The Impact of Youth-Friendly Structures of Care on Retention among HIV-Infected Youth

Limited data exist on how structures of care impact retention among youth living with HIV (YLHIV). We describe the availability of youth-friendly structures of care within HIV Research Network (HIVRN) clinics and examine their association with retention in HIV care. Data from 680 15- to 24-year-old YLHIV receiving care at 7 adult and 5 pediatric clinics in 2011 were included in the analysis. 

The primary outcome was retention in care, defined as completing ≥2 primary HIV care visits ≥90 days apart in a 12-month period. Sites were surveyed to assess the availability of clinic structures defined a priori as 'youth-friendly'. Univariate and multivariable logistic regression models assessed structures associated with retention in care. 

Among 680 YLHIV, 85% were retained. Nearly half (48%) of the 680 YLHIV attended clinics with youth-friendly waiting areas, 36% attended clinics with evening hours, 73% attended clinics with adolescent health-trained providers, 87% could email or text message providers, and 73% could schedule a routine appointment within 2 weeks. Adjusting for demographic and clinical factors, YLHIV were more likely to be retained in care at clinics with a youth-friendly waiting area, evening clinic hours, and providers with adolescent health training. 

Youth-friendly structures of care impact retention in care among YLHIV. Further investigations are needed to determine how to effectively implement youth-friendly strategies across clinical settings where YLHIV receive care.

Purchase full article at:   http://goo.gl/SwzQ6G

By:  Lee L1, Yehia BR2, Gaur AH3, Rutstein R4, Gebo K5, Keruly JC5, Moore RD5, Nijhawan AE6, Agwu AL5.

• 1 Divisions of General Pediatrics and Adolescent Medicine, Johns Hopkins School of Medicine , Baltimore, Maryland.
• 2 Department of Infectious Diseases, University of Pennsylvania Perelman School of Medicine , Philadelphia, Pennsylvania.
• 3 Department of Infectious Diseases, St. Jude Children's Research Hospital , Memphis, Tennessee.
• 4 Division of General Pediatrics, Children's Hospital of Philadelphia , Philadelphia, Pennsylvania.
• 5 Divisions of Infectious Diseases, Johns Hopkins School of Medicine , Baltimore, Maryland.
• 6 Department of Internal Medicine, University of Texas Southwestern Medical Center , Dallas, Texas. 
• AIDS Patient Care STDS. 2016 Apr;30(4):170-7. doi: 10.1089/apc.2015.0263. Epub 2016 Mar 16.

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Baseline Clinical Characteristics, Antiretroviral Therapy Use, and Viral Load Suppression among HIV-Positive Young Men of Color Who Have Sex with Men

Given the continued high incidence of HIV infection in the United States among racial/ethnic minority young men who have sex with men (YMSM), and an appreciation that antiretroviral therapy (ART) can provide personal and public health benefits, attention is needed to enhance the detection of HIV-infected youth and engage them in medical care and support services that encourage sustained HIV treatment and suppression of viremia. Poor retention in clinical care has been associated with higher mortality, an increase in HIV RNA, and decreased CD4 cell count. 

The goal of the current study was to evaluate the health care utilization and health outcomes of HIV-infected racial/ethnic minority YMSM enrolled in an outreach, linkage, and retention study funded by the Health Resources and Services Administration (HRSA) HIV/AIDS Bureau (HAB). We hypothesized that among racial/ethnic minority YMSM, baseline CD4 counts and usage of ART are influenced by age, race, drug and alcohol use, and mental health symptoms. 

Overall, 155 subjects had at least a baseline CD4 count recorded at study entry. There was a low rate of ART use in this population with only one-half of the cohort with CD4 counts ≤350 cells/mm³ being prescribed ART to treat their infection. However, of those youth who were started on ART, the majority (74%) did achieve undetectable viral loads (<400 copies). 

Given the continued increase in cases of HIV infection among racial/ethnic minority YMSM, efforts to increase both the provision of ART and support services that encourage adherence in this population are warranted.

Full article at:   http://goo.gl/WVmIZm

By:  Lisa B. Hightow-Weidman, M.D., M.P.H.,1 Karen Jones, M.S.,2 Gregory Phillips, II, M.S.,2 Amy Wohl, Ph.D.,3 andThomas P. Giordano, M.D., M.P.H.4, for The YMSM of Color SPNS Initiative Study Group

¹University of North Carolina, Chapel Hill, Chapel Hill, North Carolina.

²The George Washington University School of Public Health and Health Services, Washington, District of Columbia.

³Los Angeles County Department of Public Health, Los Angeles, California.

⁴Baylor College of Medicine and the Thomas Street Health Center, Houston, Texas.

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Social & Clinical Attributes of Patients Who Restart Antiretroviral Therapy in Central & Copperbelt Provinces, Zambia

Background

About 30 % of the patients initiated on antiretroviral therapy in Zambia default treatment. Some of these patients later restart treatment; however, the characteristics of these patients have not been well described and documented. The aim of this study was to describe and document the socio-demographic and clinical characteristics of patients who default and restart antiretroviral therapy, and to determine the socio-demographic characteristics associated with CD4 count response at 6 and 24 months of restarting antiretroviral therapy.

Methods

A longitudinal retrospective analysis was performed on data from 535 adult patients restarting antiretroviral therapy in 2009 and 2010 at five antiretroviral therapy centres in Copperbelt and Central provinces of Zambia. To determine the association between the socio-demographic characteristics and CD4 cell count, quantile regression models were used.

Results

Older age above 45 years was associated with a significantly lower CD4 cell response by 38.1 cells/mm³ compared to the younger age (15–29 years). Patients in formal employment and self-employment gained significantly higher CD4 cells than those unemployed. In addition, baseline CD4 count, type of treatment, WHO staging, total duration on treatment and duration lost to follow-up were found to be strong predictors of CD4 cell count at 6 and 24 months after restarting antiretroviral therapy treatment.

Conclusion

Age and occupation were the only socio-demographic characteristics predicting CD4 count in the patients at 6 months after restarting antiretroviral therapy after adjusting for other confounding clinical variables.  

Below:  Boxplots of Interquartile range of CD4 count at restarting ART, 6 and 24 months after restaring ART

Full article at:  http://goo.gl/8P145h

By:  Chama Mulubwa, Oliver Mweemba, Patrick Katayamoyo, and Hikabasa Halwindi

Department of Public Health, School of Medicine, University of Zambia, PO Box 50110, Lusaka, Zambia

FHI 360, Plot 2374, Farmers Village, ZNFU Complex, Lusaka, Zambia

BMC Public Health. 2016; 16: 289.

Published online 2016 Mar 29. doi:  10.1186/s12889-016-2922-3

Department of Public Health, School of Medicine, University of Zambia, PO Box 50110, Lusaka, Zambia

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Adherence to Antiretroviral Therapy & Its Determinants among Persons Living with HIV/AIDS in Bayelsa State, Nigeria

BACKGROUND:

A high level of adherence is required to achieve the desired outcomes of antiretroviral therapy. There is paucity of information about adherence to combined antiretroviral therapy in Bayelsa State of southern Nigeria.

OBJECTIVES:

The objectives of the study were to determine the level of adherence to combined antiretroviral therapy among the patients, evaluate the improvement in their immune status and identify reasons for sub-optimal adherence to therapy.

METHODS:

The cross-sectional study involved administration of an adapted and pretested questionnaire to 601 consented patients attending the two tertiary health institutions in Bayesla State.

NIGERIA:

The Federal Medical Centre, Yenagoa and the Niger-Delta University Teaching Hospital Okolobiri. The tool was divided into various sections such as socio-demographic data, HIV knowledge and adherence to combined antiretroviral therapy. Information on the patient's CD4+ T cells count was retrieved from their medical records. Adherence was assessed by asking patients to recall their intake of prescribed doses in the last fourteen days and subjects who had 95-100% of the prescribed antiretroviral drugs were considered adherent.

RESULTS:

Three hundred and forty eight (57.9%) of the subjects were females and 253 (42.1%) were males. The majority of them, 557 (92.7%) have good knowledge of HIV and combined anti-retroviral therapy with a score of 70.0% and above. A larger proportion of the respondents, 441 (73.4%), had ≥95% adherence. Some of the most important reasons giving for missing doses include, "simply forgot" 147 (24.5%), and "wanted to avoid the side-effects of drugs" 33(5.5%). There were remarkable improvements in the immune status of the subjects with an increment in the proportion of the subjects with CD4+ T cells count of greater than 350 cells/mm3 from 33 (5.5%) at therapy initiation to 338 (56.3%) at study period (p<0.0001).

CONCLUSION:

The adherence level of 73.4% was low which calls for intervention and improvement. The combined antiretroviral therapy has significantly improved the immune status of the majority of patients which must be sustained. "Simply forgot" was the most important reason for missing doses.

Reasons for sub optimal adherence to combined antiretroviral therapy

Reasons a	Hospital/Sex of respondents N (%)						Total	p-value
	FMC			NDUTH
	Male	Female	Sub-Total	Male	Female	Sub-Total
	Simply forgot	20 (3.3)	62 (10.3)	82 (13.6)	24 (4.0)	40 (6.7)			64 (10.6)	147 24.5)	0.0002
Too many drugs to take	6 (1.0)	1 (0.2)	7 (1.2)	9 (1.5)	5 (0.8)	14 (2.3)	21 (3.5)
Wanted to avoid side-effects	5 (0.8)	12 (2.0)	17 (2.8)	6 (1.0)	5 (0.8)	16 (2.7)	33 (5.5)
Felt Sick	1 (0.2)	4 (0.7)	5 (0.8)	1 (0.2)	5 (0.8)	6 (1.0)	11 (1.8)
Felt depressed/down	2 (0.3)	2 (0.3)	4 (0.7)	2 (0.3)	3 (0.5)	5 (0.8)	9 (1.5)
Felt asleep	3 (0.5)	8 (1.3)	11 (1.8)	2 (0.3)	13 (2.2)	15 (2.5)	26 (4.3)
Drank alcohol	0 (0.0)	1 (0.2)	1 (0.2)	2 (0.3)	6 (1.0)	8 (1.3)	9 (1.5)
Fasting	2 (0.3)	4 (0.7)	6 (1.0)	5 (0.8)	2 (0.3)	7 (1.2)	13 (2.2)
Ran out of drugs	5 (0.8)	13 (2.2)	18 (3.0)	0 (0.0)	2 (0.3)	2 (0.3)	20 (3.3)
Felt better	21 (3.5)	0 (0.0)	21 (3.5)	7 (1.2)	0 (0.0)	7 (1.2)	28 (4.7)
Too busy with other things	17 (2.8)	9 (1.5)	26 (4.3)	7 (1.2)	10 (1.7)	17 (2.8)	43 (7.2)
Fear of others noticing	1 (0.2)	0 (0.0)	1 (0.2)	2 (0.3)	5 (0.8)	7 (1.2)	8 (1.3)
Problems taking drug at specific time	1 (0.2)	0 (0.0)	1 (0.2)	2 (0.3)	5 (0.8)	7 (1.2)	8 (1.3)
Did not want other people to notice	1 (0.2)	8 (1.3)	9 (1.5)	3 (0.5)	9 (1.5)	12 (2.0)	21 (3.5)
Lack of transport fare to get the drug	5 (0.8)	4 (0.7)	9 (1.5)	1 (0.2)	5 (0.8)	6 (1.0)	15 (2.5)
Not applicable	49 (8.2)	53 (8.8)	112 (18.6)	34 (5.7)	53 (8.8)	87 (14.5)	189 (31.4)

aFMC versus NDUTH: chi-square= 41.988, df=15, p<0.0002

Full article at:   http://goo.gl/auQwD4

By:  Suleiman IA1, Momo A2.

• 1Department of Clinical Pharmacy and Pharmacy Practice. Faculty of Pharmacy, Niger Delta University , Wilberforce Island, Bayelsa State ( Nigeria ). suleimanismail1@gmail.com.
• 2Deputy Director, Pharmacy Department, Federal Medical Centre, Yenagoa, Bayelsa State, ( Nigeria ). pharmandymomo@yahoo.com.
• Pharm Pract (Granada). 2016 Jan-Mar;14(1):631. doi: 10.18549/PharmPract.2016.01.631. Epub 2016 Mar 15.

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Factors associated with HIV Viral Load "Blips" & the Relationship Between Self-Reported Adherence & Efavirenz Blood Levels on Blip Occurrence

BACKGROUND:

The uncertain etiology of HIV viral load (VL) blips may lead to increased use of clinical resources. We evaluated the association of self-reported adherence (SRA) and antiretroviral (ART) drug levels on blip occurrence in US Military HIV Natural History Study (NHS) participants who initiated the single-tablet regimen efavirenz/emtricitabine/tenofovir disoproxil fumarate (EFV/FTC/TDF).

METHODS:

ART-naïve NHS participants started on EFV/FTC/TDF between 2006 and 2013 who achieved VL suppression (<50 copies/mL) within 12 months and had available SRA and stored plasma samples were included. Participants with viral blips were compared with those who maintained VL suppression without blips. Untimed EFV plasma levels were evaluated on consecutive blip and non-blip dates by high performance liquid chromatography, with a level ≥1 mcg/mL considered therapeutic. SRA was categorized as ≥85 or <85 %. Descriptive statistics were performed for baseline characteristics and univariate and multivariate Cox proportional hazard models were used to assess the relationship between covariates and blip occurrence.

RESULTS:

A total of 772 individuals met inclusion criteria, including 99 (13 %) blip and 673 (87 %) control participants. African-American was the predominant ethnicity and the mean age was 29 years for both groups. SRA ≥ 85 % was associated with therapeutic EFV levels at both blip and non-blip time points (P = 0.0026); however no association was observed between blips and SRA or EFV levels among cases. On univariate analysis of cases versus controls, blips were associated with higher mean pre-treatment VL (HR 1.45, 95 % CI 1.11-1.89) and pre-treatment CD4 count <350 cells/µL (68.1 vs 49.7 %). Multivariate analysis also showed that blips were associated with a higher mean VL (HR 1.42, 95 % CI 1.08-1.88; P = 0.0123) and lower CD4 count at ART initiation, with CD4 ≥500 cells/µL having a protective effect (HR 0.45, 95 % CI 0.22-0.95; P = 0.0365). No association was observed for demographic characteristics or SRA.

CONCLUSION:

Blips are commonly encountered in the clinical management of HIV-infected patients. Although blip occurrence was not associated with SRA or EFV blood levels in our study, blips were associated with HIV-related factors of pre-ART high VL and low CD4 count. Additional studies are needed to determine the etiology of blips in HIV-infected patients.

Self-reported adherence

Characteristic	All	Blip group	Control group	P value
Total self-reported adherence (%)				0.1603
≥85	597 (96.2)	84 (97.7)	513 (96.1)
<85	23 (3.8)	2 (2.3)	21 (3.9)
Last time missed a dose				0.2097
Last week	100 (16.1)	15 (17.4)	85 (15.9)
Longer than last week	521 (83.9)	71 (82.6)	450 (84.1)
Missed a dose in the last weekend				0.1528
No	572 (93.2)	80 (93.0)	492 (93.2)
Yes	42 (6.8)	6 (7.0)	36 (6.8)
Total missed doses in the last 2 weeks				0.1297
0	489 (78.6)	68 (78.2)	421 (78.7)
1 or more	127 (20.4)	17 (19.5)	110 (20.6)
All doses	5 (0.8)	2 (2.3)	3 (0.6)
Don’t know	1 (0.2)	0 (0.0)	1 (0.2)

Data expressed as N (%) or mean (SD)

Full article at:   http://goo.gl/FuL78U

By:  Farmer A1, Wang X2, Ganesan A3, Deiss RG4, Agan BK2, O'Bryan TA5, Akers K6, Okulicz JF7.

• 1Infectious Disease Service, San Antonio Military Medical Center, 3551 Roger Brooke Drive, Fort Sam Houston, TX USA.
• 2Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD USA ; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA.
• 3Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD USA ; Walter Reed National Military Medical Center, Bethesda, MD USA ; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA.
• 4Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD USA ; Division of Infectious Diseases, Naval Medical Center of San Diego, San Diego, CA USA ; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA.
• 5Infectious Disease Service, San Antonio Military Medical Center, 3551 Roger Brooke Drive, Fort Sam Houston, TX USA ; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD USA ; Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD USA.
• 6Infectious Disease Service, San Antonio Military Medical Center, 3551 Roger Brooke Drive, Fort Sam Houston, TX USA ; United States Army Institute of Surgical Research, Fort Sam Houston, TX USA.
• 7Infectious Disease Service, San Antonio Military Medical Center, 3551 Roger Brooke Drive, Fort Sam Houston, TX USA ; Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, MD USA. 
• AIDS Res Ther. 2016 Mar 22;13:16. doi: 10.1186/s12981-016-0100-4. eCollection 2016.

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