Literature DB >> 30349207

Adherence to antiretroviral therapy among HIV/ AIDS patients in the context of early treatment initiation in Vietnam.

Hue Thi Mai1, Giang Minh Le1,2, Bach Xuan Tran1,3,4, Ha Ngoc Do5, Carl A Latkin3, Luong Thanh Nguyen6, Thao Phuong Thi Thai7,8, Huong Thi Le9, Anh Toan Ngo10, Cuong Tat Nguyen11, Cyrus Sh Ho12, Roger Cm Ho13.   

Abstract

PURPOSE: This study aimed to assess the antiretroviral therapy (ART) compliance among patients with HIV/AIDS and its associated factors in the context of universal ART initiation in Vietnam. PATIENTS AND METHODS: A cross-sectional survey was conducted in five ART clinics located in three provinces, such as Hanoi, Thanh Hoa, and Lao Cai, from July to September 2017. Overall, adherence to ART in the last month was measured using a 100-point Visual Analog Scale (VAS). Besides, information about forgetting doses in the last 4 days and delaying taking pills in the last 7 days was also reported.
RESULTS: Among 482 patients, the suboptimal adherence rate was 54.5%. Noncurrent smoking (coefficient =4.19, 95% CI 0.42-7.97), higher baseline CD4 count (coefficient =4.35, 95% CI 0.58-8.13), and no traveling difficulties (coefficient =6.17, 95% CI 2.27-10.06) were predictors of higher VAS adherence score. Suboptimal adherence was associated with mountainous residence (OR =5.34, 95% CI 2.81-10.16). Female respondents were less likely to delay taking pills in the last 7 days (OR =0.19, 95% CI 0.07-0.52).
CONCLUSION: Our study embraced early ART initiation in Vietnam; however, this approach should be parallel with appropriate resource allocation and service delivery.

Entities:  

Keywords:  ART adherence; HIV/AIDS; VAS; Visual Analog Scale; antiretroviral therapy

Year:  2018        PMID: 30349207      PMCID: PMC6188958          DOI: 10.2147/PPA.S175474

Source DB:  PubMed          Journal:  Patient Prefer Adherence        ISSN: 1177-889X            Impact factor:   2.711


Introduction

HIV/AIDS has now evolved from an acute fatal disease to a chronic illness thanks to the extensive antiretroviral therapy (ART) access.1 This treatment reduces mortalities, morbidities, and opportunistic infections and prolongs survival.2,3 In addition, it helps to reduce HIV transmission in the community.4,5 Therefore, enhancing ART coverage is a principle strategy to end HIV/AIDS. Until June 2017, there were more than 20.9 million HIV/AIDS individuals enrolling in ART program.6 In 2015, the WHO promulgated a consolidated ART treatment guideline, promoting the universal ART access for all HIV-positive individuals regardless of CD4 cell count.7 Vietnam has adopted WHO’s recommendations since 2017 with the decision number, 5418/QD-BYT, issued by the Ministry of Health.8 These efforts have shown the strong commitment to the “90–90–90 goals” toward ending the AIDS epidemic by 2030.9 However, this strategy is subjected to new challenges in the context of shrunken funds for HIV/AIDS control in Vietnam. Previously, approximately 95% of antiretroviral (ARV) drugs were funded by international organizations and only 5% from the government budget.10 However, international funding resources have been speedily cut in recent years. Thus, early ART initiation may create greater financial burdens among HIV patients. Moreover, being enrolled in ART at healthy stage possibly leads to disease optimism. A previous study suggested that “feeling healthy” is a strong predictor of ART refusal.11 Although many studies in Vietnam have assessed the levels of ART adherence,12,13 the potential mechanisms of how early ART eligibility may predict the levels of ART adherence have not been well studied. Therefore, our study aimed to assess the levels of ART adherence and associated factors among HIV/AIDS patients in the context of universal ART in Vietnam.

Patients and methods

Study settings

A cross-sectional study was conducted from July to September 2017 in three provinces: Ha Noi, Thanh Hoa, and Lao Cai. Hanoi represented an area with a diversity of HIV risk behaviors including unsafe sex practice and drug injection. Thanh Hoa represented a setting with the high prevalence of drug trafficking. Lao Cai is the embodiment of the mountainous area with the complexity of HIV risk behaviors as well as illicit drug trafficking due to a large border with other countries. Five chosen ART clinics included the following: Thanh Hoa Provincial HIV/AIDS Control Center, Quang Xuong General Hospital, Ung Hoa General Hospital, Ba Vi General Hospital, Bao Thang General Hospital. The first clinic was the provincial level, and the remaining clinics were the district level.

Study design and patient recruitment

We selected patients based on the following criteria: 1) being at least 18 years old, 2) being present during the study period, 3) having ARV treatment at chosen clinics, 4) agreeing to involve in the study, 5) not having cognitive disabilities. All the eligible patients were clearly explained about the study purposes. If they agreed to participate in the study, they were asked to provide a written informed consent to confirm their participation. There were 482 patients participating in the study.

Measures and instrument

A structured questionnaire was used for 20-minute face-to-face interviews. The collected information is given in the following sections.

Sociodemographic characteristics

Sociodemographic characteristics were as follows: age, location, marital status, education, employment, and travel difficulties.

Clinical characteristics

Data on Visual Analog Scale (VAS) adherence score, forgetting pills in the last 4 days, delaying taking pills in the last week were collected. We used 100-point VAS with 0 indicating “absolute non-adherence” and 100 indicating “excellent adherence” in the last 30 days.14 VAS score equaling to at least 95% was defined as “optimal adherence”; otherwise, it was considered “suboptimal adherence.”15 Besides, the patients were asked whether they delayed taking pills in the last 7 days. Moreover, we asked patients to report HIV/ AIDS stages, ART duration, and ART treatment satisfaction. Data on initial/last CD4 count were extracted from patients’ medical records.

Risk behaviors

We collected information regarding current smoking, alcohol dependence, history of drug use/drug injection, and current drug use. Alcohol Use Disorders Identification Test-Consumption (AUDIT-C) was utilized to screen alcohol dependence with score ranging from 0 to 12. Patients were characterized as hazard drinkers if the score was 4 or above in males and 3 or above in females.16 Current tobacco use was defined if patients smoked in the last 30 days.

Statistical analyses

Data were cleaned and analyzed by Stata (version 12; Stata-Corp LP, College Station, TX, USA). Missing data were handled using list-wise deletion strategy.17 To identify differences between men and women, we utilized Mann–Whitney U, chi-squared, and Fisher’s exact tests. Multivariate Tobit and logistic regression models were used to detect potential predictors of VAS adherence score, suboptimal adherence, and delayed taking pills in the last week. A stepwise backward model with P-value of <0.2 was used to reduce the regression models. Results were considered statistically significant if P-value was <0.05.

Ethical considerations

The study protocol was reviewed and approved by the institutional review board of Hanoi Medical University. Patients’ personal information was completely confidential, and they could stop interviewing at any time or reject to answer any questions. For CD4 cell count, we also requested permissions from patients before extracting data from medical records.

Results

Table 1 summarizes the sociodemographic characteristics of respondents. The majority attained less than high school (66.0%), lived in urban areas (70.6%), and lived with spouse/ partners (66.5%). Nearly 40% perceived barriers in traveling to ART clinics. The average age of males (39.3 years, SD =8.0) was higher than that of females (36.8 years, SD =8.4; P<0.01).
Table 1

Sociodemographic characteristics of respondents

CharacteristicsMale
Female
Total
P-value
n%n%n%
Education0.60
Less than high school19465.512166.931566.0
High school8930.14927.113828.9
More than high school134.4116.1245.3
Geographic location0.6
Rural9231.04926.814129.4
Urban8428.35831.714229.6
Mountainous12140.77641.519741.0
Marital status<0.01
Single5919.9168.87515.7
Living with spouse/partner21873.710055.031866.5
Divorced/separated/widowed196.46636.38517.8
Difficulty in traveling to the clinic0.08
Yes10636.18044.218639.2
No18864.010155.828960.8

MeanSDMeanSDMeanSD

Age (years)39.38.036.88.438.48.3<0.01
Most of the respondents had an initial CD4 cell count of ≥350 cells/mm3 (53.0%), in which male respondents had higher baseline CD4 cell count than female respondents (P<0.01), which is summarized in Table 2. With regard to HIV stages, asymptomatic patients were dominant (82.6%) and only 3.9% were in AIDS stage. The average ART duration was 3.8 (SD =2.5), and approximately 93% were completely satisfied with ART treatment outcomes. The proportion of patients having methadone maintenance treatment (MMT) was 16.5%, in which the percentage of patients co-treated with MMT was higher in females than that in males (P<0.01).
Table 2

Clinical characteristics of respondents

CharacteristicsMale
Female
Total
P-value
n%n%n%
Initial CD4 count (cells/mm3)<0.01
<2007733.12116.39827.1
200–3505121.92116.37219.9
≥35010545.18767.419253.0
Last CD4 count (cells/mm3)<0.01
<2004519.31310.15816.0
200–3505523.61511.67019.3
≥35013357.110178.323464.6
HIV stage0.30
Asymptomatic15674.610579.626176.5
Symptomatic5325.42720.58023.5
Co-treatment with MMT<0.01
Yes7124.731.97416.5
No21775.415898.137583.5
Treatment satisfaction0.20
Totally satisfied25791.117095.042792.6
Partially satisfied248.584.5326.9
Not satisfied10.410.620.4

MeanSDMeanSDMeanSD

ART duration3.62.44.22.73.82.50.06

Abbreviations: ART, antiretroviral therapy; MMT, methadone maintenance treatment.

The assessments of risk behaviors are summarized in Table 3. One-third of respondents were hazardous drinkers (38.5%), and more than half of patients reported that they were current smokers. Besides, 44.8% used to addict to the illicit drug, and 14.1% currently used the drug. The history of drug injection was commonly reported among respondents (41.2%). Rates of various health risk behaviors, such as hazard drinking, smoking, history of drug use/drug injection, and current drug use, were significantly higher among males in comparison with females (P<0.01).
Table 3

Health-related risk behaviors of respondents

CharacteristicsMale
Female
Total
P-value
n%n%n%
Hazard drinking<0.01
Yes17257.9126.618438.5
No12542.116993.429461.5
Current smoking<0.01
Yes21875.1773.8522547.67
No7224.8317596.1524752.33
History of drug use<0.01
Yes20870.073.821544.8
No8930.017696.226555.2
Current drug use0.68
Yes14068.6457.114468.3
No6431.4342.96731.8
History of drug injection<0.01
Yes19164.863.319741.2
No10435.317796.728158.8
Table 4 summarizes that the mean percentage of adherence in the last month was 89.3 (SD =8.2). There were 45.5% patients achieving optimal adherence, 3.9% patient forgetting taking pills in the last 4 days, and 12.5% delaying taking pills in the last week. Table 5 summarizes that noncurrent smoking (coefficient =4.19, 95% CI 0.42–7.97), baseline CD4 count of at least 500 cells/mm3 (coefficient =4.35, 95% CI 0.58–8.13), and no traveling difficulties (coefficient =6.17, 95% CI 2.27–10.06) were strong predictors of increased VAS score. Meanwhile, mountainous residence was associated with suboptimal adherence (OR =5.34, 95% CI 2.81–10.16). In addition, female respondents were less likely to delay taking pills in the last 7 days (OR =0.19, 95% CI 0.07–0.52).
Table 4

Self-reported adherence to ART

CharacteristicsMale
Female
Total
P-value
n%n%n%
Optimal adherence<0.05
Yes11741.68951.720645.5
No16458.48348.324754.5
Forgot doses in the last 4 days0.34
Yes134.552.8183.9
No27495.517597.244996.2
Delayed taking pills in the last week<0.01
Yes4917.395.05812.5
No23482.717195.040587.5

MeanSDMeanSDMeanSD

VAS adherence score88.812.890.215.689.38.2<0.01

Abbreviations: ART, antiretroviral therapy; VAS, Visual Analog Scale.

Table 5

Factors associated with ART suboptimal adherence

CharacteristicsVAS score
Suboptimal adherence
Delayed taking pills in the last week
Coefficient95% CIOR95% CIOR95% CI
Sex (vs male)
Female0.63*(0.36–1.09)0.19**(0.07–0.52)
Location (vs urban)
Mountainous−4.87***(−9.00 to −0.74)5.34**(2.81–10.16)0.44***(0.19–1.00)
Employment (vs unemployed)
Employed−5.29***(−9.62 to −0.96)1.95***(1.06–3.60)
Education (vs, high school)
High school−2.84(−6.79 to 1.12)
.High school8.02*(−1.25 to 17.30)
Travel obstacles (vs yes)
No6.17**(2.27–10.06)0.70(0.41–1.19)0.28**0.14–0.58
Current smoking (vs yes)
No4.19***(0.42–7.97)
Initial CD4 count (vs <500 cell/mm3)
≥500 cell/mm34.35***(0.58–8.13)0.35**(0.17–0.72)
Last CD4 count (vs <500 cell/mm3)
≥500 cell/mm32.02*(0.93–4.43)

Notes:

P<0.1;

P<0.01;

P<0.05.

Abbreviations: ART, antiretroviral therapy; VAS, Visual Analog Scale.

Discussion

The current study endorses the high prevalence of ART suboptimal adherence among HIV/AIDS patients in the context of early ART eligibility in Vietnam. Mountainous residence, travel difficulties, and current smoking were strong predictors of suboptimal adherence. In contrast, being females and having initial CD4 counts of at least 500 cell/mm3 were associated with optimal adherence. The suboptimal adherence rate was considerably higher in comparison with previously published studies in Vietnam.12,13 This may be due to the data collection time as we conducted this study after the implementation of early ART initiation program. Literature has highlighted that HIV individuals might be less motivated to comply with ART regimens when they are clinically asymptomatic.11,18 This hypothesis requires further studies to elaborate the potential mechanisms of how physical health status could predict ART compliance. Another potential justification was that early ART initiation could increase treatment costs for CD4/viral load tests and travels. A prior study in Vietnam indicated that the amount of willingness to pay for CD4/viral load testing was only a fraction of the current cost.19 This highlights the importance of financial mobilization to ensure the quality, adherence, and treatment outcomes, especially in the context of universal ART program in Vietnam. The regression model showed that female patients were more likely to comply with treatment regimens. The result was in line with various studies in China,20 sub-Saharan Africa, and Asia,21 while contradictory results were affirmed in several studies in the USA,22 British Columbia, and Canada.23 The heterogeneity across studies, perhaps, could be explained by the sociocultural differences. In many Asian countries, husband–wife HIV transmission was highly prevalent due to the acceptance of husband’s extramarital sex, delayed notification of husbands’ HIV/AIDS status, and unawareness of husband’s promiscuity.24 Thus, we supposed that the passive HIV/AIDS infection motivated women to comply with ART regimens – the lifesaving. Besides, men have greater risks of diverse HIV risk behaviors such as multiple types of drug abuse,25 alcohol use,26 and tobacco use,27 which were significant predictors of suboptimal adherence.22,23,28,29 Of note, mountainous residents were less likely to achieve optimal adherence. This issue may be due to socioeconomic disadvantages. A study by Tran et al in Vietnam revealed that ethnic minorities had lower access, adherence, and outcome of ART services due to socioeconomic inequity.30 Besides, we observed a positive correlation between poor adherence and travel difficulty. We highly recommend the integration of ART in commune health centers to elevate the service accessibility. In fact, Vietnam successfully piloted the treatment 2.0 initiatives in 2011 regarding the joint initiative of WHO and the Joint United Nation Program on HIV/AIDS (UNAIDS). Five main elements included decentralizing and integrating HIV services into commune health centers; HIV testing, care, and treatment at the commune level; early diagnosis with quick tests; optimizing treatment regimens; and mobilizing community participation. Our findings embraced the expansion of this model in hard-to-reach locations. It was noteworthy that those with high initial CD4 cell counts (>500 cell/mm3) were more likely to achieve optimal adherence. We assumed that those with clinical symptoms might receive multiple drug regimens, leading to a higher likelihood of ART non-adherence due to pill burdens and drug interactions.31 Some previous studies suggested that higher pre-ART CD4 cell count was associated with decreased mortality, improved treatment outcomes, and increased adherence.32–34 Our findings supported the national guideline on HIV/AIDS care which increased the threshold of CD4 cell counts for ART initiation from <350 cell/mm3 in 2011 to <500 cell/mm3 in 2015, and most recently, enrolled all HIV-diagnosed patients in ART regardless of CD4 counts. Our study affirmed smoking as a strong predictor of suboptimal adherence. It has been well evident that HIV-infected smokers are at greater risks of low CD4 counts, pulmonary infections, and lung cancer;35 and nicotine dependence could alleviate health benefits of ART adherence.36 While HIV-infected individuals are at greater risks of smoking than the general population,37 tobacco cessation has been not properly paid attention in the HIV-infected group. Thus, it is called for pragmatic smoking cessation programs to minimize the disease burdens and promote the treatment outcomes among HIV-infected patients. The core implication of our study is that early ART initiation should be parallel with appropriate resource allocation and service delivery. This, perhaps, could be performed by mobilizing the government budget, including health insurance, and decentralizing/integrating HIV services into commune health centers. Besides, tobacco cessation programs should be implemented in ART clinics with dynamic forms such as behavioral therapies and nicotine replacement therapies. Our study has several strengths. First, this current study provided up-to-date evidence on the level of ART adherence and associated factors in the context of early treatment in Vietnam. Thus, this current study would contribute to the benefits of early ART initiation. Second, as we recruited patients from urban, rural, and mountainous locations, it allowed us to obtain the sample size with diverse socio-demographic backgrounds, increasing the generalizability of the study population. Apart from these advantages, this study was subjected to several limitations. Although the self-reported measure was the most convenient method to evaluate ART adherence,38 it might be subjected to recall and social desirability biases. Other direct methods such as therapeutic drug monitoring and biomarkers may promise more accurate results. Yet, costs and resources related to such methods should be taken into account. Besides, missing data might occur because patients could refuse to answer any questions or provide any information. To minimize missing data, interviewers explained clearly about the study purposes and emphasized the assurance of information confidentiality.

Conclusion

Our study endorsed the high prevalence of ART suboptimal adherence among HIV-infected patients. Optimal adherence was associated with female patients or patients who had high baseline CD4 count, while suboptimal adherence was linked with mountainous residence and current smoking. While we embrace early ART eligibility in Vietnam, it should be parallel with improved resource allocation and service delivery.
  29 in total

1.  Antiretroviral therapy refusal among newly diagnosed HIV-infected adults.

Authors:  Ingrid T Katz; Thandekile Essien; Edmore T Marinda; Glenda E Gray; David R Bangsberg; Neil A Martinson; Guy De Bruyn
Journal:  AIDS       Date:  2011-11-13       Impact factor: 4.177

2.  High coverage of ART associated with decline in risk of HIV acquisition in rural KwaZulu-Natal, South Africa.

Authors:  Frank Tanser; Till Bärnighausen; Erofili Grapsa; Jaffer Zaidi; Marie-Louise Newell
Journal:  Science       Date:  2013-02-22       Impact factor: 47.728

3.  The AUDIT alcohol consumption questions (AUDIT-C): an effective brief screening test for problem drinking. Ambulatory Care Quality Improvement Project (ACQUIP). Alcohol Use Disorders Identification Test.

Authors:  K Bush; D R Kivlahan; M B McDonell; S D Fihn; K A Bradley
Journal:  Arch Intern Med       Date:  1998-09-14

4.  Measuring adherence to antiretroviral therapy in a diverse population using a visual analogue scale.

Authors:  Thomas P Giordano; David Guzman; Richard Clark; Edwin D Charlebois; David R Bangsberg
Journal:  HIV Clin Trials       Date:  2004 Mar-Apr

5.  Gender differences in smoking behaviors in an Asian population.

Authors:  Yi-Wen Tsai; Tzu-I Tsai; Chung-Lin Yang; Ken N Kuo
Journal:  J Womens Health (Larchmt)       Date:  2008 Jul-Aug       Impact factor: 2.681

6.  Association of alcohol consumption and HIV surrogate markers in participants of the swiss HIV cohort study.

Authors:  Anna Conen; Qing Wang; Tracy R Glass; Christoph A Fux; Maria C Thurnheer; Christina Orasch; Alexandra Calmy; Enos Bernasconi; Pietro Vernazza; Rainer Weber; Heiner C Bucher; Manuel Battegay; Jan Fehr
Journal:  J Acquir Immune Defic Syndr       Date:  2013-12-15       Impact factor: 3.731

7.  The prevention and handling of the missing data.

Authors:  Hyun Kang
Journal:  Korean J Anesthesiol       Date:  2013-05-24

8.  Impact of Socioeconomic Inequality on Access, Adherence, and Outcomes of Antiretroviral Treatment Services for People Living with HIV/AIDS in Vietnam.

Authors:  Bach Xuan Tran; Jongnam Hwang; Long Hoang Nguyen; Anh Tuan Nguyen; Noah Reed Knowlton Latkin; Ngoc Kim Tran; Vu Thi Minh Thuc; Huong Lan Thi Nguyen; Huong Thu Thi Phan; Huong Thi Le; Tho Dinh Tran; Carl A Latkin
Journal:  PLoS One       Date:  2016-12-22       Impact factor: 3.240

9.  Adherence to antiretroviral therapy for HIV in sub-Saharan Africa and Asia: a comparative analysis of two regional cohorts.

Authors:  Rimke Bijker; Awachana Jiamsakul; Cissy Kityo; Sasisopin Kiertiburanakul; Margaret Siwale; Praphan Phanuphak; Sulaimon Akanmu; Romanee Chaiwarith; Ferdinand W Wit; Benedict Lh Sim; Tamara Sonia Boender; Rossana Ditangco; Tobias F Rinke De Wit; Annette H Sohn; Raph L Hamers
Journal:  J Int AIDS Soc       Date:  2017-03-03       Impact factor: 5.396

10.  Co-financing for viral load monitoring during the course of antiretroviral therapy among patients with HIV/AIDS in Vietnam: A contingent valuation survey.

Authors:  Quyen Le Thi Nguyen; Long Hoang Nguyen; Bach Xuan Tran; Huong Thi Thu Phan; Huong Thi Le; Hinh Duc Nguyen; Tho Dinh Tran; Cuong Duy Do; Cuong Manh Nguyen; Vu Thi Minh Thuc; Carl Latkin; Melvyn W B Zhang; Roger C M Ho
Journal:  PLoS One       Date:  2017-02-15       Impact factor: 3.240

View more
  7 in total

1.  Cost and Cost-Effectiveness of Incentives for Viral Suppression in People Living with HIV.

Authors:  Laura J Dunlap; Stephen Orme; Gary A Zarkin; David R Holtgrave; Catherine Maulsby; Andrew M Rodewald; August F Holtyn; Kenneth Silverman
Journal:  AIDS Behav       Date:  2021-08-26

2.  Factors Associated With Adherence To Anti-Retroviral Therapy Among People Living With HIV/AIDS At Wangaya Hospital In Denpasar, Bali, Indonesia: A Cross-Sectional Study.

Authors:  Ketut Suryana; Hamong Suharsono; I Gede Putu Jarwa Antara
Journal:  HIV AIDS (Auckl)       Date:  2019-11-19

3.  HIV/AIDS treatment funding system to support the people affected by HIV/AIDS in Surakarta, Indonesia.

Authors:  Argyo Demartoto; Bhisma Murti; Siti Zunariyah
Journal:  SAHARA J       Date:  2021-12

4.  Smartphone Use and Willingness to Pay for HIV Treatment-Assisted Smartphone Applications among HIV-Positive Patients in Urban Clinics of Vietnam.

Authors:  Thu Minh Bui; Men Thi Hoang; Toan Van Ngo; Cuong Duy Do; Son Hong Nghiem; Joshua Byrnes; Dung Tri Phung; Trang Huyen Thi Nguyen; Giang Thu Vu; Hoa Thi Do; Carl A Latkin; Roger C M Ho; Cyrus S H Ho
Journal:  Int J Environ Res Public Health       Date:  2021-02-04       Impact factor: 3.390

Review 5.  An update on drug-drug interactions between antiretroviral therapies and drugs of abuse in HIV systems.

Authors:  Nuti Desai; Leah Burns; Yuqing Gong; Kaining Zhi; Asit Kumar; Nathan Summers; Santosh Kumar; Theodore J Cory
Journal:  Expert Opin Drug Metab Toxicol       Date:  2020-08-31       Impact factor: 4.481

6.  Effects of substance use on monetary delay discounting among people who use stimulants with and without HIV: An ecological momentary assessment study.

Authors:  Yunan Xu; Sheri L Towe; Shakiera T Causey; Paul A Dennis; Christina S Meade
Journal:  Exp Clin Psychopharmacol       Date:  2020-08-06       Impact factor: 3.157

7.  Using mobile health technologies to test the association of cocaine use with sexual desire and risky sexual behaviors among people with and without HIV who use illicit stimulants.

Authors:  Yunan Xu; Sheri L Towe; Shakiera T Causey; Christina S Meade
Journal:  Drug Alcohol Depend       Date:  2021-05-20       Impact factor: 4.852

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.