.49 (0.17–1.35) .167 0.53 (0.19–1.480 .225
 >130 17 609.0 2.79 0.45 (0.15–1.35) .156 0.52 (0.17–1.55) .241
 Missing 18 569.3 3.16 0.53 (0.18–1.56) .250 0.64 (0.21–1.90) .419
BMI before start of cART, kg/m2
 ≤18.5 15 462.3 3.24 1.00
 18.6–24.9 20 760.1 2.63 0.82 (0.42–1.61) .567 0.86 (0.44–1.68) .662
 >24.9 1 111.4 0.90 0.28 (0.04–2.14) .221 0.30 (0.04–2.28) .245
 Missing 46 1362.3 3.38 1.06 (0.59–1.90) .842 1.12 (0.62–2.00) .707
Antiretroviral treatment (ARV)
 2 NRTIs + PI 19 618.5 3.07 1.00
 2 NRTIs + NNRTI 60 2024.8 2.96 0.96 (0.57–1.61) .874 1.02 (0.61–1.71) .942
 Others 3 52.9 5.67 1.83 (0.54–6.20) .329 1.67 (0.50–5.70) .401
CD4 count after 6 months of cART, cells/mm3
 ≤50 13 152.4 8.53 1.00
 51–100 15 454.3 3.30 0.38 (0.18–0.81) .012 0.38 (0.18–0.81) .012
 101–200 29 972.4 2.98 0.35 (0.18–0.67) .002 0.35 (0.18–0.67) .002
 >200 25 1117.1 2.24 0.26 (0.14–0.52) .001 0.26 (0.14–0.52) .001
Hemoglobin after 6 months of cART, mg/dL
 ≤80 3 25.0 12.02 1.00
 81–130 35 1065.8 3.28 0.27 (0.08–0.89) .032 0.32 (0.10–1.05) .059
 >130 30 1088.6 2.76 0.23 (0.07–0.76) .016 0.27 (0.08–0.90) .034
 Missing 14 516.7 2.71 0.23 (0.07–0.80) .021 0.29 (0.08–1.03) .056
AIDS event in first 6 months
 No 73 2535.4 2.88 1.00
 Yes 9 160.8 5.60 1.97 (0.99–3.94) .055 1.76 (0.88–3.54 .111

Abbreviations: IDU, intravenous drug use; cART, combination antiretroviral therapy; HbSAg, Hepatitis B surface antigen; HCV, hepatitis C virus; IQR, interquartile range; BMI, body mass index; ART, antiretroviral therapy; CI, conficence interval; NNRTI, nonnucleoside reverse transcriptase inhibitor; NRTI, nucleoside reverse transcriptase inhibitor; PI, protease inhibitor.

The CD4 count and hemoglobin level at the start of cART were not found to be associated with disease progression. In this study, there was no association found between HIV disease progression and other covariates that were examined; these included baseline BMI, history of AIDS illness prior to commencing cART, ART regimen, and AIDS illness occurring within the first 6 months.

Discussion

In this study of HIV-1-infected adults initiating cART with advanced disease, CD4 count and hemoglobin levels at month 6 were associated with disease progression. Individuals who acquired HIV through injection drug use were more likely to develop a new AIDS illness or die in comparison with those who acquired HIV infection through heterosexual transmission, and Indian patients had a greater risk of disease progression compared with Chinese patients. Patient characteristics at the commencement of cART, including BMI, hemoglobin, and CD4 count, were not found to be associated with disease progression.

The association of CD4 count with HIV disease progression was described early in the HIV epidemic16 and its role in predicting HIV disease progression was defined by data from a number of prospective studies.912 Baseline CD4 count has been shown to be the most significant predictor of HIV disease progression2,17 and survival prior to the commencement of cART. Consequently, current ART guidelines recommend ART initiation based on CD4 count in preference to any single marker.5,18 However, in the majority of patients, remarkable rises in CD4 count are observed within months following initiation of cART19,20 and the predictive role of baseline CD4 count may perhaps decrease.9,2124 Data from the studies investigating specific AIDS-defining illnesses suggest that the current CD4 count compared with the CD4 count at the start of therapy is more useful in predicting the occurrence of clinical disease in HIV patients receiving cART.2527 Results from our study are similar to the findings from previous studies which showed that after starting cART, the CD4 count following 6 months of cART was a better prognostic factor for HIV clinical progression compared with baseline CD4 count.9,23,28

Despite increased access to HIV treatment in developing countries, the costs of CD4 count and HIV-RNA monitoring remain relatively high. Therefore, parameters that are easy to measure have been investigated as surrogate makers that may be useful in monitoring therapy in these countries. The decrease in hemoglobin levels has been correlated with reducing CD4 counts, and monitoring hemoglobin levels has been shown to be useful in predicting disease progression.2934 Generally, initiation of cART is associated with an increase in hemoglobin levels.29,32 Our findings are consistent with those of a previous report suggesting that in a patient population receiving cART, the most recent hemoglobin level is a stronger predictor of disease progression.32 The BMI is a simple measure and has also been shown to predict disease progression in some studies.3335 A rapid decline in BMI is observed in the 6 months preceding AIDS35 and a low BMI persistently less than 17 kg/m2 6 months after the start of cART has been associated with a 2-fold increase in the risk of death.36 Although BMI decline may be a useful marker of progression to AIDS, the sensitivity of this measure is only about 33%.37 In other words, weight loss is only noted in about one-third of the HIV-infected individuals who develop AIDS; however, if weight loss is present, it is predictive for AIDS.

We observed that patients with injection drug use as mode of HIV transmission had a greater risk of disease progression compared with those who acquired HIV through heterosexual transmission. This finding is similar to findings from previous studies which showed that the rate of clinical progression was higher in patients infected through injection drug use compared with those infected through other routes.2,23 Independent of HIV infection, these patients are known to have increased risk of death from other causes including overdose and violent causes.38,39

Similar to previous reports from studies of HIV-infected patients in the Asia-Pacific region, tuberculosis was the most frequently occurring AIDS-defining diagnosis.14,40,41 The risk and prognostic significance of tuberculosis for patients enrolled in TAHOD has been published elsewhere.40 In a report of HIV-infected patients receiving cART in programs in sub-Saharan Africa, it accounted for up to 21% of all the deaths.42 Other commonly occurring AIDS-defining illnesses in this study were chronic herpes simplex and P jiroveci pneumonia. Although there was a high occurrence of AIDS-defining illnesses within the first 6 months of commencing cART in this cohort of patients, it was not significantly associated with an increased risk of subsequent disease progression. This may in part be due to the fact that by month 6, 42% of the patients had achieved a CD4 count greater than 200 cells/mm3 and 22% of the patients had a CD4 count less than 100 cells/mm3 compared with 64% at the start of cART. The cause of the greater morbidity and mortality observed within the first 6 months after initiation of ART6,42 is not fully known but immune restoration disease is postulated to play a significant role.4244 Immune restoration disease is particularly common in low-income countries, where HIV-infected individuals have a higher prevalence of comorbidities; yet, resources for diagnostic facilities, prophylaxis, and effective treatment of opportunistic infections are limited. Moreover, individuals who have high immunodeficiency at the start of cART, as included in this study, are at a greater risk of developing immune restoration disease.45

This study has a number of possible limitations. First, some of the factors that have been associated with HIV disease progression in the previously published literature were not found to be associated with disease progression in this study. This may be due to the limited power of this analysis as a result of the small number of participants and end points. Second, we were not able to examine the effect of opportunistic infection prophylaxis on clinical progression because prophylaxis information was not regularly documented in this cohort. Third, viral load measurements, an important prognostic factor of disease progression, were not consistently available and therefore were not incorporated in this analysis.

In conclusion, results from this study suggest that measurement of the CD4 count and hemoglobin level after the first 6 months of cART may be useful for early identification of subsequent risk of HIV clinical progression in patients who commences cART with advanced disease. Our findings contribute to data in the Asia-Pacific region and are especially important in resource-limited settings where the majority of patients commences cART with advanced disease and routine plasma HIV viral and CD4 count monitoring are not readily available.

Acknowledgments

The TREAT Asia HIV Observational Database is part of the Asia-Pacific HIV Observational Database and is an initiative of TREAT Asia, a program of amfAR, The Foundation for AIDS Research, with support from the National Institute of Allergy and Infectious Diseases (NIAID) of the US National Institutes of Health (NIH) as part of the International Epidemiologic Databases to Evaluate AIDS (IeDEA; grant No. U01AI069907), and from the Dutch Ministry of Foreign Affairs through a partnership with Stichting Aids Fonds. The National Centre in HIV Epidemiology and Clinical Research is funded by the Australian Government Department of Health and Ageing, and is affiliated with the Faculty of Medicine, The University of New South Wales. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of any of the institutions mentioned above.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Appendix A

The TREAT Asia HIV Observational Database

C. V. Mean, V. Saphonn,* and K. Vohith, National Center for HIV/AIDS, Dermatology & STDs, Phnom Penh, Cambodia; F. J. Zhang,* H. X. Zhao, and N. Han, Beijing Ditan Hospital, Beijing, China; P. C. K. Li*† and M. P. Lee, Queen Elizabeth Hospital, Hong Kong, China; N. Kumarasamy* and S. Saghayam, YRG Centre for AIDS Research and Education, Chennai, India; S. Pujari* and K. Joshi, Institute of Infectious Diseases, Pune, India; T. P. Merati* and F. Yuliana, Faculty of Medicine Udayana University & Sanglah Hospital, Bali, Indonesia; E. Yunihastuti* and O. Ramadian, Working Group on AIDS Faculty of Medicine, University of Indonesia/Ciptomangunkusumo Hospital, Jakarta, Indonesia; S. Oka* and M. Honda, International Medical Centre of Japan, Tokyo, Japan; J. Y. Choi* and S. H. Han, Division of Infectious Diseases, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea; C. K. C. Lee* and R. David, Hospital Sungai Buloh, Kuala Lumpur, Malaysia; A. Kamarulzaman* and A. Kajindran, University of Malaya Medical Centre, Kuala Lumpur, Malaysia; G. Tau,* Port Moresby General Hospital, Port Moresby, Papua New Guinea; R. Ditangco* and R. Capistrano, Research Institute for Tropical Medicine, Manila, Philippines; Y. M. A. Chen,* W. W. Wong, and Y. W. Yang, Taipei Veterans General Hospital and AIDS Prevention and Research Centre, National Yang-Ming University, Taipei, Taiwan; P. L. Lim,* O. T. Ng, and E. Foo, Tan Tock Seng Hospital, Singapore; P. Phanuphak* and M. Khongphattanayothin, HIV-NAT/Thai Red Cross AIDS Research Centre, Bangkok, Thailand; S. Sungkanuparph* and B. Piyavong, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand; T. Sirisanthana*‡ and W. Kotarathititum, Research Institute for Health Sciences, Chiang Mai, Thailand; A. H. Sohn,* L. Messerschmidt,* and B. Petersen, The Foundation for AIDS Research, Bangkok, Thailand; J. Chuah,* Gold Coast Sexual Health Clinic, Miami, Queensland, Australia; D. A. Cooper, M. G. Law,* K. Petoumenos, and J. Zhou,* National Centre in HIV Epidemiology and Clinical Research, The University of New South Wales, Sydney, Australia. *TAHOD Steering Committee member; †Steering Committee Chair; ‡co-Chair.

Footnotes

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Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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